Conditions: Migraine
Allocation: NON_RANDOMIZED | Intervention model: PARALLEL
Enrollment: 16
Healthy volunteers: yes

Brief summary:
This is a multi-center, open-label, non-randomized, parallel-group, adaptive, single dose study.

This study will enroll up to 32 participants using an adaptive design that can include up to 3 groups of 8 participants with different degree of renal impairment and one group of 8 control participants with normal renal function.

Screening data will be reviewed to determine participant eligibility. Participants who meet all inclusion criteria and none of the exclusion criteria will be entered in the study.

First, approximately 16 participants will be enrolled with severe renal impairment and matched participants with normal renal function. There will be 8 participants in each of the following groups based on renal function at screening:

* Group 1: Healthy participants with normal renal function (estimated glomerular filtration rate \[eGFR\] ≥ 90 milliliters per minute per 1.73 meters squared \[mL/min/1.73m²\])
* Group 2: Severe renal impairment participants (eGFR \< 30 mL/min/1.73m²) Based on safety and pharmacokinetic (PK) results from participants with severe renal impairment (Group 2), Group 3 (Moderate Renal Impairment) and Group 4 (Mild Renal Impairment) will be enrolled if substantial change in the exposure of lasmiditan is observed in participants with severe renal impairment.

Detailed description:

Arms:
arm 1: Participants received single 200 milligrams (mg) oral tablet of lasmiditan. arm 2: Participants received single 200 mg oral tablet of lasmiditan.

Interventions: intervention 1: Lasmiditan
Intervention descriptions: intervention 1: 200 mg, single oral tablet

Protocol document:
Prot_000.pdf: 
Protocol H8H-CD-LAHN (V1) (CUD-P4-001 (COL MIG-113))
A Phase I, Multicenter, Open-Label, Parallel-Group Adaptive Pharmacokinetic 
Single Dose Study of Oral Lasmiditan in Subjects With Normal and Impaired Renal 
Function
NCT03009162 
Approval Date: 6-Jan-2017


 
 
 
A Phase I, Multicenter, Open-Label, Parallel-Group Adaptive Pharmacokinetic Single 
Dose Study of Oral Lasmiditan in Subjects with Normal and Impaired Renal Function 
 
Protocol Number: 
CUD-P4-001 (COL MIG-113) 
Investigational Product: 
Lasmiditan 
Sponsor: 
CoLucid Pharmaceuticals, Inc. 
222 Third Street 
Suite 1320 
Cambridge, MA, USA, 02142 
Sponsor’s contact person: 
Tel. 
Cell.
Email. 
 
 
 
Protocol Version 
Date 
1.0 
Original 
2016/12/01 
2.0 
Amendment 01 
2017/01/06 
 
COMPLIANCE 
The study will be conducted in accordance with standards of Good Clinical Practice, as defined 
by the International Conference on Harmonisation and all applicable federal and local 
regulations. 
 
CONFIDENTIALITY STATEMENT 
The information provided in this document is strictly confidential and is available for review to investigator(s) 
and to the appropriate Independent Ethics Committee (IEC) or Institutional Review Board (IRB). It may not be 
used, divulged, published or otherwise disclosed without the written authorization from Algorithme Pharma or 
the sponsor. 
Algorithme Pharma 
Head Office 
575 Armand-Frappier  
Blvd. 
Laval (Quebec) H7V 4B3 
Canada 
www.algopharm.com 
Tel. : (450) 973-6077 
Fax : (450) 973-7866 
PPD
PPD
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TABLE OF CONTENTS 
1. INTRODUCTION .............................................................................................................................................. 14 
1.1. Background ................................................................................................................................................... 14 
1.2. Nonclinical Studies ....................................................................................................................................... 14 
1.3. Pharmacokinetics .......................................................................................................................................... 14 
1.4. Clinical Information ...................................................................................................................................... 15 
1.5. Study Rationale ............................................................................................................................................. 15 
2. STUDY OBJECTIVES ...................................................................................................................................... 15 
2.1. Primary Objective ......................................................................................................................................... 15 
2.2. Secondary Objectives .................................................................................................................................... 15 
3. STUDY DESIGN ................................................................................................................................................ 16 
3.1. General Study Design .................................................................................................................................... 16 
3.2. Number of Centers and Subjects ................................................................................................................... 16 
3.3. Schedule of Drug Administration .................................................................................................................. 16 
4. SUBJECT SELECTION .................................................................................................................................... 17 
4.1. Study Population ........................................................................................................................................... 17 
4.2. Inclusion Criteria ........................................................................................................................................... 17 
4.3. Exclusion Criteria .......................................................................................................................................... 18 
4.4. Withdrawal Criteria ....................................................................................................................................... 21 
5. STUDY TREATMENTS .................................................................................................................................... 22 
5.1. Description and Handling of Study Treatments ............................................................................................ 22 
5.1.1. Formulation of Test Product .................................................................................................................. 22 
5.1.2. Packaging and Labeling ......................................................................................................................... 22 
5.1.3. Storage and Handling ............................................................................................................................. 23 
5.2. Method of Assigning Subjects to Treatment Groups .................................................................................... 23 
5.3. Blinding ......................................................................................................................................................... 23 
5.4. Dosing and Administration ........................................................................................................................... 23 
5.4.1. Dispensing .............................................................................................................................................. 23 
5.4.2. Administration Instructions .................................................................................................................... 23 
5.4.3. Treatment Compliance ........................................................................................................................... 24 
5.4.4. Study Drug Accountability..................................................................................................................... 24 
5.5. Prior and Concomitant Medication ............................................................................................................... 24 
5.6. Study-Specific Restrictions ........................................................................................................................... 26 


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6. STUDY PROCEDURES AND GUIDELINES................................................................................................. 26 
6.1. Study Procedures ........................................................................................................................................... 31 
6.1.1. Physical Examination ............................................................................................................................. 31 
6.1.2. C-SSRS Questionnaire ........................................................................................................................... 31 
6.1.3. Vital Signs .............................................................................................................................................. 31 
6.1.4. Laboratory Evaluations .......................................................................................................................... 31 
6.1.4.1. Pregnancy Tests .............................................................................................................................. 32 
6.1.5. 12-Lead Electrocardiogram .................................................................................................................... 32 
6.1.6. Follow-up Call ....................................................................................................................................... 32 
6.1.7. Pharmacokinetic Sampling ..................................................................................................................... 32 
6.1.7.1. Sample processing, storage and shipping ........................................................................................ 33 
6.2. Bioanalytical Methods ................................................................................................................................... 33 
6.2.1. Aberrant values and retested samples .................................................................................................... 33 
6.2.2. Incurred sample reproducibility ............................................................................................................. 33 
6.3. Pharmacokinetic Measurements .................................................................................................................... 33 
7. ADVERSE EVENTS .......................................................................................................................................... 34 
7.1. Definitions ..................................................................................................................................................... 34 
7.1.1. Severity Assessment ............................................................................................................................... 35 
7.1.2. Causality Assessment ............................................................................................................................. 36 
7.2. Routine Reporting ......................................................................................................................................... 36 
7.3. Serious Adverse Event Reporting ................................................................................................................. 37 
8. STATISTICAL ANALYSIS .............................................................................................................................. 38 
8.1. Analysis Sets ................................................................................................................................................. 38 
8.1.1. Safety Analysis Set ................................................................................................................................ 38 
8.1.2. Pharmacokinetic Analysis Set ................................................................................................................ 38 
8.2. Sample Size Determination ........................................................................................................................... 39 
8.3. Statistical Analysis ........................................................................................................................................ 39 
8.3.1. Descriptive Analysis .............................................................................................................................. 39 
8.3.1.1. Safety Analyses ............................................................................................................................... 39 
8.3.1.2. Pharmacokinetic Endpoint Analyses ............................................................................................... 39 
8.3.2. Statistical Methodology ......................................................................................................................... 39 
8.3.2.1. Interim Analysis .............................................................................................................................. 40 
9. ETHICS ............................................................................................................................................................... 40 
9.1. Institutional Review Board (IRB) ................................................................................................................. 40 
9.2. Ethical Conduct of the Study ......................................................................................................................... 41 


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9.3. Participant Information and Consent ............................................................................................................. 41 
9.4. Subject Confidentiality .................................................................................................................................. 41 
10. DATA COLLECTION, RETENTION, AND MONITORING ...................................................................... 41 
10.1. Case Report Forms ........................................................................................................................................ 41 
10.2. Data Management and Processing ................................................................................................................. 42 
10.3. Quality Assurance ......................................................................................................................................... 42 
10.4. Record Retention ........................................................................................................................................... 42 
10.5. Monitoring of the Study ................................................................................................................................ 42 
11. ADMINISTRATIVE PROCEDURES .............................................................................................................. 42 
11.1. Adherence to Protocol ................................................................................................................................... 42 
11.2. Investigator Responsibilities ......................................................................................................................... 43 
11.3. Delegation of Investigator Duties .................................................................................................................. 43 
11.4. Premature Termination or Suspension of a Study ......................................................................................... 43 
11.5. Clinical Trial Application (CTA) .................................................................................................................. 43 
11.6. Exemption Application for Controlled Substances ....................................................................................... 43 
11.7. Publications ................................................................................................................................................... 43 
12. REFERENCES ................................................................................................................................................... 45 
APPENDIX 01 ........................................................................................................................................................... 46 


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LIST OF IN-TEXT TABLES 
Table 1: Formulation of Lasmiditan, 200 mg Tablets .................................................................. 22 
Table 2. Schedule of Assessments for all subjects ....................................................................... 28 
Table 3. Schedule of Pharmacokinetic Assessments .................................................................... 30 
Table 4. Pharmacokinetic Parameters ........................................................................................... 34 
Table 5. Adverse Event Relationship to Study Drug .................................................................... 36 


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STUDY SYNOPSIS 
Name of Sponsor/Company: 
CoLucid Pharmaceuticals, Inc. 
Name of Product: 
Lasmiditan 
Title of Study: 
A Phase I, Multicenter, Open-Label, Parallel-Group Adaptive 
Pharmacokinetic Single Dose Study of Oral Lasmiditan in Subjects 
with Normal and Impaired Renal Function 
Study Development Phase: 
Phase I 
Objectives: 
The primary objective of this study is to evaluate the 
pharmacokinetic (PK) profile of lasmiditan following a single oral 
200 mg dose in subjects with impaired renal function relative to 
matched, healthy controls with normal renal function. 
The secondary objective of this study is to assess the safety and 
tolerability of a single oral 200 mg dose of lasmiditan in subjects 
with normal and impaired renal function. 
Test Product: 
Lasmiditan 200 mg tablets 
Dose and Mode of 
Administration: 
Single dose of 200 mg of lasmiditan administered orally. 
Study Design: 
This is a multicenter, open-label, non-randomized, parallel-group, 
adaptive, single dose study.  
This study will enroll up to 32 subjects using an adaptive design 
that can include up to 3 groups of subjects with different degrees of 
renal impairment and one group of control subjects with normal 
renal function. 
First, subjects with severe renal impairment (Group 2) and matched 
subjects with normal renal function (Group 1) will be enrolled. 
There will be 8 subjects in each group. 
Based on safety and PK results from subjects with severe renal 
impairment, Group 3 (Moderate Renal Impairment) and Group 4 
(Mild Renal Impairment) will be enrolled if a substantial change in 
the exposure of lasmiditan is observed in subjects with severe renal 
impairment. There will be 8 subjects in each group. 
All subjects will participate in one treatment period and will receive 
a single dose of lasmiditan in the fasting state.  
Subjects will be confined to the clinic from 10 hours prior to dosing 
until 36 hours after drug administration. 
Duration of Study: 
Up to 38 days, including Screening. 
Study Population: 
Male and female adult subjects with normal renal function and 
male and female adult patients with mild, moderate, and severe 
renal impairment (according to the definition of the National 
Kidney Foundation) using the Modification of Diet in Renal 
Disease (MDRD) classification. 


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Planned Number of Subjects: 
The study is planned to enroll up to 32 subjects: 8 subjects with 
severe renal impairment, 8 subjects with moderate renal 
impairment, 8 subjects with mild renal impairment, and 8 with 
normal renal function. 
Subjects with moderate and mild renal impairment will be enrolled 
as determined by review of safety and PK data from previous 
groups. 
Main Criteria for Inclusion: 
• Male or female aged  ≥ 18 years 
• Body mass index  ≥ 18.50 to < 42.00 kg/m2 
• Negative screening for alcohol and drugs of abuse 
• Non clinically significant findings on 12-lead electrocardiogram 
(ECG) 
• For females, negative result on a pregnancy test 
Group 1 (Normal Renal Function) 
• Presence of normal renal function (eGFR ≥ 90 mL/min/1.73m2) 
• Subjects will be matched by age (±10 years), weight (±20%), 
and gender to the pooled mean values of subjects with the severe 
renal impairment. 
Group 2 (Severe Renal Impairment) 
• Presence of severe renal impairment (eGFR< 30 mL/min/1.73m2) 
Group 3 (Moderate Renal Impairment) 
• Presence of moderate renal impairment (eGFR 30-
59mL/min/1.73m2) 
Group 4 (Mild Renal Impairment) 
• Presence of mild renal impairment (eGFR 60-89 mL/min/1.73m2) 
Renal function for each subject will be determined at the Screening 
Visit, calculated using the MDRD classification. 
Procedures and Assessments 
Safety evaluations including vital signs (body temperature, pulse 
rate and blood pressure), physical exams, safety laboratory tests 
(general biochemistry, hematology, urinalysis, pregnancy test, drug, 
and alcohol screen), ECGs, adverse event (AE) collection, and 
concomitant medication recording will be conducted prior to and 
during the treatment period. 
PK blood samples will be collected at predose and for 36 hours 
after dosing on Day 1; 18 PK blood samples will be obtained from 
each patient/subject. 
PK urine samples will be collected at predose and for 36 hours after 
dosing on Day 1; 6 PK urine samples will be collected postdose 
from urine pooled during specified collection intervals.  
 


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Criteria for Evaluation: 
Safety:  
Safety will be evaluated by assessment of 12-lead safety ECGs, 
measurements of vital signs, physical examination and clinical 
laboratory tests at baseline and at various time points during the 
study, and by the documentation of AEs/concomitant medication. 
Pharmacokinetics: 
The following plasma and urine PK parameters of lasmiditan will 
be calculated: Cmax, Tmax, AUC0-T, AUC0-∞, AUC0-T/∞, λz, Thalf, 
ClTOT/F, VD/F, Ae(0-t), fe, Clr. 
Statistical Analyses: 
Safety data will be listed by subject and summarized by renal 
function group using frequency of event/abnormality or descriptive 
statistical summaries, as appropriate. 
PK parameters will be listed and summarized by group using 
descriptive statistics. Mean and individual plasma concentration-
time profiles will be presented graphically. 
A regression analysis in which the estimated renal function and the 
pharmacokinetic parameters are treated as continuous variables will 
be used to evaluate the relationship between renal function and the 
estimated pharmacokinetic parameters of lasmiditan. If the slope is 
found to be significantly different from zero (p < 0.05), and if more 
than one group of subjects with impaired renal function are 
enrolled, an analysis of variance will be performed to assess the 
difference in the PK parameter between the control and each group 
of subjects with impaired renal function. The 90% confidence 
interval of the difference will be calculated for each comparison. 


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LIST OF ABBREVIATIONS 
Term 
Definition 
AE 
Adverse event 
ANOVA 
Analysis of variance 
AUC 
Area under the curve 
BLQ 
Below the limit of quantification 
Cmax 
Maximum observed concentration 
CNS 
Central Nervous System 
CL 
Clearance 
C-SSRS 
Columbia Suicide Severity Rating Scale 
CV 
Coefficient of variation 
EOI 
End of infusion 
GeoCV% 
Percent geometric coefficient of variation 
GeoMean 
Geometric mean 
λZ 
Apparent terminal elimination rate constant 
IV 
Intravenous 
LLOQ 
Lower limit of quantification 
MDRD 
Modification of Diet in Renal Disease 
MRT∞ 
Mean residence time extrapolated to infinity 
MTD 
Maximum tolerated dose 
Min 
Minimum 
Max 
Maximum 
n 
Number of Observations 
NCA 
Noncompartmental analysis 
PD 
Pharmacodynamic 
PK 
Pharmacokinetic 
QA 
Quality assurance 
QC 
Quality control 
SAP 
Statistical analysis plan 
SD 
Standard deviation 
SE 
Standard error 
SEM 
Standard error of the mean 
SOP 
Standard Operating Procedure 
Thalf 
Apparent terminal elimination half-life 
Tmax 
Time to peak concentration 
U.S. 
United States 
 


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FACILITIES 
AUTHOR OF THE PROTOCOL: 
575 Armand-Frappier Blvd. 
Laval, Quebec, Canada 
H7V 4B3 
COORDINATING PRINCIPAL INVESTIGATOR: 
 
  
1200 Beaumont Ave. 
Mount-Royal, Quebec, Canada 
H3P 3P1 
Phone: 
 
PRINCIPAL INVESTIGATOR: 
Maisonneuve-Rosemont 
5415 de l'Assomption Bvl. 
Montreal, Quebec, Canada 
H1T 2M4 
Phone: 
 
SCREENING FACILITY: 
Algorithme Pharma  
1100 Beaumont Ave. 
Mount-Royal, Quebec, Canada 
H3P 3H5 
CIUSSS de l'est-de-l'île-de-Montréal - installation Hôpital 
Maisonneuve-Rosemont 
5305 de l'Assomption Bvl. 
Montreal, Quebec, Canada 
H1T 2M4 
MEDICAL LABORATORY*: 
Dynacare Solutions Santé 
4850 Dobrin St. 
Montreal, Quebec, Canada 
H4R 2P8 
*Samples may be outsourced to affiliated accredited laboratory facilities, if necessary. 
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BIOANALYTICAL FACILITY: 
Covance Laboratories 
3301 Kinsman Blvd, 
Madison, WI 53704, USA  
 
SCIENTIFIC AND REGULATORY FACILITY: 
Algorithme Pharma  
575 Armand-Frappier Blvd. 
Laval, Quebec, Canada 
H7V 4B3 
PROJECT MANAGEMENT: 
575 Armand-Frappier Blvd. 
Laval, Quebec, Canada 
H7V 4B3 
STATISTICAL FACILITY: 
1200 Beaumont Ave. 
Mount-Royal, Quebec, Canada 
H3P 3P1 
DATA MANAGEMENT FACILITY:
1200 Beaumont Ave. 
Mount-Royal, Quebec, Canada 
H3P 3P1 
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1.
INTRODUCTION
1.1. Background 
CoLucid Pharmaceuticals, Inc. (CoLucid) is developing lasmiditan (COL-144), a small molecule 
5-HT1F receptor agonist. The chemical name of lasmiditan (COL-144) is 2,4,6-trifluoro-N-[6-(1-
methylpiperidine-4-carbonyl)pyridine-2-yl]benzamide hemisuccinate.
Triptans, which are 5-HT1B/1D receptor agonists, are well established as an acute therapy for 
migraine, though they are not effective in all patients or attacks. Triptans were developed as 
cerebral vasoconstrictors, mediated via their affinity for 5-HT1B receptors located on vascular 
smooth muscle. Inherent in this mechanism of action is a liability for coronary vasoconstriction, 
and therefore, triptans are contraindicated in patients with cardiovascular disease. 
1.2. Nonclinical Studies 
Unlike triptans, lasmiditan is a highly selective and potent agonist at the 5-HT1F receptor with 
>470-fold higher affinity for the 5-HT1F receptor than for 5-HT1B/1D receptors. In preclinical
models (rodent) of relevance to migraine, agonists selective for 5-HT1F receptors inhibited
trigeminal nociceptive processing without affecting blood vessel tone. Unlike triptans, lasmiditan
did not constrict rabbit saphenous vein, an assay predictive of human coronary artery
constriction. Lasmiditan is under development as a neurally acting treatment for migraine
without the vasoconstrictor liability of triptans.
Safety pharmacology studies (central nervous system [CNS] respiratory, cardiovascular, and 
renal) employing single intravenous (IV) administration of lasmiditan indicated that 
administration of lasmiditan at the intended clinically effective exposure levels is unlikely to 
produce adverse effects on cardiovascular, respiratory or renal function. Based on observations 
in mice, the neural mechanism of action of lasmiditan may, with exposure to high doses, produce 
CNS effects such as increased sensitivity to auditory stimuli, analgesia, reduced activity, 
hypothermia, and anticonvulsant activity. However, there have been no comparable observations 
in clinical studies, apart from alleviation of headache pain. 
1.3. Pharmacokinetics 
Cmax and AUC for subjects dosed orally (200 mg) were also measured in a fed/fasted study (COL 
MIG-104). During fed conditions (394.7 ng/mL and 2244 ng*h/mL, respectively) PK parameters 
were slightly increased compared to the fasted condition (322.8 ng/mL and 1892 ng*h/mL, 
respectively). Hence, food had a minor effect on the PK of lasmiditan. 
The plasma clearance (~59 L/h IV and 160 L/h oral), and the high total volume of distribution 
(~300 L for IV and 1016 L for oral), indicated extensive distribution. There were no significant 
effects of gender or body weight on PK parameters. 
In vitro and in vivo metabolism studies have shown that the metabolic pathways of lasmiditan 
include N-oxidation, N-dealkylation, carbonyl oxidation, desaturation of the piperidine moiety, 
ketoreduction, or a combination of each. Up to 12 metabolites have been detected in human 
hepatocytes, of which none were unique to human. When examined in vivo using LC-MS/MS 


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analysis of human plasma samples from subjects receiving oral lasmiditan, three major 
metabolites (M7, M8, and (S,R)-M18) were detected. The relative proportions of metabolites to 
intact lasmiditan remained reasonably constant throughout the oral dose range studied and their 
PK were approximately linear. 
The half-life of the metabolites fell into two categories; the non-reduced metabolites with a half-
life similar to or only slightly longer than intact lasmiditan (~4.5 h), and the reduced metabolites 
with a half-life distinctly longer (>12 h) than that of lasmiditan. 
1.4. Clinical Information 
Five Phase 1 studies of lasmiditan have been completed in Europe using IV, sublingual, and oral 
formulations of lasmiditan in 213 healthy subjects. Two European Phase 2 studies have been 
completed with lasmiditan in the acute treatment of migraine. COL MIG-301 (SAMURAI) the 
first of two, Phase 3 randomized, double-blind, placebo controlled trials has completed in the 
United States. The second confirmatory study, COL MIG-302 (SPARTAN), is ongoing in the 
US, UK and Germany along with COL MIG-305, the open-label year long dosing study. 
Further information on the lasmiditan formulation, animal studies, and human studies can be 
found in the current Investigator’s Brochure. 
1.5. Study Rationale 
Lasmiditan is excreted through the kidneys. This study was designed to evaluate the effects of 
impaired renal function on lasmiditan PK parameters, and on its safety. This study will employ a 
targeted, reduced PK study design in which subjects enrolled will have severe renal impairment 
with a screening estimated eGFR < 30 mL/min/1.73m2. Data from these subjects will be 
compared to matched subjects with normal renal function (eGFR ≥ 90 mL/min/1.73m2). This 
approach is consistent with recommendations in the FDA Guidance for Industry entitled 
“Pharmacokinetics in Patients with Impaired Renal Function-Study Design, Data Analysis, and 
Impact on Dosing and Labeling”. Should substantial changes in exposure be observed, additional 
groups including subjects with lesser degrees of renal impairment will be enrolled.  
Results of this study may inform on lasmiditan dosing recommendation in patients with renal 
impairment. 
2. STUDY OBJECTIVES 
2.1. Primary Objective 
The primary objective of this study is to evaluate the pharmacokinetic profile of lasmiditan 
following a single oral 200 mg dose in subjects with impaired renal function relative to matched, 
healthy controls with normal renal function. 
2.2. Secondary Objectives 
The secondary objective of this study is to assess the safety and tolerability of a single oral 
200 mg dose of lasmiditan in subjects with normal and impaired renal function. 


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3. STUDY DESIGN 
3.1. General Study Design 
This is a multi-center, open-label, non-randomized, parallel-group, adaptive, single dose study.  
This study will enroll up to 32 subjects using an adaptive design that can include up to 3 groups 
of 8 subjects with different degree of renal impairment and one group of 8 control subjects with 
normal renal function. 
Screening data will be reviewed to determine subject eligibility. Subjects who meet all inclusion 
criteria and none of the exclusion criteria will be entered in the study. 
First, approximately 16 subjects will be enrolled with severe renal impairment and matched 
subjects with normal renal function. There will be 8 subjects in each of the following groups 
based on renal function at screening: 
• Group 1: Healthy subjects with normal renal function (eGFR ≥ 90 mL/min/1.73m2) 
• Group 2: Severe renal impairment subjects (eGFR < 30 mL/min/1.73m2) 
Based on safety and PK results from subjects with severe renal impairment (Group 2), Group 3 
(Moderate Renal Impairment) and Group 4 (Mild Renal Impairment) will be enrolled if 
substantial change in the exposure of lasmiditan is observed in subjects with severe renal 
impairment. There will be 8 subjects in each of the following groups based on renal function at 
screening: 
• Group 3: Moderate renal impairment subjects (eGFR 30-59 mL/min/1.73m2) 
• Group 4: Mild renal impairment subjects (eGFR 60-89 mL/min/1.73m2) 
All subjects will participate in one treatment period and will receive a single dose of lasmiditan 
in the fasting state.  
Subjects will be confined to the clinic from 10 hours prior to dosing until 36 hours after drug 
administration. 
The total duration of each subject’s participation in the study will be 3 days (Day –1 through the 
last PK sample taken on Day 2), not including the screening and follow-up phone call. 
3.2. Number of Centers and Subjects 
The study is planned to enroll up to 32 subjects in 2 centers. Eight subjects will be enrolled in 
each group. Subjects who withdraw from the study may be replaced. Replacement subjects will 
be not enrolled for subjects who discontinue the study due to treatment-related AEs. 
An effort will be made to include subjects with high BMI, moreover, an effort will be made to 
enroll more females than males (for an approximate ratio of 60%/40%) or at least 50%/50%. 
3.3. Schedule of Drug Administration 
The following treatment regimen will be used: 


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• Experimental treatment: Lasmiditan 200 mg 
The total duration of the study is expected to be 35 days, including the screening. 
The study may be stopped or interrupted at any time for safety, PK, or administrative reasons. 
4. SUBJECT SELECTION 
4.1. Study Population 
Subjects who meet all the inclusion criteria and none of the exclusion criteria will be eligible for 
participation in this study. A signed copy of the informed consent form will be provided to each 
subject. 
4.2. Inclusion Criteria 
All subjects: 
1. Availability for the entire study period 
2. Motivated volunteer and absence of intellectual problems likely to limit the validity of 
consent to participate in the study or the compliance with protocol requirements; ability 
to cooperate adequately; ability to understand and observe the instructions of the 
physician or designee 
3. Male or female volunteer 
4. A female volunteer must meet one of the following criteria: 
- 
If of childbearing potential – agrees to use one of the accepted contraceptive regimens 
from at least 28 days prior to the drug administration, during the study and for at least 
60 days after the dose. An acceptable method of contraception includes one of the 
following: 
• Abstinence from heterosexual intercourse 
• Systemic contraceptives (birth control pills, injectable/implant/insertable 
hormonal birth control products, transdermal patch) 
• Intrauterine device (with or without hormones) 
• Condom with spermicide or condom with intra-vaginally applied spermicide 
- 
If of non-childbearing potential – should be surgically sterile (i.e. has undergone 
complete hysterectomy, bilateral oophorectomy, or tubal ligation) or in a menopausal 
state (at least one year without menses) 
5. A male volunteer with sexual partners who are pregnant, possibly pregnant, or who could 
become pregnant must meet the following criteria: 


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- 
Participant is unable to procreate, defined as surgically sterile (i.e. has undergone a 
vasectomy within at least the last 6 months) 
- 
Participant is apt to procreate and agrees to use one of the accepted contraceptive 
regimens from first drug administration until 3 months after the drug administration. 
An acceptable method of contraception includes one of the following: 
• Abstinence from heterosexual intercourse. 
• Condom with spermicide or condom with intra-vaginally applied spermicide 
6. A male volunteer agrees to refrain from sperm donation from drug administration until 
3 months after the drug administration 
7. Volunteer aged of at least 18 years 
8. Volunteer with a body mass index (BMI) ≥18.50 kg/m2 and < 42.00 kg/m2 
9. Light-, non- or ex-smokers. A light smoker is defined as someone smoking 10 cigarettes 
or less per day for at least 3 months before Day 1 of this study. An ex-smoker is defined 
as someone who completely stopped smoking for at least 6 months before Day 1 of this 
study 
10. Willingness to adhere to the protocol requirements as evidenced by the informed consent 
form (ICF) duly read, signed and dated by the volunteer 
Subjects with Normal Renal Function: 
11. Clinical laboratory values within the laboratory's stated normal range; if not within this 
range, these must be without any clinical significance 
12. Have no clinically significant diseases captured in the medical history or evidence of 
clinically significant findings on physical examination and/or clinical laboratory 
evaluations (hematology, general biochemistry, electrocardiogram [ECG], and urinalysis) 
13. For each gender, have to match by age (± 10 years) and weight (± 20%) to the pooled 
mean values of subjects with severe renal impairment 
14. Have an eGFR ≥ 90 mL/min/1.73m2 calculated using MDRD equation at screening 
Renal Impaired Subjects: 
15. Considered clinically stable in the opinion of the Investigator 
16. Presence of mild renal impairment (eGFR 60-89 mL/min/1.73m2), moderate renal 
impairment (eGFR 30-59 mL/min/1.73m2), or severe renal impairment (eGFR < 30 
mL/min/1.73m2) calculated using MDRD equation at screening 
4.3. Exclusion Criteria 
All Subjects: 
1. Females who are pregnant or are lactating 


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2. History of significant hypersensitivity to lasmiditan or any related products (including 
excipients of the formulations) as well as severe hypersensitivity reactions (like 
angioedema) to any drugs  
3. Suicidal tendency, history of or disposition to seizures, state of confusion, clinically 
relevant psychiatric diseases 
4. Subject is at imminent risk of suicide (positive response to question 4 or 5 on the C-
SSRS) or had a suicide attempt within 6 months prior to the screening visit 
5. Presence or history of any disorder (including Parkinson disease) that could interfere with 
completion of the study based on the opinion of the Principal Investigator 
6. Any history of tuberculosis and/or prophylaxis for tuberculosis 
7. Positive results to HIV Ag/Ab Combo, Hepatitis B surface Antigen (HBsAG (B) 
(hepatitis B)) or Hepatitis C Virus (HCV (C)) tests 
8. Maintenance therapy with any drug or significant history of drug dependency or alcohol 
abuse (> 3 units of alcohol per day, intake of excessive alcohol, acute or chronic) 
9. Use of any enzyme-modifying drugs, including strong inhibitors of cytochrome P450 
(CYP) enzymes (such as cimetidine, fluoxetine, quinidine, erythromycin, ciprofloxacin, 
fluconazole, ketoconazole, diltiazem and HIV antivirals) and strong inducers of CYP 
enzymes (such as barbiturates, carbamazepine, glucocorticoids, phenytoin, rifampin and 
St John’s Wort), in the previous 28 days before Day 1 of this study 
10. Females who are pregnant according to a positive pregnancy test 
11. Volunteers who took lasmiditan in the previous 28 days before Day 1 of this study 
12. Volunteers who took an Investigational Product (in another clinical trial) in the previous 
28 days before Day 1 of this study 
13. Volunteers who have already participated in this clinical study 
14. Volunteers who donated 50 mL or more of blood in the previous 28 days before Day 1 of 
this study 
15. Donation of 500 mL or more of blood (Canadian Blood Services, Hema-Quebec, clinical 
studies, etc.) in the previous 56 days before Day 1 of this study 
Subjects with Normal Renal Function: 
16. Seated pulse rate less than or equal 40 Beats per Minute (bpm) or more than 100 bpm at 
screening 
17. Seated blood pressure below 90/60 mmHg or higher than 140/90 mmHg at screening 
18. Presence of significant gastrointestinal, liver, or kidney disease, or any other conditions 
known to interfere with the absorption, distribution, metabolism, or excretion of drugs or 
known to potentiate or predispose to undesired effects 


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19. History of significant gastrointestinal, liver or kidney disease that may affect drug 
bioavailability, including but not limited to cholecystectomy 
20. Presence of significant cardiovascular, pulmonary, hematologic, neurological, 
psychiatric, endocrine, immunologic or dermatologic disease 
21. Presence of out-of-range cardiac interval (PR < 110 msec, PR > 220 msec, QRS < 
60 msec, QRS >119 msec and QTc > 450 msec for males and > 460 msec for females) on 
the screening ECG or other clinically significant ECG abnormalities 
22. Positive screening of alcohol and/or drugs of abuse 
23. Any clinically significant illness in the previous 28 days before Day 1 of this study 
Renal Impaired Subjects: 
24. Seated pulse rate less than 50 bpm or more than 110 bpm at screening 
25. Seated blood pressure below 90/50 mmHg or higher than 180/110 mmHg at screening 
26. Currently undergoing any method of dialysis 
27. History of renal transplant 
28. History or presence, in the opinion of the Investigator, of significant clinically unstable 
respiratory, cardiovascular, pulmonary, hepatic, hematologic, gastrointestinal, endocrine, 
immunologic, dermatologic, neurologic, or psychiatric disease,  
29. Have poorly controlled Type 1 or Type 2 diabetes as defined by Hemoglobin A1c > 10% 
30. Require immunosuppressive medications for treatment of immune-mediated renal disease 
or kidney transplant recipients 
31. Evidence of renal carcinoma present at the time of screening 
32. Have relevant clinical laboratory abnormalities, including any elevation of alanine 
aminotransferase (ALT), aspartate aminotransferase (AST), or bilirubin at screening. If 
the investigator concludes that there is no safety risk for subjects with isolated laboratory 
abnormalities (eg, those that do not reflect end-organ dysfunction; for example, elevated 
bilirubin in Gilbert’s subjects) to participate in the study, such cases need to be discussed 
and approved by the sponsor’s medical monitor prior to study enrollment 
33. Presence of clinically significant physical, laboratory, or ECG finding that, in the opinion 
of the Investigator and/or sponsor, may interfere with any aspect of study conduct or 
interpretation of results 
34. Subjects with acute, unstable, or untreated significant medical conditions. Subjects 
requiring treatment for renal impairment or other chronic disease (eg, well-controlled 
diabetes, hypertension) must be on a stable treatment plan (medicines, doses, and 
regimens) for at least 2 weeks (except insulin) prior to Day 1 and during the entire study.  
Small adjustments in the dosages of some concomitant medications may be permitted 
during the study, and will be discussed on a case-by-case basis.  In all cases, the subjects’ 


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treatment history must be reviewed and their enrollment must be agreed to by both the 
investigator and the sponsor’s medical monitor 
35. Positive screening of alcohol and/or drugs of abuse unless results can be explained by a 
prescription medication 
36. Concurrent use of medications known to affect the elimination of serum creatinine (eg, 
trimethoprim/sulfamethoxazole [Bactrim®] or cimetidine [Tagamet®]) and competitors 
of renal tubular secretion (eg, probenecid) within 30 days prior to the first dose of study 
drug or anticipated need for these therapies through the last PK sample 
4.4. Withdrawal Criteria 
Subjects may voluntarily withdraw from the study, or be removed from the study at the 
discretion of the Investigator or sponsor at any time. The Investigator may withdraw a subject at 
any time if it is determined that continuing the study would result in a significant safety risk to 
the subject. 
If such withdrawal occurs, or if the subject fails to return for visits, the Investigator should 
determine the primary reason for a subject’s premature withdrawal from the study and record the 
reason in the respective subject’s study documents. Attempts should be made to have the subject 
complete the Post-Study tests or Early Termination study procedures.  
Premature withdrawal may occur for any of the following reasons: 
• A subject who experiences emesis within 5 hours following drug administration will be 
removed from the study period. 
• Noncompliance with the protocol requirements 
• Difficulties with blood collection 
• Pregnancy 
• AE 
• Subject request 
• Investigator request 
• Sponsor request 
• Unanticipated event that could result in an inadequately characterized pharmacokinetic 
profile, such as a missed blood draw, an AE, meal deviations or concomitant 
medications. 
• Subjects who are prematurely withdrawn from the study for reasons other than safety 
may be replaced by an equal number of newly enrolled subjects at the sponsor’s 
discretion. 


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5.
STUDY TREATMENTS
5.1. Description and Handling of Study Treatments 
5.1.1. Formulation of Test Product 
Lasmiditan is a new formulation of 
, which are 5-HT1F receptor agonists, developed by 
CoLucid Pharmaceuticals, Inc. for oral administration of the acute treatment of migraine. Oral 
doses of lasmiditan 50 mg, 100 mg and 200 mg are being investigated in Phase 3 clinical trials. 
Lasmiditan is available in a 200 mg tablets. The Test product used in this study will be provided 
by the sponsor. See Table 1 for the formulation of lasmiditan. 
Table 1: Formulation of Lasmiditan, 200 mg Tablets 
Component 
Function 
Amount 
200mg Tablet 
Intragranular Components 
Lasmiditan hemisuccinate 
a, b
Active 
Ingredient 
231.28 mg 
Microcrystalline cellulose 
PH102 b 
Filler 
123.47 mg 
Starch 1500 
Binder 
30.0 mg 
Croscarmellose sodium 
Disintegrant 
22.5 mg 
Sodium lauryl sulfate 
Wetting Agent 
2.25 mg 
Purified water c 
Granulating 
Medium 
Qs 
Extragranular Components 
Croscarmellose sodium 
Disintegrant 
31.5 mg 
Magnesium stearate 
(Non-bovine) 
Lubricant 
9.0 mg 
Totals 
450 mg 
Film Coating Materials 
Opadry II White 
(85F18422) d 
Film Coat 
11.25 mg 
Purified water e 
Suspending 
Agent 
(45.00 mg) 
 a 
A salt correction factor for the hemisuccinate is assigned as 0.865 
b
Note that the amount of lasmiditan hemisuccinate may be adjusted for purity and moisture content.  An 
adjustment will be made to the amount of microcrystalline cellulose used to maintain tablet weight. 
c
Water for granulation is removed upon drying of the wet mass. 
d
Opadry II White (85F18422) is prepared as a suspension at 20% w/w in Sterile Water for Injection and 
applied to a target of 2.5% weight gain. 
e 
The amount of water may be adjusted to facilitate suspension of the coating agent.  This water is removed 
during processing and does not appear in the final product. 
5.1.2. Packaging and Labeling 
The sponsor will be responsible for ensuring that the treatment is manufactured in accordance 
with applicable Good Manufacturing Practice regulations and requirements. All labels for study 
CCI


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drugs will meet applicable requirements of the protocol and the Canadian Health Products and 
Food Branch. 
5.1.3. Storage and Handling 
Lasmiditan tablets should be stored by the study site at controlled room temperature of 25°C 
(77°F); excursions are permitted to 15°C (59°F). 
Measures that minimize drug contact with the body should always be considered during 
handling, preparation, and disposal procedures. 
5.2. Method of Assigning Subjects to Treatment Groups 
No randomization will be performed for this study. Instead subjects will be categorized into 
either the control group of healthy volunteers with normal renal function, or into one of the three 
groups of subjects with varying degrees of renal impairment. 
Once a subject number has been assigned to a subject, it will not be reassigned to another 
subject. Subjects who withdraw from the study may be replaced. Replacement subjects will not 
be enrolled for subjects who discontinue the study due to treatment-related toxicity. A new 
unique subject number will be assigned to the replacement subject. 
5.3. Blinding 
No unblinding procedure is required, as this is an open-label study. 
5.4. Dosing and Administration 
5.4.1. Dispensing 
Designated site staff will dispense study drug in tablet form. 
Study drugs will be administered to the subjects under supervision of the study center personnel. 
5.4.2. Administration Instructions 
Study drug will be administered orally in the morning.  
Dosing will be performed by trained personnel and supervised by the Principal Investigator or 
physician in charge. Adequate time intervals between subjects will be observed to ensure timely 
blood sampling. 
Subjects will be asked to fast overnight (no food or drink, except water) prior to each dosing, for 
a minimum of 10 hours, at Day -1. Fasting will continue for at least 4 hours following drug 
administration, after which a standardized lunch will be served. A supper, a light snack and other 
meals will also be served at appropriate times thereafter, but not before 9 hours after dosing. 
Fluid intake other than water will be controlled for housing period and for all subjects. Water 
will be provided ad libitum until 1 hour pre-dose. The drug will be given with about 240 mL 
(8 oz.) of water at room temperature. Water will be allowed ad libitum beginning 1 hour after the 
administration of the drug. 


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The tablet must be swallowed whole and must not be chewed or broken. 
Study medications will be administered to each subject consecutively for the purpose of accurate 
sampling time. The date and time of each dose must be recorded. 
The physician in charge will remain at the clinical site for at least the first 4 hours following drug 
administration, and will remain available at all times during the study. 
5.4.3. Treatment Compliance 
The following measures will be employed to ensure treatment compliance: 
• All doses will be administered under the supervision of the Investigator (or designee). 
• A mouth and hand check of all subjects will be carried out to ensure that all tablets have 
been swallowed. 
5.4.4. Study Drug Accountability 
Complete and accurate records of all study drugs must be kept. This includes acknowledgment of 
receipt of each shipment of study product (quantity and condition), subject dispensing records, 
and returned or destroyed study product. 
At the conclusion of the study, all unused investigational products and all medication containers 
will be returned to the sponsor unless the sponsor has approved other arrangements. Drug 
accountability will be performed at the completion of the trial. 
5.5. Prior and Concomitant Medication 
Renal-impaired subjects will be permitted to continue taking any prescription or OTC medication 
necessary for the management of their renal disease or other concurrent illness. The dosing 
schedules must be stable for 2 weeks (except insulin) before Day 1 of the study and maintained 
throughout the study. Minor dose changes consistent with treatment practices may be permitted 
at the discretion of the Investigator. All medications taken during the 14 days prior to dosing will 
be recorded in the subject’s CRF and reviewed by the Investigator. When concomitant 
medications are administered, the indication, name, dose, route, and frequency will be recorded 
in each subject’s CRF. 
For healthy subjects, beside enzyme-modifying drugs that are not allowed for 28 days (refer to 
exclusion criteria), subjects will be requested to abstain from taking any prescription medications 
used with the intention to treat a condition for 28 days prior to the first dosing and during the 
study, unless judged differently by the Principal Investigator or designee. Systemic 
contraceptives and hormone replacement therapy will be permitted. Subjects will also be 
requested to abstain from taking any over-the-counter (OTC) products for 7 days prior to the first 
dosing and during the study. They will be specifically reminded that this includes cold 
preparations (containing ASA), acetylsalicylic acid (ASA), vitamins and natural products used 
for therapeutic benefits and antacid preparations. Vitamins used as nutritional supplements in 
non-therapeutic doses (as judged by the Principal  Investigator or designee) may be accepted, but 
they must be stopped at least 48 hours prior to the first dosing and during the study. 


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If a medication (including OTC) other than those specified in the protocol is used after the first 
drug administration or at any time before the end of the study, the Principal Investigator or 
designee and/or the sponsor will decide whether the subject will be permitted to remain in the 
study, depending on the drug used, the time of drug intake, etc. The drug and dose will be noted. 


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5.6. Study-Specific Restrictions 
• Subjects will be requested to abstain from alcohol for 48 hours prior to dosing and during 
study period. Throughout the study (including the return visits), in case of any doubt 
about alcohol consumption, a test for alcohol may be performed to confirm the 
physician's judgment. 
• During the study, subjects who are light-smokers should not smoke more than 
10 cigarettes per day. They will also be instructed to abstain from smoking for 2 hours 
prior to and until 4 hours after drug administration at study period. 
• Subjects will be requested to avoid food or beverages containing xanthines (i.e. tea, 
coffee, cola drinks, energy drinks or chocolate) for 48 hours prior to dosing and during 
study period. 
• Subjects will be instructed to avoid food or beverages containing grapefruit and/or 
pomelo for 7 days prior to dosing and during study period. 
• Subjects will remain seated for the first 4 hours following drug administration, avoiding 
both vigorous exertion and complete rest. However, should AEs occur at any time, 
subjects may be placed in an appropriate position. Subjects will not engage in strenuous 
activity at any time during the confinement. 
• Female volunteers of childbearing potential will have to take appropriate measures to 
prevent pregnancy for at least 28 days prior to the administration of the study drug, 
during the study and for at least 60 days after the drug administration, as described in 
Section 4.2. 
• Male subjects who are apt to procreate will be expected to use an acceptable 
contraceptive regimen from Day 1 of this study, throughout the duration of the entire 
study, and until at least 3 months after the drug administration, as described in Section 
4.2. Condoms with spermicide will be provided to subjects upon departure from the 
clinical site. In addition to the use of condoms with spermicide, subjects will be informed 
that it is strongly recommended that their female partner uses one of the two methods 
listed below: 
- 
Systemic contraceptives (birth control pills, injectable/ implantable/ insertable 
hormonal birth control products, transdermal patch). 
- 
Intrauterine device. 
• Male subjects must refrain from sperm donation from the screening and until at least 
3 months after the drug administration. 
6. STUDY PROCEDURES AND GUIDELINES 
Unless otherwise stated in this protocol, clinical site standard operating procedures (SOPs), 
which are available for all activities relevant to the quality of the study, will be followed during 
this study. The different parts of this study are summarized in Table 2 and explained in the 
following sections. The list of assessments for each study parts are indicated with an "X" when 


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the assessments have to be performed. Any deviation from protocol procedures should be noted 
in the CRFs and the sponsor should be notified. 


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Table 2. Schedule of Assessments for all subjects 
Examination 
Screening 
Days 
Post-
Study 
Tests or 
ETa 
End of Study 
Day 28 to – 1 
-1 
1 
2 
2 
7 (±3) 
Review Inc/Exclusion Criteria & Medical 
History 
X 
 
 
 
 
 
Informed Consent 
X 
 
 
 
 
 
Check-in 
 
X 
 
 
 
 
Dosing 
 
 
X 
 
 
 
Clinic Confinement 
 
X 
X 
X 
 
 
Discharge 
 
 
 
X 
 
 
Demographics 
X 
 
 
 
 
 
C-SSRS questionnaire 
X 
 
 
 
X 
 
Concomitant Medication 
X 
X 
X 
X 
X 
X 
Physical Examination 
X 
 
 
 
X 
 
Vital Signs 
X 
 
Xb 
 
X 
 
Height, Weight, and BMI 
X 
 
 
 
 
 
12-lead ECG 
X 
Xc 
Xc 
 
X 
 
HIV Ag/Ab Combo, HBsAg (B) (Hepatitis 
B) and HCV (C) Tests 
X 
 
 
 
 
 
Drug and Alcohol Screen 
X 
X 
 
 
 
 
Pregnancy test (females) 
X 
X 
 
 
X 
 
Clinical Laboratory Evaluations 
X 
Xd 
 
 
X 
 
PK Blood Samplese 
 
 
X 
X 
 
 
Urine PK Collectione 
 
 
X 
X 
 
 
Follow-up Call 
 
 
 
 
 
X 
AEs Recording 
X 
X 
X 
X 
X 
 


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a Early Termination (ET).  
b Vital signs will be measured prior to dosing and approximately 2 and 4 hours after study drug administration. 
c 12-lead ECG will be performed prior to dosing and approximately 2 hours after study drug administration. 
d Clinical laboratory tests (hematology, biochemistry, and urinalysis) will be performed in the evening prior to drug administration.  
e PK blood and urine samples will be collected according to schedule of PK assessments in Table 4. 
 


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Table 3. Schedule of Pharmacokinetic Assessments 
PK Blood Sampling 
Urine PK Collection Intervals 
Prior to dosing 
Prior to dosing  
0.25, 0.5, 0.75, 1, 1.25, 1.5, 1.75, 2, 2.5, 3, 4, 6, 8, 12, 16, 24 
and 36 hours postdose 
0-2, 2-4, 4-8, 8-12, 12-24 and 24-36 hours postdose 
 
 
Time of PK sampling and dosing must be recorded. 
 
 


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6.1. Study Procedures 
Safety assessments will include physical examination, vital signs (blood pressure, heart rate, and 
body temperature), 12-lead ECG, laboratory tests (hematology, biochemistry, and urinalysis), 
and continuous AE monitoring. Body weight and height will be measured at Screening. 
Clinically significant physical examination findings prior to the administration of study drug will 
be recorded as a medical history; clinically significant findings after the drug administration will 
be recorded as an AE. 
The laboratory tests will be carried out according to the standard operating procedures of the 
licensed medical laboratory. Abnormal results will be verified to rule out laboratory error. 
Persistent relevant abnormal values should be followed up until the cause is determined or until 
the values return to the pre-medication value. 
After the ICF is signed, information about all local and systemic clinical events, whether 
volunteered by the subject, discovered by Investigator questioning, or detected through other 
means, will be collected, recorded and followed as appropriate. 
6.1.1. Physical Examination 
A complete physical examination will be performed by a medically qualified and licensed 
individual as scheduled in Table 2. The physical examination will include a review of the 
following: head and neck, heart, lungs, abdomen and general appearance. 
Demographic data (age, gender, race, body weight adjusted for indoor clothing, height, BMI), 
and alcohol and smoking habits will be recorded. 
During study days, not requiring a complete physical examination, a symptom-targeted physical 
exam should be done if a new AE is reported, if medically indicated. 
6.1.2. C-SSRS Questionnaire 
A Columbia Suicide Severity Rating Scale will be performed as scheduled in Table 2. 
6.1.3. Vital Signs 
Vital sign measurements (body temperature, pulse rate, blood pressure and orthostatic blood 
pressure) are specified in Table 2. Vital signs can also be monitored during the study when 
judged necessary by the physician in charge or designee. Vital signs are to be performed prior to 
blood draws. 
6.1.4. Laboratory Evaluations 
Laboratory evaluations will be performed as scheduled in Table 2. The physician in charge or 
designee will assess each abnormal value to determine if it is clinically significant. Postdose 
clinically significant laboratory values will be reported as AEs. 


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•
General biochemistry: Sodium, potassium, chloride, glucose, blood urea nitrogen (BUN),
creatinine, eGFR, total bilirubin, alkaline phosphatase, AST, ALT and albumin
•
Hematology: White cell count with differential (absolute values of neutrophil,
lymphocyte, monocyte, eosinophil, and basophil), red cell count, hemoglobin,
hemoglobin A1c, hematocrit, mean corpuscular volume (MCV), and platelets count
•
Urinalysis: Color, appearance, specific gravity, pH, leukocyte, protein, glucose, ketones,
bilirubin, blood, nitrite, urobilinogen. Microscopic examination will only be performed if
the dipstick test is outside of the reference range for leukocyte, blood, nitrite or protein
•
Serology: HIV Ag/Ab Combo, HBsAg and HCV
•
Drug Screen: Alcohol, amphetamines, barbiturates, cannabinoids (THC), cocaine, opiates
and phencyclidine (PCP)
6.1.4.1. 
Pregnancy Tests 
A pregnancy test will be performed on female subjects as specified in Table 2. 
6.1.5. 12-Lead Electrocardiogram 
Twelve-lead ECGs will be performed as specified in Table 2. On study days ECGs are 
conducted, they should be scheduled prior to blood draws that occur for that day, as the blood 
draws can impact the ECG reading. Subjects must be in a supine position for 10 minutes prior to 
ECG. 
6.1.6. Follow-up Call 
A symptom-directed follow-up telephone call will be made to all subjects following drug 
administration as specified in Table 2. 
6.1.7. Pharmacokinetic Sampling 
Blood samples will be collected by direct venipuncture. However, as an option to the volunteer 
or if judged necessary by the clinical staff, blood samples may be collected from an indwelling 
cannula (stylet catheter that requires no flushing), which will be placed in the forearm vein of the 
subject. Blood samples will be kept in an ice-water bath pending processing. Blood samples will 
be collected in one tube of 6 mL each. 
The complete schedule for each part is presented in Table 3. The time of blood sample collection 
will be calculated according to the drug administration schedule. The clock time of all blood 
draws will be recorded and reported for all subjects in the CRF. For postdose samples, all 
deviations from the scheduled sampling time of 2 minutes or more will be reported in the final 
report. 
The total volume of blood withdrawn, including ~21 mL required for screening, on-study and 
poststudy tests, should not exceed 129 mL per subject. 
During the study, a baseline urine sample will be collected before drug administration. After 
dosing, urine samples will be collected over 36 hours over 6 collection intervals (Table 3). The 


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total volume of urine collected at each interval will be measured and two containers (~ 5 mL 
each) will be preserved. 
6.1.7.1. 
Sample processing, storage and shipping 
Blood samples will be processed, split, stored, and shipped according to the sample processing 
instructions supplied by the bioanalytical facility. 
Urine samples will be processed, split, stored, and shipped according to the sample processing 
instructions supplied by the bioanalytical facility. 
6.2. Bioanalytical Methods 
Plasma and urine lasmiditan concentrations will be measured according to validated 
bioanalytical methods.  
Samples from all subjects who received the investigational product will be assayed. 
6.2.1. Aberrant values and retested samples 
Unacceptable values attributable to bioanalytical reasons will be determined according to the 
bioanalytical Facility’s SOPs. Such re-assayed samples will be termed “repeats”. The method of 
re-assay and the acceptance criteria for selecting which value to report for the re-assayed samples 
will follow the bioanalytical Facility’s SOPs. All cases of re-assay will be reported in the final 
report. 
No samples will be repeated for pharmacokinetic reasons. 
6.2.2. Incurred sample reproducibility 
In order to establish the reproducibility of the assay with incurred samples, at least 10% of the 
total analyzable study samples will be selected and re-assayed. The replicate measurement is not 
to be averaged with the original one, but both values will be presented in the bioanalytical report 
with the initial value being used for PK calculations. The concentrations of the original and 
replicate samples will be tabulated, along with the percent difference between the two values. 
6.3. Pharmacokinetic Measurements 
The PK parameters are presented in Table 4. Below limit of quantitation concentrations (coded 
BLQ) will be treated as zero for all PK analyses. All reported sampling time deviations (see 
Section 6.1.7) will be taken into consideration for evaluation of plasma PK parameters. 
The pharmacokinetic parameters will be estimated using a non-compartmental approach with a 
log-linear terminal phase assumption. The trapezoidal rule will be used to estimate the area under 
the curve, and the terminal phase will be estimated by maximizing the coefficient of 
determination estimated from the log-linear regression model. Disposition parameters (AUC0-∞, 
AUC0-T/∞, λZ, Thalf, ClTOT/F and VD/F) will not be estimated for individual concentration-time 
profiles where the terminal log-linear phase cannot be reliably characterized. 
In the case where less than 3 consecutive measurable plasma concentrations of lasmiditan is 
observed, the AUC parameters will not be estimated. 


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Table 4. Pharmacokinetic Parameters 
PK Parameter 
Definition 
Cmax  
Maximum observed plasma concentration 
Tmax 
Time of maximum observed plasma concentration; if it occurs at more than 
one time point, Tmax is defined as the first time point with this value 
AUC0-T 
Cumulative area under the plasma concentration time curve calculated from 0 
to TLQC using the linear trapezoidal method, where TLQC represents time of last 
observed quantifiable plasma concentration 
AUC0-∞  
Area under the plasma concentration time curve extrapolated to infinity, 
calculated as AUCT + CLQC/λZ, where CLQC is the measured concentration at 
time TLQC  
AUC0-T/∞ 
Relative percentage of AUC0-T with respect to AUC0-∞ 
λZ 
Apparent elimination rate constant, estimated by linear regression of the 
terminal linear portion of the log concentration versus time curve 
Thalf 
Terminal elimination half-life, calculated as ln(2)/λZ 
ClTOT/F 
Apparent Total Plasma Clearance, calculated as dose /AUC0-∞  
VD/F 
Apparent Volume of Distribution, calculated as dose / λZ*AUC0-∞  
Ae(0-t) 
Amount excreted in urine (Total lasmiditan concentration * Volume of Urine) 
fe 
Fraction of dose excreted in urine (Ae / dose) 
Clr 
Renal Clearance (Ae(0-t)/AUC0-T) 
 
Additional pharmacokinetic parameters may be calculated if deemed appropriate. 
Pharmacokinetic analyses will be generated using Phoenix® WinNonlin® Version 6.3 (or higher). 
7. ADVERSE EVENTS 
7.1. Definitions 
An AE is defined as any untoward medical occurrence in a subject administered a medicinal 
product and which does not necessarily have to have a causal relationship with this treatment. 
AEs occurring after the initiation of the treatment are referred to as treatment emergent adverse 
events (TEAEs). An AE can therefore be any unfavorable and unintended sign (for example, an 
abnormal laboratory finding), symptom, or disease temporally associated with the use of a 
medicinal product, whether or not considered related to this medicinal product. 
A suspected adverse reaction is any AE for which there is a reasonable possibility that the drug 
caused the AE. ‘Reasonable possibility’ means there is evidence to suggest a causal relationship 
between the drug and the AE. A suspected adverse reaction implies a lesser degree of certainty 
about causality than adverse reaction, which means any AE caused by a drug. 
An AE may be: 


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• A new illness, 
• Worsening of a concomitant illness, 
• An effect of the study medication including comparator; it could be an abnormal 
laboratory value as well as a significant shift from baseline within normal range which 
the Principal Investigator or medical qualified designate considers to be clinically 
important. 
Surgical procedures themselves are not AEs. They are therapeutic measures for conditions that 
required surgery. The condition for which the surgery is required is an AE, if it occurs or is 
detected during the study period. Planned surgical measures permitted by the clinical study 
protocol and the conditions(s) leading to these measures are not AEs, if the condition(s) was 
(were) known before the start of study treatment. In the latter case, the condition should be 
reported as medical history. 
A serious adverse event (SAE) or reaction is any untoward medical occurrence that at any dose: 
• Results in death, 
• Is life-threatening, 
• Requires inpatient hospitalization or prolongation of existing hospitalization, 
• Results in persistent or significant disability or incapacity (defined as a substantial 
disruption of a person’s ability to conduct normal life functions), 
• Is a congenital anomaly or birth defect, 
Is an important medical event (including development of drug dependence or drug abuse) that 
may jeopardize the subject or may require intervention to prevent one of the other outcomes 
listed above (according to medical judgment of the Principal Investigator). 
7.1.1. Severity Assessment 
All AEs will be graded as mild, moderate, or severe according to the following definitions: 
Mild: 
Causing no limitation of usual activities; the subject may experience slight 
discomfort. 
Moderate: 
Causing some limitation of usual activities; the subject may experience annoying 
discomfort. 
Severe: 
Causing inability to carry out usual activities; the subject may experience 
intolerable discomfort or pain. 
Every effort will be made to obtain an adequate evaluation of the severity. 


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7.1.2. Causality Assessment 
The Principal Investigator or a medical qualified designate will determine the relationship of any 
AE to study drug using the following guidelines in Table 5. 
Table 5. Adverse Event Relationship to Study Drug 
Relationship to Drug 
Comment 
Reasonable Possibility 
A temporal relationship exists between the AE onset and 
administration of the investigational product that cannot be readily 
explained by the subject’s clinical state or concomitant therapies. 
Furthermore, the AE appears with some degree of certainty to be 
related, based on the known therapeutic and pharmacologic actions or 
AE profile of the investigational product. 
In case of cessation or reduction of the dose, the AE may abate or 
resolve and it may reappear upon rechallenge. 
No Reasonable Possibility 
Evidence exists that the AE has an etiology other than the 
investigational product. 
For SAEs, an alternative causality must be provided (eg, pre-existing 
condition, underlying disease, intercurrent illness, or concomitant 
medication). 
7.2. Routine Reporting 
For the purposes of this study, the period of observation of AEs extends from the screening visit 
until the follow-up call. During this period, all AEs spontaneously reported by the subject, 
observed by the clinical staff, or elicited by general questioning will be recorded and reported in 
the CRF. 
Any AE which remains unresolved as of the last visit will require an evaluation and follow-up 
until the AE has been resolved or a reasonable explanation for its persistence found, or is deemed 
mild and safely resolving. 
In the case of AEs deemed related to the Investigational Product, every effort will be made to 
determine the final outcome. 
It is the Investigator’s responsibility to ensure subjects experiencing AE receive appropriate 
follow-up, treatment where required, and that every action is well documented. 
Subjects will be questioned on their health status at the beginning of study period and before 
departure from the clinical site. Open-ended questions will be asked. 
Subjects will be questioned on their health status at the beginning of the study period and before 
the departure from the clinical site. Open-ended questions will be asked. 
Classification will be performed by System Organ Class (SOC) and Preferred Term (PT) using 
the Medical Dictionary for Regulatory Activities (MedDRA), version 19.0 or higher. 
In general, AEs occurring secondary to other events (eg, clinical sequelae or a cascade of events) 
should be identified by their primary cause. For example, if severe vomiting is known to result in 
dehydration, it is sufficient to record only vomiting as SAE or AE in the CRF. However, 


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medically significant AEs occurring secondary to an initiating event that are separated in time 
should be recorded as independent events on the CRF. 
Pregnancy in a female subject on the study shall be reported to the sponsor within 24 hours of the 
knowledge of its occurrence by the Principal Investigator or designee (for pregnancies occurring 
during the course of the study or immediately following the end of the study). Because of the 
possibility that the fetus/embryo could have been exposed to the study drug through the parent 
and for the subject’s safety, the pregnancy will be followed up to determine its outcome, 
including spontaneous or voluntary termination, details of birth, presence or absence of any birth 
defects, congenital anomalies, or maternal and/or newborn complications. 
The pregnancy will be recorded and reported by the Principal Investigator or designee to the 
sponsor. Pregnancy follow-up will also be properly recorded to ensure quality and completeness 
of the data belonging to the study drug and will include an assessment of the possible causal 
relation between the study drug and any pregnancy outcome. Any SAE experienced during 
pregnancy will be reported on a SAE Report Form. 
7.3. Serious Adverse Event Reporting 
Algorithme Pharma will notify any SAE to the sponsor, without regard to causality, within 
24 hours after becoming aware of its occurrence.  
If, during follow-up, any non-serious AE worsens and eventually meets the criteria for an SAE, 
that AE should be recorded as a new SAE. 
The initial SAE report must be as complete as possible, including details of the current illness 
and SAE, and an assessment of the causal relationship between the event and the investigational 
product(s). Information not available at the time of the initial report (eg, an end date for the AE, 
laboratory values received after the report, or hospital discharge summary) must be documented. 
All follow-up information must be reported as soon as the relevant info is available. 
The notification should be directed to the following sponsor representatives: 
Tel. 
Fax.
Email: 
 
An SAE will be considered “unexpected” if the AE is not listed in the investigator brochure or is 
not listed at the specificity or severity that has been observed; or, if an investigator brochure is 
not required or available, is not consistent with the risk information described in the general 
investigational plan or elsewhere in the current application. "Unexpected," as used in this 
definition, also refers to AEs that are mentioned in the investigator brochure as occurring with a 
class of drugs or as anticipated from the pharmacological properties of the drug, but are not 
specifically mentioned as occurring with the particular drug under investigation. 
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Algorithme Pharma will determine whether any serious unexpected related AE must be reported 
to the IRB. If so, the event will be reported via fax or email within 15 calendar days of the 
investigator or staff becoming aware of the event. 
The sponsor will determine whether the SAE must be reported in an expedited manner to the 
appropriate regulatory agencies. If so, Algorithme Pharma Inc, on the behalf of the sponsor will 
report the event to the appropriate regulatory agencies, and all participating investigators. 
During a clinical trial conducted in Canada, it is required to inform Health Canada of any 
serious, unexpected adverse drug reaction that has occurred inside or outside Canada: 
• Where it is neither fatal nor life-threatening, within 15 days after becoming aware of the 
information; 
• Where it is fatal or life-threatening, immediately where possible and, in any event, within 
7 days after becoming aware of the information; and 
• Within 8 days after having informed Health Canada of the ADR, submit as complete a 
report as possible which includes an assessment of the importance and implication of any 
findings. 
If reports of any new and unexpected AEs become available to the sponsor during the clinical 
portion of this study (related or not to the present study), the sponsor must advise 
Algorithme Pharma, through its Clinical Investigator, of those events. If required by the sponsor, 
Algorithme Pharma may advise the Canadian authorities. 
8. STATISTICAL ANALYSIS 
8.1. Analysis Sets 
8.1.1. Safety Analysis Set 
The safety population will include all subjects who received the investigational product under 
study. 
8.1.2. Pharmacokinetic Analysis Set 
All subjects who received lasmiditan, had no major protocol deviations, and completed the 
period with evaluable (sufficient and interpretable) data will be included in the PK analysis. 
Concentration data of the remaining subjects will be presented separately. 
If some subjects do not complete the sampling schedule resulting in an inadequately 
characterized AUC and elimination parameters, samples of these subjects could be included in 
the statistical pharmacokinetic analysis for only the Cmax and Tmax parameters. This decision is to 
be documented by the SRA department and approved by the sponsor before the start of the 
sample analysis by the bioanalytical facility. 


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8.2. Sample Size Determination 
There is no formal statistical sample size calculation for this study. A sample size of 32; 
including 8 subjects/patients for each renal function group (8 subjects with normal renal function 
8 patients with mildly impaired renal function, 8 patients with moderately impaired renal 
function, and 8 with severely impaired renal function) was chosen because it is considered 
typical for studies evaluating the effect of renal function on the pharmacokinetics of a drug. 
8.3. Statistical Analysis 
A detailed statistical analysis plan (SAP) describing the methodology to be used will be prepared 
prior to the completion of the clinical phase of the study. The sections below summarize the data 
analysis to be undertaken. 
8.3.1. Descriptive Analysis 
8.3.1.1. 
Safety Analyses 
Data to be listed by subject and summarized by group will include demographic data, AEs, vital 
signs, ECG parameters, and clinical laboratory evaluations. All values outside the clinical 
reference ranges will be flagged on the data listings. Other data to be listed by subject will 
include urinary drug screen, serology results, physical examination findings and concomitant 
medications. 
AEs will be coded according to the Medical Dictionary for Regulatory Activities (MedDRA 
Version 19.0 or higher). Concomitant medications will be coded using the World Health 
Organisation drug dictionary (WHO-DDE March 1st, 2016). 
8.3.1.2. 
Pharmacokinetic Endpoint Analyses 
Descriptive statistics will be calculated for plasma concentrations at each individual time point 
and for all PK parameters. The individual plasma concentration/time profiles will be presented 
using the actual sampling times whereas the mean plasma concentration/time profiles will be 
presented using the theoretical sampling times. 
8.3.2. Statistical Methodology 
The natural logarithmic transformation of Cmax, AUC0-T, AUC0-∞, λZ, Ae(0-t), fe, Clr, ClTOT/F and 
VD/F as well as the rank-transformation of Tmax will be used for all statistical inference.  
Statistical analyses will be generated using validated SAS® (version 9.4 or higher) using the Reg 
(and Mixed, if applicable) procedure(s).  
The statistical analysis described in this section will be done using both eGFR and Cockcroft-
Gault estimate of the creatinine clearance. However, analysis using the eGFR will be considered 
as the primary analysis and the analysis using the Cockcroft-Gault estimate of the creatinine 
clearance will be considered as supportive. 


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Regression Analysis  
The eGFR and Cockcroft-Gault estimate of the creatinine clearance at baseline will be used as 
separate measures of renal function for a regression analysis to evaluate the relationships 
between estimated renal function and the PK parameters. For each PK parameter, a regression 
analysis will be performed to assess the impact of impaired eGFR and creatinine clearance 
(CLCR), using a regression model of the form α + β*eGFR (or CLCR) + ε where the errors (ε) 
will be assumed to be independent and normally distributed with mean zero and variance σ2. The 
parameter β represents the correlation between the relevant PK parameter and eGFR (or CLCR) 
which will be treated as a continuous variable. 
The hypothesis of the slope of trend being different from zero will be assumed if the two-sided 
test of the nullity of the parameter β is statistically significant at the 5% level.  
Analysis of Variance  
Based on the regression analysis described in the previous section, if the slope of trend of the 
regression analysis between a PK parameter and the estimated renal function (eGFR or CLCR) is 
found to be significant (p < 0.05), and if more than one group of subjects with impaired renal 
function are enrolled, an analysis of variance (ANOVA) will be performed to assess the 
difference in the PK parameter among the renal function groups. 
The renal function (normal, mild, moderate and severe) will be entered as a fixed effect in the 
ANOVA model. Pairwise comparisons of renal function groups will be generated using the 
Tukey-Kramer’s procedure of adjustment for multiple comparisons (if more than 2 renal function 
groups) and statistical significance will be assessed at the two-sided 5% level. The ratio of 
geometric LS means (of each renal function group being compared), with a corresponding 90% 
confidence interval (adjusted using Tukey-Kramer’s procedure if applicable), will be computed. 
Heterogeneity of variance among groups will be assumed.  
8.3.2.1. 
Interim Analysis 
First, subjects with severe renal impairment and healthy subjects with normal renal function will 
be enrolled. Samples will be assayed and PK will be performed. If substantial changes in the 
exposure of lasmiditan are observed in subjects with severe renal impairment compared to 
subjects with normal renal function, subjects with mild and moderate renal impairment will be 
enrolled. 
Interim analysis of subjects with severe renal impairment and healthy subjects with normal renal 
function will be performed as described in Section 8.3.2. 
9. ETHICS 
9.1. Institutional Review Board (IRB) 
This protocol and the ICF will be submitted to IRBs (or IECs) (one for each study center) prior 
to initiation of the study and the study will not start until the Board has approved the documents. 
Notification of the Board’s approval will be appended to the final report. 


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9.2. Ethical Conduct of the Study 
This study will be conducted in compliance with the study protocol, the ethical principles in the 
latest version of the Declaration of Helsinki, the ICH Guideline E6 for GCP, the FDA GCP Code 
of Federal Regulations (CFR) Title 21, part 56, European regulation EU 536/2014 and the 
Tri-Council Policy Statement (Canada). 
9.3. Participant Information and Consent 
Before inclusion in the study, each prospective subject will be given a full explanation of the 
purpose of the study, the procedures to be carried out and the potential hazards. Once this 
essential information is provided to the volunteer and once the physician in charge or designee 
has the conviction that the volunteer understands the implications of participating in the study, 
the volunteers will be required to read, sign and date a properly executed written informed 
consent form prior to enrollment. Subjects will be assured that they may withdraw from the study 
at any time without jeopardizing their medical care. They will be given a copy of their informed 
consent form. 
If an amended or revised ICF is introduced during the study, each subject’s further consent 
should be obtained. 
9.4. Subject Confidentiality 
The Investigators and the sponsor will preserve the confidentiality of all subjects taking part in 
the study, in accordance with GCP and local regulations. Subjects should be identified by a 
unique subject identifier on all study documents provided to the sponsor. In compliance with 
Federal regulations/ICH GCP Guidelines, it is required that the Investigator and institution 
permit authorized representatives of the company, of the regulatory agency(s), and IRB access to 
review the subject’s original medical records for verification of study-related procedures and 
data. The investigator is obligated to inform the subject that his/her study-related records will be 
reviewed by the above named representatives without violating the confidentiality of the subject. 
10. DATA COLLECTION, RETENTION, AND MONITORING 
10.1. Case Report Forms 
A CRF is a gathering of all pertinent data collected for each subject included (i.e., who received 
an Investigational Product treatment) in a clinical trial. Once all CRF forms (including 
multi-subject CRF forms) are completed and reviewed. At Algorithme Pharma, the complete 
CRF will be approved and signed by the Study Manager, who received a signature delegation 
from the Principal Investigator. At the CIUSSS de l'est-de-l'île-de-Montréal - installation Hôpital 
Maisonneuve-Rosemont, the complete CRF will be approved and signed by the Principal 
Investigator. 
The original source documents and a copy of the corresponding CRFs will be retained by the 
Investigator. Copies of the CRFs will be provided to the sponsor. 


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10.2. Data Management and Processing 
Data entry will be performed according to clinical site facility procedures. Information will be 
entered into a Medrio database, which will be used for developing tables and listings for the final 
study report. Appropriately trained and designated individuals will be given access to the 
database and will perform entry of the data from the CRFs. The data management process will 
comply with all regulatory standards and will use from the clinical sites for generating the final 
locked database. 
10.3. Quality Assurance 
Designated personnel from Algorithme Pharma will be responsible for maintaining quality 
assurance (QA) and quality control (QC) systems to ensure that the portion of the trial conducted 
in the Algorithme Pharma clinic and the clinical/PK/statistical data are generated, documented 
and reported in compliance with the protocol and ICH Guideline E6 for Good Clinical Practices. 
Furthermore, Algorithme Pharma will qualify the vendor(s) or external clinical site(s) used in the 
conduct of the study. 
All parts of the bioanalytical phase of the study and all its documentation will be subject to 
inspection by the quality assurance unit of the bioanalytical facility to ensure that the data are 
generated, documented and reported in compliance with the protocol and applicable 
requirements as outlined in the FDA and OECD Principles of GLP. 
10.4. Record Retention 
All essential documents and records will be maintained by the study centers for a period of 
25 years. These documents may be retained for a longer period if required by the applicable 
regulatory requirement(s) (FDA CFR 312.57 (C)) or if needed by the sponsor. 
10.5. Monitoring of the Study 
The sponsor or its representative may visit the study facilities at any time in order to maintain 
current and personal knowledge of the study through review of the records, comparison with 
source documents, observation and discussion of the conduct and progress of the study. 
Algorithme Pharma will permit trial-related monitoring, audits, IRB/IEC review, and regulatory 
inspection(s) by providing direct access to source data/documents. 
11. ADMINISTRATIVE PROCEDURES 
11.1. Adherence to Protocol 
Excluding an emergency situation in which proper treatment is required for the protection, safety 
and well-being of the study subjects, the study will be conducted as described in the approved 
protocol and performed according to ICH/GCP and FDA guidelines. Any deviation from the 
protocol will be recorded and explained. 
If amendments to the protocol and/or amendments or revisions to the ICF are required, the 
modifications will be documented and submitted to an IRB for approval. 


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11.2. Investigator Responsibilities 
The form “Qualified Investigator Undertaking” will be signed by the Investigator responsible for 
the medical decisions and care provided to the subjects (being also referred to as the “Qualified 
Investigator”) at each site prior to the commencement of his responsibilities with respect to the 
clinical trial, as required by the Food and Drug Regulations. The undertaking form will be 
maintained with the trial records and will be made available upon request. 
In addition, the FDA 1572 form, Statement of Investigator [Title 21, CFR Part 312], duly signed 
by the Principal Investigator and/or the Principal Investigator (if in charge of clinical assessment) 
as a condition for conducting the clinical investigation will be kept on file and will be available 
upon request. 
11.3. Delegation of Investigator Duties 
The Principal Investigator will ensure that all personnel involved in the trial are adequately 
qualified and informed about the protocol, any amendments to the protocol, the study treatments, 
and their trial-related duties and functions. 
The Principal Investigator will maintain a list of sub-investigator and other appropriately-
qualified persons to whom he delegates significant trial-related duties. 
Should the Principal Investigator delegate the supervision of the investigational product 
administration to a designated person, this individual must have the appropriate medical 
qualifications to effectively conduct or supervise any potential resuscitation procedures. 
11.4. Premature Termination or Suspension of a Study 
The sponsor or its representative may terminate the study at any time for scientific or corporate 
reasons. 
If the trial is prematurely terminated or suspended for any reason, Algorithme Pharma or the 
Principal Investigator should promptly inform the trial subjects, should assure appropriate 
therapy and follow-up for the subjects and should inform the regulatory authority (ies) when 
required. All procedures should be done according to clinical site procedures. 
11.5. Clinical Trial Application (CTA) 
A CTA must be submitted to Health Canada prior to the study, and a “No Objection Letter” 
(NOL) must be obtained before any drug administration. 
11.6. Exemption Application for Controlled Substances 
This trial does not involve a controlled substance. 
11.7. Publications 
The preparation and submission for publication of a manuscript containing the study results shall 
be in accordance with a process determined by mutual written agreement among the study 


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sponsor and participating institutions. The publication or presentation of any study results shall 
comply with all applicable privacy laws. 


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12. REFERENCES 
Investigational Brochure, Lasmiditan (COL-144), version 8.0, February 23, 2016 


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APPENDIX 01 
AMENDMENT 01 
 
 
RATIONALE: 
 
Reason for amendment: 
To update the blood volume required per PK sample and in 
the study. 
 
Requested by:  
 
CoLucid Pharmaceuticals, Inc. 
 
TEXT OF AMENDMENT: 
 
Amendment 01: 
 
1) Protocol, p. 32, Section 6.1.7 Pharmacokinetic Sampling, Changed: 
'Blood samples will be collected in one tube of 5 mL each.' 
To 
'Blood samples will be collected in one tube of 6 mL each.' 
2) Protocol, p. 32, Section 6.1.7 Pharmacokinetic Sampling, Changed: 
'The total volume of blood withdrawn, including ~21 mL required for screening, on-
study and poststudy tests, should not exceed 111 mL per subject.' 
To 
'The total volume of blood withdrawn, including ~21 mL required for screening, on-
study and poststudy tests, should not exceed 129 mL per subject.' 


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3) ICF, p. 5, Section Blood Sampling, Changed: 
'The first sample (1 x 5 mL, approximately 1 teaspoon) will be collected prior to the 
administration of the drug. All other samples (1 x 5 mL each, approximately 1 
teaspoon each) will be collected following drug administration.' 
To 
'The first sample (1 x 6 mL, approximately 1 teaspoon) will be collected prior to the 
administration of the drug. All other samples (1 x 6 mL each, approximately 1 
teaspoon each) will be collected following drug administration.' 
4) ICF, p. 5, Section Blood Sampling, Changed: 
'The total volume of blood drawn over an approximate 35-day period (including the 
screening period), including the volume necessary for the laboratory tests, should not 
exceed 111 mL (about ½ cup) per participant.' 
To 
'The total volume of blood drawn over an approximate 35-day period (including the 
screening period), including the volume necessary for the laboratory tests, should not 
exceed 129 mL (about ½ cup) per participant.' 
5) FCE, p. 5, Section Prélèvements sanguins, Changed: 
'Le premier échantillon (1 x 5 mL, environ 1 cuillère à thé) sera prélevé avant 
l'administration du médicament. Tous les autres échantillons (1 x 5 mL chacun, 
environ 1 cuillère à thé chacun) seront prélevés suivant la prise du médicament.' 
To 
'Le premier échantillon (1 x 6 mL, environ 1 cuillère à thé) sera prélevé avant 
l'administration du médicament. Tous les autres échantillons (1 x 6 mL chacun, 
environ 1 cuillère à thé chacun) seront prélevés suivant la prise du médicament.' 
6) FCE, p. 6, Section Prélèvements sanguins, Changed: 
'Le volume total de sang prélevé sur une période d’environ 35 jours (incluant la 
période de sélection), y compris celui nécessaire pour les tests de laboratoire, ne 
devrait pas excéder 111 mL (environ ½ tasse) par participant.' 
To 


PPD
PPD

SAP_001.pdf: 
Statistical Analysis Plan (V4) H8H-CD-LAHN (COL MIG-113)
A Phase I, Multicenter, Open-Label, Parallel-Group Adaptive Pharmacokinetic 
Single Dose Study of Oral Lasmiditan in Subjects With Normal and Impaired Renal 
Function
NCT03009162 
Approval Date: 15-Feb-2018


Clinical Study Report  
Project No COL MIG-113/H8H-CD-LAHN 
 
16.1.9 
Documentation of Statistical Methods 
16.1.9.1 Statistical analysis plan (SAP)  
16.1.9.2 Documentation of statistical analysis – SAS® output of Lasmiditan 
16.1.9.3 Documentation of statistical analysis – SAS® output of (S)-M8 
16.1.9.4 Documentation of statistical analysis – SAS® output of (S,R)-M18 
16.1.9.5 Documentation of statistical analysis – SAS® output of (S,S)-M18 
16.1.9.6 Documentation of statistical analysis – SAS® output of M7 
16.1.9.7 Documentation of statistical analysis – SAS® output of M3 


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STATISTICAL ANALYSIS PLAN 
 
 
For: 
CoLucid Pharmaceuticals, Inc. 
 
SPONSOR PROTOCOL No. COL MIG-113 
 
A Phase I, Multicenter, Open-Label, Parallel-Group Adaptive 
Pharmacokinetic Single Dose Study of Oral Lasmiditan in Subjects 
with Normal and Impaired Renal Function 
 
Algorithme Project No. CUD-P4-001 
 
Prepared by:  
Algorithme Pharma 
575 Armand-Frappier 
Laval, Quebec 
Canada, H7V 4B3 
 
 
Version: Final  4.0 
Date: 2017/02/15 
 
 


.., Altasciences 
C L' N tC Al RfH ARCH 
~ 
ALGORlTHME PHARMA 
STATISTICAL ANALYSIS PlAN APPROVAL 
We have carefully read this Stalislical Analysis Plan and agree it contains the necessary informabon required to handle lhe 
statistical analysis of study data 
-
 
Date 
On behalf of the Sponsor 
Research Protoco' No CUD-P4-001 1 Sponsor Project No COL MIG-113; Version FINAL 4 012018102115 
2 
PPD
PPD
PPD
PPD
PPD


 
Research Protocol No CUD-P4-001 | Sponsor Project No COL MIG-113| Version FINAL 4.0| 2018/02/15 
3 
VERSION CONTROL 
 
Version 
Number 
Version Date Author 
Description of Significant Changes 
from  
Previous Approved Version 
DRAFT 0.1 
2017/04/28 
Sarah Vahey / Josée 
Michaud 
Not Applicable – First Version 
DRAFT 0.2 
2017/05/15 
Sarah Vahey / Josée 
Michaud 
Updated according to client comments 
DRAFT 0.3 
2017/05/25 
Sarah Vahey / Josée 
Michaud 
Updated according to client comments 
FINAL 1.0 
2017/06/07 
Sarah Vahey 
Updated version to Final 
FINAL 2.0 
2017/09/05 
Nolwenn Rondet/Jade 
Huguet  
Updated 
according 
FDA 
recommendations from final 1.0 to Final 
2.0  
FINAL 3.0 
2017/09/22 
Nolwenn 
Rondet/Josée  
Michaud  
Updated 
according 
FDA 
recommendations from final 1.0 to Final 
2.0  
FINAL 3.1 
2017/09/22 
Nolwenn Rondet  
Updated 
according 
FDA 
recommendations from final 1.0 to Final 
2.0 and client comments 
FINAL 3.2 
2017/10/25 
Nolwenn 
Rondet 
/ 
Josée Michaud 
Updated according client comments 
FINAL 3.3 
2017/10/28 
Katia 
Charland 
/ 
Josée Michaud 
Final Version  
FINAL 4.0 
2018/02/15 
Patrick Guorong Chen Amendment 
to 
include 
Tmax 
in 
statistical 
analysis 
and 
L16.2.2.2 
Protocol Deviation 
 
 


 
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CONTENTS 
STATISTICAL ANALYSIS PLAN APPROVAL 
2 
VERSION CONTROL 
3 
ABBREVIATIONS 
6 
1. 
INTRODUCTION 
7 
2. 
STUDY OBJECTIVES 
8 
Primary Objectives 
8 
Secondary Objective 
8 
3. 
STUDY DESIGN 
9 
General Description 
9 
Study procedures 
9 
Randomization and Unblinding Procedure 
9 
4. 
STUDY ENDPOINTS 
10 
Pharmacokinetic Endpoints 
10 
Safety Endpoints 
10 
Sample Size Determination 
10 
5. 
ANALYSIS POPULATIONS 
11 
6. 
STATISTICAL METHODOLOGY 
12 
Analysis Time Points 
12 
Methods for Handling Missing Data 
12 
7. 
STUDY SUBJECTS 
13 
Disposition 
13 
Protocol Deviations 
13 
8. 
DEMOGRAPHIC AND OTHER BASELINE CHARACTERISTICS 
14 
Demographic and Background Characteristics 
14 
Lifestyle 
14 
Medical/Social history 
14 
Prior Medication 
14 
9. 
PHARMACOKINETICS AND STATISTICS 
15 
Pharmacokinetic Analysis 
15 
Statistical Analysis 
15 
10. 
SAFETY 
17 
Adverse Events 
17 
Concomitant Medications 
17 
Extent of Exposure 
17 
Clinical Laboratory Evaluations 
18 
Vital Signs 
18 
Electrocardiogram 
18 
Physical Examination Findings 
18 
Columbia-Suicide Severity Rating Scale (C-SSRS) 
18 
11. 
INTERIM ANALYSES AND DATA SAFETY MONITORING 
19 
12. 
CHANGES TO PROTOCOL-SPECIFIED ANALYSES 
20 
13. 
GENERAL INFORMATION RELATED TO DATA PRESENTATIONS 
21 


 
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PLANNED END-OF-TEXT TABLES 
23 
PLANNED LISTINGS 
25 
APPENDIX A 
28 
STUDY SCHEDULES 
28 
APPENDIX B 
30 
Pharmacokinetic Parameters 
30 
APPENDIX C 
31 
TABLE SHELLS 
31 
APPENDIX D 
47 
PHARMACOKINETIC OUTPUTS SHELLS 
47 
PHARMACOKINETIC FIGURES SHELLS 
53 
APPENDIX E 
64 
LISTING SHELLS 
64 
 
 
 


 
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ABBREVIATIONS 
AE 
Adverse Event 
ANOVA 
Analysis of Variance 
ATC 
AUC 
Anatomical/Therapeutic/Chemical 
Area Under Curve 
BMI 
Body Mass Index 
CI 
Confidence Interval 
CLCR 
Creatinine Clearance 
CNS 
Central Nervous System 
CRF 
Case Report Form 
CS 
Clinically Significant 
C-SSRS 
Columbia-Suicide Severity Rating Scale 
CSR 
Clinical Study Report 
eGRF 
Estimated Glomerular Filtration Rate 
EOS 
End of Study 
ICF 
Informed Consent Form 
MedDRA 
Medical Dictionary for Regulatory Activities 
NCS 
Not Clinically Significant 
PK 
Pharmacokinetic(s) 
SAE 
Serious Adverse Event 
SAP 
Statistical Analysis Plan 
SD 
Standard Deviation 
SE 
Standard Error 
SOC 
System Organ Class 
TEAE 
Treatment-Emergent Adverse Event 
TFLs 
Tables, Figures, and Listings 
WHO-DDE 
WHO Drug Dictionary Enhanced 
 
 
 


 
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1. 
INTRODUCTION 
 
This statistical analysis plan (SAP) provides a detailed description of the statistical methods and procedures to be implemented 
for the analyses of data from Protocol No. COL MIG-113. The analyses described in the SAP are based upon the final protocol 
(Amendment 1) dated 2017/01/06.   
 
 


 
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2. 
STUDY OBJECTIVES 
Primary Objectives 
The primary objective of this study is to evaluate the pharmacokinetic profile of lasmiditan following a single oral 200 mg dose in 
subjects with impaired renal function relative to matched, healthy controls with normal renal function. 
Secondary Objective 
The secondary objective of this study is to assess the safety and tolerability of a single oral 200 mg dose of lasmiditan in subjects 
with normal and impaired renal function.  
 


 
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3. 
STUDY DESIGN  
General Description 
This is a multi-center, open-label, non-randomized, parallel-group, adaptive, single dose study. 
This study will enroll up to 32 subjects using an adaptive design that can include up to 3 groups of 8 subjects with different 
degrees of renal impairment and one group of 8 control subjects with normal renal function. 
First, approximately 16 subjects will be enrolled with severe renal impairment and matched subjects with normal renal function. 
There will be 8 subjects in each of the following groups based on renal function at screening: 

Group 1: Healthy subjects with normal renal function (eGFR ≥ 90 mL/min/1.73m2) 

Group 2: Severe renal impairment subjects (eGFR < 30 mL/min/1.73m2) 
Based on safety and PK results from subjects with severe renal impairment (Group 2), Group 3 (Moderate Renal Impairment) 
and Group 4 (Mild Renal Impairment) will be enrolled if substantial change in the exposure of lasmiditan is observed in subjects 
with severe renal impairment. There will be 8 subjects in each of the following groups based on renal function at screening: 

Group 3: Moderate renal impairment subjects (eGFR 30-59 mL/min/1.73m2) 

Group 4: Mild renal impairment subjects (eGFR 60-89 mL/min/1.73m2) 
All subjects will participate in one treatment period and will receive a single dose of lasmiditan in the fasting state.  
The total duration of each subject’s participation in the study will be 3 days (Day –1 through the last PK sample taken on Day 2), 
not including the screening and follow-up phone call. The total duration of the study is expected to be 35 days, including the 
screening. 
The following treatment regimen will be used: 

Experimental treatment: Lasmiditan 200 mg 
Study procedures 
For complete details on the study assessments to be performed for the study, refer to Appendix A.  
Randomization and Unblinding Procedure 
No randomization will be performed for this study. Instead subjects will be categorized into either the control group of healthy 
volunteers with normal renal function, or into one of the three groups of subjects with varying degrees of renal impairment. 
 
Subjects who withdraw from the study may be replaced. Replacement subjects will not be enrolled for subjects who discontinue 
the study due to treatment-related toxicity.  
 
No unblinding procedure is required, as this in an open-label study. 
 
  
 


 
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4. 
STUDY ENDPOINTS 
Pharmacokinetic Endpoints 
The following plasma and urine PK parameters of lasmiditan will be calculated: Cmax, Tmax, AUC(0-tlast), AUC(0-∞), %AUC(tlast-), 
λz, T1/2, CL/F, Vz/F, Ae(0-t), fe, CLr. 
For all the metabolites [(S)-M8, (S,R)-M18, M7 and (S,S)-M18], the following PK parameters Cmax, Tmax, AUC(0-tlast), AUC(0-∞), 
%AUC(tlast-), λz, Thalf, Ae(0-t), CLr,met and individual metabolic ratio (metabolite AUC/parent AUC) will be calculated, if 
quantifiable. 
Safety Endpoints 
Safety endpoints include: 

Adverse Events   

Clinical Laboratory Tests (hematology, chemistry, urinalysis) 

Vital Signs 

Physical examination  

Concomitant medication 

ECGs 

C-SSRS 
The details of the safety endpoints’ assessment are presented in Section 10. 
Sample Size Determination 
There is no formal statistical sample size calculation for this study. A sample size of 32; including 8 subjects/patients for each 
renal function group (8 subjects with normal renal function, 8 patients with mildly impaired renal function, 8 patients with 
moderately impaired renal function, and 8 with severely impaired renal function) was chosen because it is considered typical for 
studies evaluating the effect of renal function on the pharmacokinetics of a drug. 
 


 
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5. 
ANALYSIS POPULATIONS 
 
Safety Population: 
All subjects who received a dose of study medication will be included in the safety population. This population will be used for all 
demography and safety analyses.  
Pharmacokinetics (PK) Population: 
All subjects who received lasmiditan, had no major protocol deviations, and completed the period with evaluable (sufficient and 
interpretable) data will be included in the PK population. 
If some subjects do not complete the sampling schedule resulting in an inadequately characterized some PK parameters (e.g. 
AUC, VZ/F, λZ), samples of these subjects could be included in the statistical pharmacokinetic analysis for only the evaluable 
parameters. 
 


 
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6. 
STATISTICAL METHODOLOGY 
 
All analyses will be conducted using the SAS software, version 9.4, or higher. Descriptive statistics of the PK data will be 
performed by  Phoenix® WinNonlin® version 6.3 or higher, Phoenix® ConnectTM version 1.3.1 or higher). 
Adverse events and medical history will be classified using the standard MedDRA terminology version 19.1.  
Prior and concomitant medications will be coded with the WHO-DDE dictionary version March 01, 2016. 
In general, all summary tables will be presented for safety population. Summaries will be presented by renal function group.  
In general, the data listings will include all enrolled subjects up to the point of study completion or discontinuation; exceptions will 
be listings pertaining to a subset of subjects only (e.g., subjects with blood sampling time deviations) or a subset of 
records/events (e.g., abnormal laboratory values). 
Categorical variables will be summarized using the PROC FREQ procedure. Continuous variables will be summarized using the 
PROC UNIVARIATE procedure. For log-transformed endpoints, geometric mean, and coefficient of variation will also be 
presented. 
The following general comments also apply to all statistical analyses and data presentations: 

Duration variables in days will be calculated using the general formula: (end date - start date) +1. 

Individual subject listings of all data represented on the CRFs will be provided to facilitate the investigation of 
tabulated values and to allow for the clinical review of all efficacy and safety parameters. 

When assessments are repeated for a given timepoint, only the result which is closes to the dosing time will 
be included in the summary tables. 
The analyses described in this plan are considered a priori, that they have been defined prior to database lock.  Any analyses 
performed subsequent to database lock will be considered post hoc and exploratory.  Post hoc analyses will be labeled as such 
in the corresponding statistical output and identified in the CSR. 
Analysis Time Points  
Unless otherwise specified, the baseline value will be defined as the last non-missing evaluation prior to the first dose of study 
medication. 
Methods for Handling Missing Data  
No imputations of values for missing data will be performed. All data recorded on the case report form will be included in the 
listings that will accompany the clinical study report.   
 
 


 
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7. 
STUDY SUBJECTS 
Disposition 
The subject disposition will be summarized for all subjects enrolled in this study, including: 

The number of subjects enrolled; 

The number of screen failure subjects; 

The number of subjects screened; 

The number and percentage of subjects who completed the study; 

The number and percentage of subjects discontinued from the study by primary reason for discontinuation and overall; 

The number and percentage of subjects included in each of the safety and PK populations. 
The percentages will be calculated using the number of subjects randomized as denominator. 
A listing of subject’s disposition will be provided. A listing of subjects included in each of the analysis populations will also be 
provided. Screen failure subjects will also be presented in a listing. 
Protocol Deviations 
All protocol deviations will be presented in a listing. A separate listing will be generate for Inclusion/exclusion criteria violations.All 
deviations from the scheduled PK sampling time of 2 minutes or more for post dose samples will be taken into consideration for 
the evaluation of PK parameters. 
 
 
 


 
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8. 
DEMOGRAPHIC AND OTHER BASELINE CHARACTERISTICS 
Demographic and Background Characteristics 
Demographic data and baseline characteristics will be presented in a data listing and summarized by renal function group in a 
table. Quantitative assessments to be summarized are age, height, body weight and body mass index (BMI) at screening. 
Subject demographics include sex, age, ethnicity, race and country. Baseline characteristics include height, weight, and BMI. 
Lifestyle 
Alcohol and smoking intake history will be recorded and presented in separate listings. 
Medical/Social history  
Any medical history findings will be recorded and presented in a listing. The listing will include the coding terms (e.g., SOC and 
Preferred Term).  
Prior Medication 
Any medications taken including prescription, nonprescription, OTC (cold and antacid medications), dietary supplements, 
vitamins or herbal medications from screening to the first dose of the study drug will be recorded and presented as prior 
medications in a listing. The listing will include the coding terms (e.g., ATC and Preferred Term).   
 
 
 


 
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9. 
PHARMACOKINETICS AND STATISTICS 
Pharmacokinetic Analysis 
The PK parameters are presented in Section 4 and Appendix B. All reported sampling time deviations (see Section 7) will be 
taken into consideration for evaluation of plasma PK parameters. 
Only quantifiable concentrations will be used to calculate PK parameters. An exception to this rule is made for concentrations 
below the quantification limit (BQL), which will be set to zero when all of the following conditions are met: 

The time points occur before the first quantifiable concentration. 
All other BQL concentrations will be treated as missing sample. 
The pharmacokinetic parameters will be estimated using a non-compartmental approach with a log-linear terminal phase 
assumption. The trapezoidal rule will be used to estimate the area under the curve, and the terminal phase will be estimated by 
maximizing the coefficient of determination estimated from the log-linear regression model. These parameters (AUC(0-∞), 
%AUC(tlast-), λZ, T1/2, CL/F and Vz/F) will be estimated for individual concentration-time profiles only when the terminal log-
linear phase cannot be reliably characterized using the following criteria: 

Phoenix® WinNonlin® Best fit range selection (if adequate):  

R2 of at least 80%  
In the case where less than 3 consecutive measurable plasma concentrations of lasmiditan or its metabolites [(S)-M8, (S,R)-
M18, M7 and (S,S)-M18] is observed, the AUC parameters will not be estimated for that particular analyte. 
Additional pharmacokinetic parameters may be calculated if deemed appropriate. 
Pharmacokinetic analyses and associated descriptive statistics will be generated using Phoenix® WinNonlin® Version 6.3 (or 
higher). 
 
Statistical Analysis  
The natural logarithmic transformation of Cmax, AUC(0-tlast), AUC(0-∞), , Ae(0-t), as well as the rank-transformation of Tmax will be 
used for all statistical inference for the parent (lasmiditan).and all metabolites [(S)-M8, (S,R)-M18, M7 and (S,S)-M18].  
Statistical analyses will be generated using validated SAS® (version 9.4 or higher) using the Reg (and Mixed, if applicable) 
procedure(s). 
The statistical analysis described in this section will be done using both eGFR and Cockcroft-Gault estimate of the creatinine 
clearance. However, analysis using the eGFR will be considered as the primary analysis and the analysis using the Cockcroft-
Gault estimate of the creatinine clearance will be considered as supportive. 
Regression Analysis 
The eGFR and Cockcroft-Gault estimate of creatinine clearance at baseline will be used as separate measures of renal function 
for a regression analysis to evaluate the relationships between estimated renal function and the PK parameters.  
For each log-transformed PK parameter and the rank-transformation of Tmax, a regression analysis will be performed, using a 
model of the form α + β*eGFR+ ε where the errors (ε) will be assumed to be independent and normally distributed with mean 
zero and variance σ2. The parameter β represents the correlation between the relevant PK parameter and eGFR which will be 
treated as a continuous variable. 
The hypothesis of the slope of trend being different from zero will be assumed if the two-sided test of the nullity of the parameter 
β is statistically significant at the 5% level. 


 
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The regression analysis will be repeated for each log-transformed PK parameter and the rank-transformation of Tmax with the 
Cockcroft-Gault estimate of creatinine clearance at baseline. 
Analysis of Variance 
 An analysis of variance (ANOVA) will be performed to assess the difference in the PK parameter among the renal function 
groups. 
The renal function (normal, mild, moderate and severe) will be entered as a fixed effect in the ANOVA model. Pairwise 
comparisons of renal function groups will be generated using the Tukey-Kramer’s procedure of adjustment for multiple 
comparisons (if more than 2 renal function groups) and statistical significance will be assessed at the two-sided 5% level. The 
ratio of geometric LS means (of each renal function group being compared), with a corresponding 90% confidence interval 
(adjusted using Tukey-Kramer’s procedure if applicable), will be computed. Heterogeneity of variance among groups will be 
assumed. 
 
 


 
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10. 
SAFETY 
Adverse Events 
An AE is defined as any untoward medical occurrence in a subject administered a medicinal product and which does not 
necessarily have to have a causal relationship with this treatment. An AE can therefore be any unfavorable and unintended sign 
(for example, an abnormal laboratory finding), symptom, or disease temporally associated with the use of a medicinal product, 
whether or not considered related to this medicinal product. 
A suspected adverse reaction is any AE for which there is a reasonable possibility that the drug caused the AE. ‘Reasonable 
possibility’ means there is evidence to suggest a causal relationship between the drug and the AE. A suspected adverse reaction 
implies a lesser degree of certainty about causality than adverse reaction, which means any AE caused by a drug.  
AEs occurring after the initiation of the treatment are referred to as treatment emergent adverse events (TEAEs). 
 
As an overall summary of AEs, the following will be presented by renal function group and overall: 

Number of reported AEs;  

Number of reported TEAEs;  

Number and percentage of subjects experiencing TEAEs;  

Number and percentage of subjects experiencing a drug-related TEAE (i.e. those with a relationship classified as 
reasonable possibility) 

Number and percentage of TEAEs by relationship to study treatment (i.e. reasonable possibility, no reasonable 
possibility);  

Number and percentage of TEAEs by severity;  

Number of reported SAEs (serious adverse events);  

Number and percentage of subjects experiencing SAEs;  

Number and percentage of subjects experiencing drug-related SAEs; 

Number and percentage of TEAEs leading to withdrawal; and 

SAEs with an outcome of death.  
Frequency tables will be presented by renal function group, system organ class and preferred term that summarize all Treatment 
Emergent Adverse Events (TEAEs) and all drug-related TEAEs.  
Subject listings of all Adverse Events (AEs) including severity and relationship to study drug will be provided. AEs leading to 
withdrawal and SAEs will also be presented in separate listings. 
Concomitant Medications 
Medications taken after the first dose of study drug until after discharge from the study will be recorded. Concomitant 
medications will be presented in a listing. The medication name, active ingredient, dose, units, formulation, route, indication or 
reason taken, code, date and time taken will be presented. The listing will also include the coding terms (e.g., ATC and Preferred 
Term). 
Extent of Exposure 
Details of drug dosing (actual treatment received, actual date and time of administration, dose administered, and route of 
administration) will be listed by subject. 
 
 


 
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Clinical Laboratory Evaluations 
Planned laboratory analyses include: 

General Biochemistry: Sodium, potassium, chloride, glucose, blood urea nitrogen (BUN), creatinine, eGFR, total 
bilirubin, alkaline phosphatase, AST, ALT and albumin; 

Hematology: White cell count with differential (absolute values of neutrophil, lymphocyte, monocyte, eosinophil, and 
basophil), red cell count, hemoglobin, hemoglobin A1c, hematocrit, mean corpuscular volume (MCV), and platelets 
count; 

Urinalysis: Color, appearance, specific gravity, pH, leukocyte, protein, glucose, ketones, bilirubin, blood, nitrite, 
urobilinogen. Microscopic examination will only be performed if the dipstick test is outside of the reference range for 
leukocyte, blood, nitrite or protein 

Other: serology urine drug screen and serum pregnancy. 
Hematology, chemistry and quantitative urinalysis laboratory test results will be summarized by renal function group, parameter 
and visit and will also be presented in a listing 
Separate listings of for serology, urine drug screen and serum pregnancy will also be provided. 
Subject listings of abnormal on-study laboratory values will be provided. Similarly, clinically significant on-study laboratory data 
will be presented in a second listing.   
Vital Signs 
Vital signs will include the measurement of blood pressure, heart rate, oral temperature, and orthostatic blood pressure.  
For all vital signs, raw values, at each time point will be summarized by renal function group, parameter and visit. Vital signs data 
will also be presented in a listing. 
Subject listing of abnormal on-study vital signs values (Out-of-Range – Not Clinically Significant (NCS) or Clinically Significant 
(CS)) will be provided. Similarly, CS on-study vital signs values (Out-of-Range – CS) will be presented in a second listing. 
Electrocardiogram 
A 12-lead ECG will be obtained throughout the study. In some cases, repeat abnormal ECGs may be obtained. 
Raw values at each time point will be summarized by renal function group, parameter and visit and will also be presented in a 
listing. Overall safety assessment will also be presented in the listing. 
A subject listing of abnormal on-study ECG assessments (Abnormal – NCS or Abnormal – CS) will be provided. Similarly, CS on-
study ECG assessments (Abnormal – CS) will be presented in a second listing. 
Physical Examination Findings 
A physical examination will be conducted and will be presented in a listing. 
Columbia-Suicide Severity Rating Scale (C-SSRS) 
The Columbia-Suicide Severity Rating Scale (C-SSRS) is a suicidal ideation rating scale. The scale identifies behaviors and 
thoughts that are associated with an increased risk of suicidal actions in the future.  
Subjects who answer ‘Yes’ to any of the questions on the C-SSRS questionnaire will be presented in a listing. 
 
 


 
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INTERIM ANALYSES AND DATA SAFETY MONITORING 
 
First, subjects with severe renal impairment and healthy subjects with normal renal function will be enrolled. Samples will be 
assayed and PK will be performed. If substantial changes in the exposure of lasmiditan are observed in subjects with severe 
renal impairment compared to subjects with normal renal function, subjects with mild and moderate renal impairment will be 
enrolled. 
Interim analysis of subjects with severe renal impairment and healthy subjects with normal renal function will be performed as 
described in the regression analysis paragraph of Section 9. 
 
 


 
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12. 
CHANGES TO PROTOCOL-SPECIFIED ANALYSES 
 
There is no change from the planned analysis described in the protocol.  The analyses described in the protocol was meant to be 
an overview.  The final analyses is per this statistical analysis plan. 
 
 


 
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13. 
GENERAL INFORMATION RELATED TO DATA PRESENTATIONS 
 
Safety  
 
All programs used to generate statistical analyses will be validated according to Algorithme Pharma’s standard operating 
procedures. 
TFLs will be displayed on letter size paper, 8 ½ inches by 11 inches, using the Courier New font.     
In general, summary statistics for raw variables (i.e., variables measured at the study site or central laboratory) will be displayed 
as follows: if required minima, maxima, means, quartiles, standard deviations and confidence limits will be displayed to the same 
number of decimal places as the raw data; if required medians will be displayed to one additional decimal place.   
Percentages will be displayed to one decimal place. Percentages between 0 and 0.1 (exclusive) will be displayed as ‘<0.1’.  P-
values will be displayed to 3 decimal places. P-values that are less than 0.001 will be displayed as ‘<0.001’.   
The numbers of decimal places for summary statistics of derived variables (i.e., variables that are not measured by the study site 
but are calculated for analysis based on other measured variables) will be determined on a case by case basis.  In general, 
minima and maxima will be displayed to the commonly used unit of precision for the parameter. Means, medians, quartiles, and 
confidence limits will be displayed to one additional decimal place and standard deviations will be displayed to two additional 
decimal places. 
The formats and layouts of TFLs are provided in subsequent sections.  Actual formats and layouts may be altered slightly from 
those presented in the templates as necessary to accommodate actual data or statistics.  Minor format changes will not require 
updates to the SAP. 
The tables and listings listed below are common data displays. Their numbering and general content follow the ICH E3 
guidelines.  Some of the tables and listings may not be applicable/appropriate/necessary for a particular study.  Additional tables 
and listings may be included, provided the numbering scheme remains consistent with ICH E3. 
PK Data 
 
All programs used to generate statistical analyses will be validated according to Algorithme Pharma’s standard operating 
procedures. 
 
TFLs will be displayed on letter size paper, 8 ½ inches by 11 inches, using Tahoma. 
 
Raw variables (i.e., variables measured at the study site or central laboratory) will be displayed with the same number of decimal 
places as received as per bioanalytical laboratory. Derived variables (i.e., variables that are not measured by the study site but 
are calculated for analysis based on other measured variables) will be displayed as follow: 
 

All calculated pharmacokinetic parameter values should be reported to three significant digits. 

Observed concentration data, e.g. Cmax, should be reported as received.  

Observed time data, e.g. Tmax, should be reported as received. 

N and percentage values should be reported as whole numbers, except for the %AUC(tlast-∞). 

Median values should be treated as an observed parameter and reported to the same number of decimal places 
as minimum and maximum values. 
 
Summary statistics of raw variables: minima, mean, geometric mean, median, maxima, and standard deviation, coefficient of 
variation will be displayed with the same number of decimal places as the raw data; 
 


 
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
The following summary statistics will be listed for all variables except Tmax and  T1/2, arithmetic mean, SD, and CV; 
geometric mean and CV; N, minimum, maximum, and median. 

Summary statistics for Tmax, and other discrete parameters, will be limited to N, minimum, maximum, and median.  
Report not calculated (NC) for other statistics 

Summary statistics for T1/2 will be limited to geometric mean and CV; N, minimum, maximum, and median. Report not 
calculated (NC) for other statistics. 
 
Summary statistics of derived variables will be displayed with the same number of decimal places as the derived variable. 


 
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PLANNED END-OF-TEXT TABLES 
 
Demographic Data 
Table 14.1.1 
Subject Disposition – All Subjects 
Table 14.1.2.1 
Summary of Demographic Characteristics (Safety Population) 
Table 14.1.2.2 
Summary of Demographic Characteristics (Pharmacokinetic Population) 
 
Pharmacokinetic Data  
Section 14.2.1.1 
Statistical Analysis – SAS output - Lasmiditan 
Section 14.2.1.2 
Statistical Analysis – SAS output - (S)-M8 
Section 14.2.1.3 
Statistical Analysis – SAS output - (S,R)-M18 
Section 14.2.1.4 
Statistical Analysis – SAS output – M7 
Section 14.2.1.5 
Statistical Analysis – SAS output - (S,S)-M18 
 
 
 
Safety Data 
Tables in this section are based on the safety population unless otherwise stated. 
Table 14.3.1.1 
Summary of Adverse Events  
Table 14.3.1.2 
Summary of Treatment Emergent Adverse Events by System Organ Class and MedDRA 
Preferred Term 
Table 14.3.1.3 
Summary of Drug-Related Treatment Emergent Adverse Events by System Organ Class and 
MedDRA Preferred Term 
Table 14.3.2.1 
Listing of Deaths, Other Serious and Significant Adverse Events 
Table 14.3.2.2 
Listing of Treatment Emergent Adverse Events Leading to Withdrawal 
Table 14.3.4.1 
Listing of Abnormal On-Study Laboratory Values 
Table 14.3.4.2 
Listing of Clinically Significant On-Study Laboratory Values 
Table 14.3.4.3 
Summary of Blood Chemistry 
Table 14.3.4.4 
Summary of Hematology 
Table 14.3.4.5 
Summary of Quantitative Urinalysis 
Table 14.3.5.1 
Listing of Abnormal On-Study Vital Signs Values 
Table 14.3.5.2 
Listing of Clinically Significant On-Study Vital Signs Values 
Table 14.3.5.3 
Summary of Vital Signs 
Table 14.3.6.1 
Listing of Abnormal On-Study ECG Assessments 
Table 14.3.6.2 
Listing of Clinically Significant On-Study ECG Assessments 
Table 14.3.6.3 
Summary of ECG Assessments 
 


 
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PLANNED IN-TEXT TABLES 
PK Parameters of Lasmiditan 
Summary of Statistical Analysis of Lasmiditan 
PK Parameters of (S)-M8 
Summary of Statistical Analysis of (S)-M8 
PK Parameters of (S,R)-M18 
Summary of Statistical Analysis of (S,R)-M18 
PK Parameters of M7 
Summary of Statistical Analysis of M7 
PK Parameters of (S,S)-M18 
Summary of Statistical Analysis of (S,S)-M18 
 
PLANNED IN-TEXT FIGURES 
Linear Profile of the Mean for Lasmiditan  
Logarithmic Profile of the Mean for Lasmiditan 
Linear Regression of ln-Transformed Cmax vs eGFR (Lasmiditan) 
Linear Regression of ln-Transformed AUC(0-tlast) vs eGFR (Lasmiditan) 
Linear Regression of ln-Transformed AUC(0-∞) vs eGFR (Lasmiditan) 
Linear Regression of ln-Transformed CL/F vs eGFR (Lasmiditan) 
Linear Profile of the Mean for (S)-M8  
Logarithmic Profile of the Mean for (S)-M8 
Linear Profile of the Mean for (S,R)-M18  
Logarithmic Profile of the Mean for (S,R)-M18 
Linear Profile of the Mean for M7  
Logarithmic Profile of the Mean for M7 
Linear Profile of the Mean for (S,S)-M18  
Logarithmic Profile of the Mean for (S,S)-M18 
 
 
 


 
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PLANNED LISTINGS 
 
Listing 16.2.1 
Listing of Study Disposition 
Listing 16.2.2.1 
Listing of PK Blood Sampling Time Deviations 
Listing 16.2.2.2 
Listing of Protocol Deviations 
Listing 16.2.3 
Listing of Analysis Populations 
Listing 16.2.4.1 
Listing of Demographic Characteristics 
Listing 16.2.4.2 
Listing of Screen Failure Subjects 
Listing 16.2.5 
Listing of Investigational Product Administration 
Listing 16.2.7 
Listing of Adverse Events  
Listing 16.2.8.1 
Listing of Blood Chemistry 
Listing 16.2.8.2 
Listing of Hematology 
Listing 16.2.8.3 
Listing of Urinalysis 
Listing 16.2.8.4 
Listing of Urine Drug Screen 
Listing 16.2.8.5 
Listing of Pregnancy Test 
Listing 16.2.8.6 
Listing of Serology 
Listing 16.2.9.1 
Listing of Alcohol Habits 
Listing 16.2.9.2 
Listing of Smoking Habits 
Listing 16.2.9.3 
Listing of Prior Medication 
Listing 16.2.9.4 
Listing of Concomitant Medication 
Listing 16.2.9.5 
Listing of Physical Examination 
Listing 16.2.9.6 
Listing of Vital Signs 
Listing 16.2.9.7 
Listing of ECG Assessments 
Listing 16.2.9.8 
Listing of Inclusion/Exclusion Criteria Summary  
Listing 16.2.9.9 
Listing of Medical History 
Listing 16.2.9.10 
Listing of Columbia-Suicide Severity Rating Scale (C-SSRS) 
 
Pharmacokinetic Data 
Appendix 16.2.6 
PK Data 
Appendix 16.2.6.1 
Lasmiditan 
Appendix 16.2.6.1.1 
PK Tables – Plasma 

Table X. Measured Human Plasma Concentrations  

Table X. Cumulative Area Under the Curve  

Table X. Pharmacokinetic Parameters  

Table X. Elimination Parameters  

Table X. Actual Sampling Time 
Appendix 16.2.6.1.2 
PK Tables – Urine  

Table X. Measured Human Urine Concentrations  

Table X. Cumulative Amount by Collection Intervals  

Table X. Pharmacokinetic Parameters  
Appendix 16.2.6.1.3 
PK – Figures – Plasma 

Figure x: Linear Profile of the Mean 

Figure x: Logarithmic Profile of the Mean  

Figure x: Individual Linear Profile of Subject x  

Figure x: Individual Logarithmic Profile of Subject x 

Figure x: Individual Elimination Profiles  
Appendix 16.2.6.2 
(S)-M8 
Appendix 16.2.6.2.1 
PK Tables – Plasma 

Table X. Measured Human Plasma Concentrations  


 
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
Table X. Cumulative Area Under the Curve  

Table X. Pharmacokinetic Parameters  

Table X. Elimination Parameters  

Table X. Actual Sampling Time 
Appendix 16.2.6.2.2 
PK Tables – Urine Table X. Measured Human Urine Concentrations  

Table X. Cumulative Amount by Collection Intervals  

Table X. Pharmacokinetic Parameters  
Appendix 16.2.6.2.3 
PK – Figures – Plasma 

Figure x: Linear Profile of the Mean 

Figure x: Logarithmic Profile of the Mean  

Figure x: Individual Linear Profile of Subject x  

Figure x: Individual Logarithmic Profile of Subject x 

Figure x: Individual Elimination Profiles  
Appendix 16.2.6.3 
 (S,R)-M18 
Appendix 16.2.6.3.1 
PK Tables – Plasma 

Table X. Measured Human Plasma Concentrations  

Table X. Cumulative Area Under the Curve  

Table X. Pharmacokinetic Parameters  

Table X. Elimination Parameters  

Table X. Actual Sampling Time 
Appendix 16.2.6.3.2 
PK Tables – Urine Table X. Measured Human Urine Concentrations  

Table X. Cumulative Amount by Collection Intervals  

Table X. Pharmacokinetic Parameters  
Appendix 16.2.6.3.3 
PK – Figures – Plasma 

Figure x: Linear Profile of the Mean 

Figure x: Logarithmic Profile of the Mean  

Figure x: Individual Linear Profile of Subject x  

Figure x: Individual Logarithmic Profile of Subject x 

Figure x: Individual Elimination Profiles  
Appendix 16.2.6.4 
 (S,S)-M18 
Appendix 16.2.6.4.1 
PK Tables – Plasma 

Table X. Measured Human Plasma Concentrations  

Table X. Cumulative Area Under the Curve  

Table X. Pharmacokinetic Parameters  

Table X. Elimination Parameters  

Table X. Actual Sampling Time 
Appendix 16.2.6.4.2 
PK Tables – Urine Table X. Measured Human Urine Concentrations  

Table X. Cumulative Amount by Collection Intervals  

Table X. Pharmacokinetic Parameters  
Appendix 16.2.6.4.3 
PK – Figures – Plasma 

Figure x: Linear Profile of the Mean 

Figure x: Logarithmic Profile of the Mean  

Figure x: Individual Linear Profile of Subject x  

Figure x: Individual Logarithmic Profile of Subject x 

Figure x: Individual Elimination Profiles  
Appendix 16.2.6.5 
M7 
Appendix 16.2.6.5.1 
PK Tables – Plasma 

Table X. Measured Human Plasma Concentrations  

Table X. Cumulative Area Under the Curve  

Table X. Pharmacokinetic Parameters  

Table X. Elimination Parameters 

Table X. Actual Sampling Time 


 
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Appendix 16.2.6.5.2 
PK Tables – Urine Table X. Measured Human Urine Concentrations  

Table X. Cumulative Amount by Collection Intervals  
Table X. Pharmacokinetic Parameters  
Appendix 16.2.6.5.3 
PK – Figures – Plasma 

Figure x: Linear Profile of the Mean 

Figure x: Logarithmic Profile of the Mean  

Figure x: Individual Linear Profile of Subject x 

Figure x: Individual Logarithmic Profile of Subject x  

Figure x: Individual Elimination Profiles 
 
 
 
 


 
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APPENDIX A 
STUDY SCHEDULES 
  
a Early Termination (ET). 
b Vital signs will be measured prior to dosing and approximately 2 and 4 hours after study drug administration. 


 
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c 12-lead ECG will be performed prior to dosing and approximately 2 hours after study drug administration. 
d Clinical laboratory tests (hematology, biochemistry, and urinalysis) will be performed in the evening prior to drug administration. 
e PK blood and urine samples will be collected according to schedule of PK assessments.  
 


 
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APPENDIX B 
Pharmacokinetic Parameters 
PK Parameter 
Definition 
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* Not calculated for metabolites 
 
 


 
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APPENDIX C 
TABLE SHELLS 
 
 


 
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CoLucid Pharmaceuticals, Inc. 
Algorithme Pharma 
Project #  COL MIG-113/CUD-P4-001 
     Page 1 of x 
 
Table 14.1.1 
Subject Disposition 
(All Subjects) 
 
   
   
Healthy Renal 
Function 
(N=XX) 
 
Severe Renal 
Function 
(N=XX) 
Overall 
(N=XX) 
  
  
 
 
 
 
Subjects Enrolled 
 
 
 
 
xx 
 
 
 
 
 
 
Screen Fail Subjects 
 
 
 
 
xx 
 
 
 
 
 
 
Subjects Screened [N] 
 
 
 
 
xx (xx.x) 
 
 
 
 
 
 
Subjects Completed the Study [n(%)] 
YES 
 
 
 
xx (xx.x) 
 
NO 
 
 
 
xx (xx.x) 
 
 
 
 
 
 
If No, Reason of Study Discontinuation [n(%)] 
Reason 1 
 
 
 
xx (xx.x) 
 
Reason 2 
 
 
 
xx (xx.x) 
 
Reason 3 
 
 
 
xx (xx.x) 
 
Etc. 
 
 
 
xx (xx.x) 
 
 
 
 
 
 
Number of Subjects Included in Each Analysis 
Population [n(%)] 
Safety Population 
 
 
 
xx (xx.x) 
 
Pharmacokinetic Population 
 
 
 
xx (xx.x) 
 
 
 
 
 
 
Programming Note: Please add Moderate and Mild Renal Function Groups to the table if enrolled 
  
  
 
 
 
 
 
Note: The percentages are based on the number of subjects screened. 
 
 
 
Date: VERSION – YYYY-MM-DD 
Data Source: XXXX 
Program Source:  XXXXX.sas 
 
 
 
 


 
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CoLucid Pharmaceuticals, Inc. 
Algorithme Pharma 
Project #  COL MIG-113/CUD-P4-001 
     Page 1 of x 
 
Table 14.1.2.1 
Summary of Demographic Characteristics 
(Safety Population) 
 
   
   
Healthy Renal 
Function 
(N=XX) 
 
Severe Renal 
Function 
 (N=XX) 
Etc. 
Overall 
(N=XX) 
 
  
  
 
 
 
 
 Age (years) 
N 
xx 
xx 
xx 
xx 
  
Mean (SD) 
xx (xx.x) 
xx (xx.x) 
xx (xx.x) 
xx (xx.x) 
  
Median 
xx.x 
xx.x 
xx.x 
xx.x 
  
Min, Max 
xx, xx 
xx, xx 
xx, xx 
xx, xx 
  
 
 
 
 
 
 Gender [n(%)] 
MALE 
xx (xx.x) 
xx (xx.x) 
xx (xx.x) 
xx (xx.x) 
  
FEMALE 
 
 
 
 
  
 
 
 
 
 
 Ethnicity [n(%)] 
HISPANIC/LATINO 
xx (xx.x) 
xx (xx.x) 
xx (xx.x) 
xx (xx.x) 
  
NOT HISPANIC/NOT LATINO 
xx (xx.x) 
xx (xx.x) 
xx (xx.x) 
xx (xx.x) 
  
 
 
 
 
 
 Race [n(%)] 
RACE1 
xx (xx.x) 
xx (xx.x) 
xx (xx.x) 
xx (xx.x) 
  
RACE2 
xx (xx.x) 
xx (xx.x) 
xx (xx.x) 
xx (xx.x) 
  
Etc. 
xx (xx.x) 
xx (xx.x) 
xx (xx.x) 
xx (xx.x) 
  
 
 
 
 
 
 Weight (kg) 
N 
xx 
xx 
xx 
xx 
  
Mean (SD) 
xx (xx.x) 
xx (xx.x) 
xx (xx.x) 
xx (xx.x) 
  
Median 
xx.x 
xx.x 
xx.x 
xx.x 
  
Min, Max 
xx, xx 
xx, xx 
xx, xx 
xx, xx 
  
 
 
 
 
 
 Height (cm) 
N 
xx 
xx 
xx 
xx 
  
Mean (SD) 
xx (xx.x) 
xx (xx.x) 
xx (xx.x) 
xx (xx.x) 
  
Median 
xx.x 
xx.x 
xx.x 
xx.x 
  
Min, Max 
xx, xx 
xx, xx 
xx, xx 
xx, xx 
  
 
 
 
 
 
 Body Mass Index(kg/m2) 
N 
xx 
xx 
xx 
xx 
  
Mean (SD) 
xx (xx.x) 
xx (xx.x) 
xx (xx.x) 
xx (xx.x) 
  
Median 
xx.x 
xx.x 
xx.x 
xx.x 
  
Min, Max 
xx, xx 
xx, xx 
xx, xx 
xx, xx 
 Programming Note: Please add Moderate and Mild Renal Function Groups to the table if enrolled 
 
 
  
 
 
 
 
 
Date: VERSION – YYYY-MM-DD 
Data Source: XXXX 
Program Source:  XXXXX.sas 
 
 
 


 
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Similar Table: 
 
Table 14.1.2.2 Summary of Demographic Characteristics (Pharmacokinetic Population) 
 
 
 
 


 
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CoLucid Pharmaceuticals, Inc. 
Algorithme Pharma 
Project #  COL MIG-113/CUD-P4-001 
     Page 1 of x 
Table 14.3.1.1 
Summary of Adverse Events  
(Safety Population) 
 
   
 
 
 
 
 
 
Healthy Renal 
Function 
(N=XX) 
 
Severe Renal 
Function 
(N=XX) 
Etc. 
Overall 
(N=XX) 
 
 
  
  
 
 
 
 
 Adverse Events (AEs) Reported [n] 
 
 
 
xx 
 
 
 
 
 
 
 
 
 Treatment Emergent Adverse Events (TEAEs) Reported [n] 
xx 
xx 
xx 
xx 
 
 
 
 
 
 
 
 
Subjects With At Least One TEAE [n(%)]  [1] 
xx (xx.x) 
xx (xx.x) 
xx (xx.x) 
xx (xx.x) 
 
 
 
 
 
 
 
Subjects With At Least One Drug-Related TEAE [n(%)] [1] 
[3] 
xx (xx.x) 
xx (xx.x) 
xx (xx.x) 
xx (xx.x) 
 
 
 
 
 
 
 
TEAEs Relationship  [2] 
 
 
 
 
 
Related [n(%)] [3] 
xx (xx.x) 
xx (xx.x) 
xx (xx.x) 
xx (xx.x) 
 
Not Related [n(%)] 
xx (xx.x) 
xx (xx.x) 
xx (xx.x) 
xx (xx.x) 
 
 
 
 
 
 
 
TEAEs Severity/Intensity  [2] 
 
 
 
 
 
Mild [n(%)]   
xx (xx.x) 
xx (xx.x) 
xx (xx.x) 
xx (xx.x) 
 
Moderate [n(%)]   
xx (xx.x) 
xx (xx.x) 
xx (xx.x) 
xx (xx.x) 
 
Severe [n(%)]   
xx (xx.x) 
xx (xx.x) 
xx (xx.x) 
xx (xx.x) 
 
 Life-Threatening [n(%)] 
xx (xx.x) 
xx (xx.x) 
xx (xx.x) 
xx (xx.x) 
 
 
 
 
 
 
 
 Serious Adverse Events (SAEs) Reported [n] [2] 
xx 
xx 
xx 
xx 
 
 
 
 
 
 
 
Subjects With At Least One SAE [n(%)][1] 
xx (xx.x) 
xx (xx.x) 
xx (xx.x) 
xx (xx.x) 
 
 
 
 
 
 
 
Subject With an TEAE Leading to Withdrawal [n(%)] [1] 
xx (xx.x) 
xx (xx.x) 
xx (xx.x) 
xx (xx.x) 
 
 
 
 
 
 
 
Death [n(%)]  [1] 
xx (xx.x) 
xx (xx.x) 
xx (xx.x) 
xx (xx.x) 
 
  
 
  
 
 
 
 
 Programming Note: Please add Moderate and Mild Renal Function Groups to the table if enrolled 
 
[1] Percentages are based on the number of subjects in the Safety population in each treatment group. 
[2] Percentages are based on the total number of treatment emergent adverse events reported in each treatment group. 
[3] TEAE that was reported with a relationship of “reasonable possibility”. 
Date: VERSION – YYYY-MM-DD 
Data Source: XXXX 
Program Source:  XXXXX.sas 


 
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CoLucid Pharmaceuticals, Inc. 
Algorithme Pharma 
Project #  COL MIG-113/CUD-P4-001 
     Page 1 of x 
 
Table 14.3.1.2 
Summary of Treatment Emergent Adverse Events by System Organ Class and MedDRA Preferred Term 
(Safety Population) 
 
   
   
 
 
 
  SOC 
   MedDRA Preferred Term 
 Healthy Renal 
Function 
(N=XX) 
 
Severe Renal Function 
(N=XX) 
Etc. 
 
 
  
  
 
 
 
 
 
 
 
 
 
 Subjects With At Least One TEAE [n(%)] 
 
xx (xx.x) 
xx (xx.x) 
 
  
 
 
 
 
 System Organ Class 1 [n(%)] 
 
xx (xx.x) 
xx (xx.x) 
 
   MedDRA Term 11 [n(%)] 
 
xx (xx.x) 
xx (xx.x) 
 
   MedDRA Term 12 [n(%)] 
 
xx (xx.x) 
xx (xx.x) 
 
   MedDRA Term 13 [n(%)] 
 
xx (xx.x) 
xx (xx.x) 
 
  
 
 
 
 
 System Organ Class 2 [n(%)] 
 
xx (xx.x) 
xx (xx.x) 
 
   MedDRA Term 21 [n(%)] 
 
xx (xx.x) 
xx (xx.x) 
 
   MedDRA Term 22 [n(%)] 
 
xx (xx.x) 
xx (xx.x) 
 
   MedDRA Term 23 [n(%)] 
 
xx (xx.x) 
xx (xx.x) 
 
   Etc. 
 
xx (xx.x) 
xx (xx.x) 
 
  
 
 
 
 
 
 
  
 
 
 
 Programming Note: Please add Moderate and Mild Renal Function Groups to the table if enrolled 
 
 
Note: Each treatment emergent adverse event is counted only once for each subject within each System Organ Class and MedDRA 
Preferred Term. 
 
 
Date: VERSION – YYYY-MM-DD 
Data Source: XXXX 
Program Source:  XXXXX.sas 
 
 
Similar Table: Table 14.3.1.3 Summary of Drug-Related Treatment Emergent Adverse Events by System Organ Class and MedDRA Preferred Term 
 
 
 
 
 


 
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CoLucid Pharmaceuticals, Inc. 
Algorithme Pharma 
Project #  COL MIG-113/CUD-P4-001 
     Page 1 of x 
 
Table 14.3.2.1 
Listing of Deaths, Other Serious and Significant Adverse Events 
(Safety Population) 
 
Subject ID 
Day/ 
Group/ 
AE # 
SOC 
  MedDRA 
Preferred Term 
    Description 
of AE 
Onset Date  
Time 
(Time since 
Last Dose) 
Resolution 
Date Time 
(Duration) 
I: Maximal 
Intensity 
R: Causality 
Assessment 
O: Outcome 
S: Serious AE 
D: AE Lead To 
Discontinuation 
Action Taken With Study 
Treatment / Other 
Action(s) Taken / 
Concomitant Given 
 
 
 
  
  
 
 
 
 
 
xxx 
xxxxx 
xxxxx 
xxxxxxxxxxxx 
  xxxxxxxxxxxx 
     
xxxxxxxxxxxx 
YYYY-MM-DD/ 
HH:MM 
(DD:HH:MM) 
YYYY-MM-
DD/ 
HH:MM 
(DD:HH:MM) xxxxxx 
xxxxx 
xxxxxx 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
  
 
  
 
 
 
 
 
 
 
 
Date: VERSION – YYYY-MM-DD 
Data Source: XXXX 
Program Source:  XXXXX.sas 
 
 
Similar Tables:  
14.3.2.2  Listing of Adverse Events Leading to Withdrawal 
 
 
 


 
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CoLucid Pharmaceuticals, Inc. 
Algorithme Pharma 
Project #  COL MIG-113/CUD-P4-001 
     Page 1 of x 
 
Table 14.3.4.1 
Listing of Abnormal On-Study Laboratory Values 
(Safety Population) 
 
Category/ 
Parameter (Unit) 
Reference 
Range 
Subject ID 
Visit 
 
 
Date / Time 
 
Value 
 
Out-of-Range 
Flag 
Assessment [1] 
 
 
 
  
 
 
 
 
 
 
Lab Category 1 
 
 
 
 
  
  
 
  Lab Test 11 
xxx-xxx 
xxx 
xxxxxx 
xxxxxx 
 
xxx 
 
xxx 
xxx 
 
 
 
 
 
 
 
 
 
 
  Lab Test 12 
xxx-xxx 
xxx 
xxxxxx 
xxxxxx 
 
xxx 
 
xxx 
xxx 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Lab Category 2 
 
 
 
 
 
 
 
 
 
  Lab Test 21 
xxx-xxx 
xxx 
xxxxxx 
xxxxxx 
 
xxx 
 
xxx 
xxx 
 
 
 
 
 
 
 
 
 
 
  Lab Test 22 
xxx-xxx 
xxx 
xxxxxx 
xxxxxx 
 
xxx 
 
xxx 
xxx 
 
 
 
 
 
 
 
 
 
 
  Etc. 
xxx-xxx 
xxx 
xxxxxx 
xxxxxx 
 
xxx 
 
xxx 
xxx 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
  
 
 
 
 
 
 
 
 
 
 
 
[1] NCS: Not Clinically Significant   /   CS: Clinically Significant   /   RPT: Repeated   /  TBC: To Be Controlled. 
Note(s): Abnormal values are determined by applying the reference ranges to the results as reported by the external laboratory 
analysis. 
 
Date: VERSION – YYYY-MM-DD 
Data Source: XXXX 
Program Source:  XXXXX.sas 
 
 
 


 
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Project #  COL MIG-113/CUD-P4-001 
     Page 1 of x 
 
Table 14.3.4.2 
Listing of Clinically Significant On-Study Laboratory Values 
(Safety Population) 
 
Category/ 
Parameter (Unit) 
Reference Range 
Subject ID 
Visit 
 
 
Date / Time 
 
Value 
 
Out-of-
Range Flag  Assessment [1] 
 
 
 
  
 
 
 
 
 
 
Lab Category 1 
 
 
 
 
  
  
 
  Lab Test 11 
xxx-xxx 
xxx 
xxxxxx 
xxxxxx 
 
xxx 
 
xxx 
xxx 
 
 
 
 
 
 
 
 
 
 
  Lab Test 12 
xxx-xxx 
xxx 
xxxxxx 
xxxxxx 
 
xxx 
 
xxx 
xxx 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Lab Category 2 
 
 
 
 
 
 
 
 
 
  Lab Test 21 
xxx-xxx 
xxx 
xxxxxx 
xxxxxx 
 
xxx 
 
xxx 
xxx 
 
 
 
 
 
 
 
 
 
 
  Lab Test 22 
xxx-xxx 
xxx 
xxxxxx 
xxxxxx 
 
xxx 
 
xxx 
xxx 
 
 
 
 
 
 
 
 
 
 
  Etc. 
xxx-xxx 
xxx 
xxxxxx 
xxxxxx 
 
xxx 
 
xxx 
xxx 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
  
 
 
 
 
 
 
 
 
 
 
 
[1] CS: Clinically Significant   /   RPT: Repeated    /    TBC: To Be Controlled 
Note(s): Abnormal values are determined by applying the reference ranges to the results as reported by the external laboratory 
analysis. 
 
Date: VERSION – YYYY-MM-DD 
Data Source: XXXX 
Program Source:  XXXXX.sas 
 
 
 
 
 
 


 
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CoLucid Pharmaceuticals, Inc. 
Algorithme Pharma 
Project #  COL MIG-113/CUD-P4-001 
     Page 1 of x 
Table 14.3.4.3 
Summary of Blood Chemistry 
(Safety Population) 
 
   
 
 
   
 
 
 
 
Parameter (unit) 
Visit Name 
 
Statistic   
 Healthy Renal 
Function(N=XX) 
Severe Renal 
Function 
 (N=XX) 
Etc. (N=XX) 
 
 
 
 
 
 
 
 
 
xxx (xxx) 
Screening 
Value 
N 
xx 
xx 
xx 
xx 
 
 
 
Mean (SD) 
xx.x (xx.xx) 
xx.x (xx.xx) 
xx.x (xx.xx) 
xx.x (xx.xx) 
 
 
 
Median 
xx.x 
xx.x 
xx.x 
xx.x 
 
 
 
Min, Max 
xx, xx 
xx, xx 
xx, xx 
xx, xx 
 
 
 
 
 
 
 
 
 
Day -1 
Value 
N 
xx 
xx 
xx 
xx 
 
 
 
Mean (SD) 
xx.x (xx.xx) 
xx.x (xx.xx) 
xx.x (xx.xx) 
xx.x (xx.xx) 
 
 
 
Median 
xx.x 
xx.x 
xx.x 
xx.x 
 
 
 
Min, Max 
xx, xx 
xx, xx 
xx, xx 
xx, xx 
 
 
 
 
 
 
 
 
 
Etc. 
 
N 
xx 
xx 
xx 
xx 
 
 
 
Mean (SD) 
xx.x (xx.xx) 
xx.x (xx.xx) 
xx.x (xx.xx) 
xx.x (xx.xx) 
 
 
 
Median 
xx.x 
xx.x 
xx.x 
xx.x 
 
 
 
Min, Max 
xx, xx 
xx, xx 
xx, xx 
xx, xx 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Programming Note: Please add Moderate and Mild Renal Function Groups to the table if enrolled 
 
 
 
 
 
 
 
 
 
 
Date: VERSION – YYYY-MM-DD 
Data Source: XXXX 
Program Source:  XXXXX.sas 
 
Similar Tables:  
14.3.4.4  Summary of Hematology 
14.3.4.5   Summary of Quantitative Urinalysis 
 
 


 
Research Protocol No CUD-P4-001 | Sponsor Project No COL MIG-113| Version FINAL 4.0| 2018/02/15 
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CoLucid Pharmaceuticals, Inc. 
Algorithme Pharma 
Project #  COL MIG-113/CUD-P4-001 
     Page 1 of x 
Table 14.3.5.1 
Listing of Abnormal On-Study Vital Signs Values 
(Safety Population) 
Assessment (Units) Subject ID 
Visit 
 
Elapsed 
Time 
 
Position 
Date / Time 
 Value 
Safety Review 
 
 
  
 
 
 
 
 
 
 
 
 
 
 
 
 
  
 
Vital Sign Test 1 
xxx 
xxxxxx 
 
xxxxxx 
xxxxxx 
YYYY-MM-DD:XX:XX 
 
xxx 
xxx 
 
 
 
 
 
 
 
 
 
 
xxx 
xxxxxx 
 
xxxxxx 
xxxxxx 
YYYY-MM-DD:XX:XX 
 
xxx 
xxx 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Vital Sign Test 2 
xxx 
xxxxxx 
 
xxxxxx 
xxxxxx 
YYYY-MM-DD:XX:XX 
 
xxx 
xxx 
 
 
 
 
 
 
 
 
 
xxx 
xxxxxx 
 
xxxxxx 
xxxxxx 
YYYY-MM-DD:XX:XX 
 
xxx 
xxx 
 
 
 
 
 
 
 
 
 
Etc. 
xxx 
xxxxxx 
 
xxxxxx 
xxxxxx 
YYYY-MM-DD:XX:XX 
 
xxx 
xxx 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
  
 
 
 
 
 
 
 
 
 
Date: VERSION – YYYY-MM-DD 
Data Source: XXXX 
Program Source:  XXXXX.sas 
 
 
 


 
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CoLucid Pharmaceuticals, Inc. 
Algorithme Pharma 
Project #  COL MIG-113/CUD-P4-001 
     Page 1 of x 
Table 14.3.5.2 
Listing of Clinically Significant On-Study Vital Signs Values 
(Safety Population) 
Assessment (Units) Subject ID 
Visit 
 
Elapsed 
Time 
 
Position 
Date / Time 
 Value 
Safety Review 
 
 
  
 
 
 
 
 
 
 
 
 
 
 
 
 
  
 
Vital Sign Test 1 
xxx 
xxxxxx 
 
xxxxxx 
xxxxxx 
YYYY-MM-DD:XX:XX 
 
xxx 
xxx 
 
 
 
 
 
 
 
 
 
 
xxx 
xxxxxx 
 
xxxxxx 
xxxxxx 
YYYY-MM-DD:XX:XX 
 
xxx 
xxx 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Vital Sign Test 2 
xxx 
xxxxxx 
 
xxxxxx 
xxxxxx 
YYYY-MM-DD:XX:XX 
 
xxx 
xxx 
 
 
 
 
 
 
 
 
 
xxx 
xxxxxx 
 
xxxxxx 
xxxxxx 
YYYY-MM-DD:XX:XX 
 
xxx 
xxx 
 
 
 
 
 
 
 
 
 
Etc. 
xxx 
xxxxxx 
 
xxxxxx 
xxxxxx 
YYYY-MM-DD:XX:XX 
 
xxx 
xxx 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
  
 
 
 
 
 
 
 
 
 
Date: VERSION – YYYY-MM-DD 
Data Source: XXXX 
Program Source:  XXXXX.sas 
 
 
 
 


 
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CoLucid Pharmaceuticals, Inc. 
Algorithme Pharma 
Project #  COL MIG-113/CUD-P4-001 
     Page 1 of x 
Table 14.3.5.3 
Summary of Vital Signs 
(Safety Population) 
 
 
 
 
 
 
 
 
 
 
Parameter (unit) 
 
Visit 
Timepoint 
 
Statistic 
Healthy Renal 
Function 
(N=XX) 
Severe Renal 
Function 
(N=XX) 
Etc. 
(N=XX) 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Vital Sign Test 1 
 
 
 
 
 
 
 
 
Screening 
 
Value 
N 
 
 
xx 
 
 
 
 
Mean (SD) 
 
 
xx (xx.x) 
 
 
 
 
Median 
 
 
xx.x 
 
 
 
 
Min, Max 
 
 
xx, xx 
 
Day 1 
2 Hours 
Value 
 
 
 
 
 
 
 
 
N 
xx 
xx 
xx 
 
 
 
 
Mean (SD) 
xx (xx.x) 
xx (xx.x) 
xx (xx.x) 
 
 
 
 
Median 
xx.x 
xx.x 
xx.x 
 
 
 
 
Min, Max 
xx, xx 
xx, xx 
xx, xx 
 
 
 
 
 
 
 
 
 
Day 1 
4 Hours 
Value 
 
 
 
 
 
 
 
 
N 
xx 
xx 
xx 
 
 
 
 
Mean (SD) 
xx (xx.x) 
xx (xx.x) 
xx (xx.x) 
 
 
 
 
Median 
xx.x 
xx.x 
xx.x 
 
 
 
 
Min, Max 
xx, xx 
xx, xx 
xx, xx 
 
 
 
 
 
 
 
 
Etc. 
Etc. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
PROGRAMMING NOTE:  All visits outlined in Appendix A will be included. Please add Moderate and Mild Renal Function Groups to 
the table if enrolled 
  
 
  
 
 
 
 
 
 
Date: VERSION – YYYY-MM-DD 
Data Source: XXXX 
Program Source:  XXXXX.sas 
 
 


 
Research Protocol No CUD-P4-001 | Sponsor Project No COL MIG-113| Version FINAL 4.0| 2018/02/15 
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CoLucid Pharmaceuticals, Inc. 
Algorithme Pharma 
Project #  COL MIG-113/CUD-P4-001 
     Page 1 of x 
 
Table 14.3.6.1 
Listing of Abnormal On-Study ECG Assessments 
(Safety Population) 
 
Subject ID 
Visit 
Time Point 
Date / Time 
  Position 
Safety Review Parameter (Unit) 
Value 
 
 
 
 
  
 
 
 
 
xxxxx 
xxxxxx 
xxx 
YYYY-MM-DD: HH:MM   xxxxxx 
xxxxxx 
 
 
 
 
 
 
   
 
 
 
 
xxxxxx 
xxx 
YYYY-MM-DD: HH:MM   xxxxxx 
xxxxxx 
 
 
 
xxxxxx 
xxx 
YYYY-MM-DD: HH:MM   xxxxxx 
xxxxxx 
 
 
 
 
 
 
   
 
 
 
 
 
 
 
   
 
 
 
xxxxx 
xxxxxx 
xxx 
YYYY-MM-DD: HH:MM   xxxxxx 
xxxxxx 
 
 
 
 
 
 
   
 
 
 
xxxxx 
xxxxxx 
xxx 
YYYY-MM-DD: HH:MM   xxxxxx 
xxxxxx 
 
 
 
 
 
 
   
 
 
 
 
 
 
 
   
 
 
 
 
 
 
 
   
 
 
 
 
 
 
 
   
 
 
 
 
 
 
 
  
 
 
 
 
 
 
 
 
  
 
 
 
 
 
 
 
 
  
 
 
 
 
 
 
 
 
  
 
 
 
 
  
 
 
 
  
 
 
 
 
 
 
 
Date: VERSION – YYYY-MM-DD 
Data Source: XXXX 
Program Source:  XXXXX.sas 
 
 
 


 
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CoLucid Pharmaceuticals, Inc. 
Algorithme Pharma 
Project #  COL MIG-113/CUD-P4-001 
     Page 1 of x 
 
Table 14.3.6.2 
Listing of Clinically On-Study ECG Assessments 
(Safety Population) 
 
Subject ID 
Visit 
Time Point 
Date / Time 
  
Position 
Safety Review Parameter (Unit) 
Value 
 
 
 
 
 
 
 
 
 
 
xxxxx 
xxxxxx 
xxx 
YYYY-MM-DD: HH:MM 
  
xxxxxx 
xxxxxx 
 
 
 
 
 
 
  
 
 
 
 
xxxxx 
xxxxxx 
xxx 
YYYY-MM-DD: HH:MM 
  
xxxxxx 
xxxxxx 
 
 
xxxxx 
xxxxxx 
xxx 
YYYY-MM-DD: HH:MM 
  
xxxxxx 
xxxxxx 
 
 
 
 
 
 
  
 
 
 
 
 
 
 
 
  
 
 
 
 
xxxxx 
xxxxxx 
xxx 
YYYY-MM-DD: HH:MM 
  
xxxxxx 
xxxxxx 
 
 
 
 
 
 
  
 
 
 
 
xxxxx 
xxxxxx 
xxx 
YYYY-MM-DD: HH:MM 
  
xxxxxx 
xxxxxx 
 
 
 
 
 
 
  
 
 
 
 
 
 
 
 
  
 
 
 
 
 
 
 
 
  
 
 
 
 
 
 
 
 
  
 
 
 
 
 
 
 
 
  
 
 
 
 
 
 
 
 
  
 
 
 
 
 
 
 
 
  
 
 
 
 
 
 
 
 
  
 
 
 
 
  
 
 
 
 
 
 
 
 
 
 
 
 
Date: VERSION – YYYY-MM-DD 
Data Source: XXXX 
Program Source:  XXXXX.sas 
 
 


 
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CoLucid Pharmaceuticals, Inc. 
Algorithme Pharma 
Project #  COL MIG-113/CUD-P4-001 
     Page 1 of x 
Table 14.3.6.3 
Summary of ECG Assessments 
(Safety Population) 
 
 
 
 
 
 
 
 
 
 
Parameter (unit) 
 
Visit 
Timepoint 
 
Statistic 
Healthy Renal 
Function 
(N=XX) 
Severe Renal 
Function 
(N=XX) 
Etc. 
(N=XX) 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
ECG Assessment Test 1 
 
 
 
 
 
 
 
 
Screening 
 
Value 
N 
 
 
xx 
 
 
 
 
Mean (SD) 
 
 
xx (xx.x) 
 
 
 
 
Median 
 
 
xx.x 
 
 
 
 
Min, Max 
 
 
xx, xx 
 
Day -1 
 
Value 
 
 
 
 
 
 
 
 
N 
xx 
xx 
xx 
 
 
 
 
Mean (SD) 
xx (xx.x) 
xx (xx.x) 
xx (xx.x) 
 
 
 
 
Median 
xx.x 
xx.x 
xx.x 
 
 
 
 
Min, Max 
xx, xx 
xx, xx 
xx, xx 
 
 
 
 
 
 
 
 
 
Day 1 
Pre-dose 
Value 
 
 
 
 
 
 
 
 
N 
xx 
xx 
xx 
 
 
 
 
Mean (SD) 
xx (xx.x) 
xx (xx.x) 
xx (xx.x) 
 
 
 
 
Median 
xx.x 
xx.x 
xx.x 
 
 
 
 
Min, Max 
xx, xx 
xx, xx 
xx, xx 
 
 
 
 
 
 
 
 
Etc. 
Etc. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
PROGRAMMING NOTE:  All visits outlined in Appendix A will be included. Please add Moderate and Mild Renal Function Groups to 
the table if enrolled 
  
 
  
 
 
 
 
 
 
Date: VERSION – YYYY-MM-DD 
Data Source: XXXX 
Program Source:  XXXXX.sas 
 
 
 
 


 
Research Protocol No CUD-P4-001 | Sponsor Project No COL MIG-113| Version FINAL 4.0| 2018/02/15 
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APPENDIX D 
PHARMACOKINETIC OUTPUTS SHELLS  
Measured Human Plasma Concentrations of Lasmiditan, Normal Renal Function, CUD-P4-001 

Time 
(h)  
0.00 
0.25 
0.50 
1.00 
… 
… 
… 
… 
… 
36.00 
Renal Function 
Subject 
Concentration 
(ng/mL)  
Normal 
101 
 
 
 
 
 
 
 
 
 
 
… 
 
 
 
 
 
 
 
 
 
 
… 
 
 
 
 
 
 
 
 
 
 
… 
 
 
 
 
 
 
 
 
 
 
… 
 
 
 
 
 
 
 
 
 
 
… 
 
 
 
 
 
 
 
 
 
 
… 
 
 
 
 
 
 
 
 
 
 
108 
 
 
 
 
 
 
 
 
 
 
N 
 
 
 
 
 
 
 
 
 
 
Mean 
 
 
 
 
 
 
 
 
 
 
SD  
 
 
 
 
 
 
 
 
 
 
 
Min  
 
 
 
 
 
 
 
 
 
 
Median 
 
 
 
 
 
 
 
 
 
 
Max 
 
 
 
 
 
 
 
 
 
 
CV% 
 
 
 
 
 
 
 
 
 
 
Geometric Mean 
 
 
 
 
 
 
 
 
 
 
Geometric CV% 
 
 
 
 
 
 
 
 
 
 
BLQ : Below Limit of Quantitation 
NC: Not Calculated 
 
Similar tables will be presented for all renal groups, for urine concentrations and for all analytes. 


 
Research Protocol No CUD-P4-001 | Sponsor Project No COL MIG-113| Version FINAL 4.0| 2018/02/15 
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Cumulative Area Under the Curve of Lasmiditan, Normal Renal Function, CUD-P4-001 

Time 
(h)  
0.00 
0.25 
0.50 
1.00 
… 
… 
… 
… 
… 
36.00 
Renal Function 
Subject 
Cumulative AUC 
(ng*h/mL)  
Normal 
101 
 
 
 
 
 
 
 
 
 
 
… 
 
 
 
 
 
 
 
 
 
 
… 
 
 
 
 
 
 
 
 
 
 
… 
 
 
 
 
 
 
 
 
 
 
… 
 
 
 
 
 
 
 
 
 
 
… 
 
 
 
 
 
 
 
 
 
 
… 
 
 
 
 
 
 
 
 
 
 
108 
 
 
 
 
 
 
 
 
 
 
N 
 
 
 
 
 
 
 
 
 
 
Mean 
 
 
 
 
 
 
 
 
 
 
SD  
 
 
 
 
 
 
 
 
 
 
Min  
 
 
 
 
 
 
 
 
 
 
Median 
 
 
 
 
 
 
 
 
 
 
Max 
 
 
 
 
 
 
 
 
 
 
 
CV% 
 
 
 
 
 
 
 
 
 
 
Geometric Mean 
 
 
 
 
 
 
 
 
 
 
Geometric CV% 
 
 
 
 
 
 
 
 
 
 
NC: Not Calculated 
 
Similar tables will be presented for all renal groups, for urine data by intervals and for all analytes. 
 


 
Research Protocol No CUD-P4-001 | Sponsor Project No COL MIG-113| Version FINAL 4.0| 2018/02/15 
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Pharmacokinetic Parameters of Lasmiditan, Normal Renal Function, CUD-P4-001 
Renal Function 
Subject 
Cmax 
(ng/mL)  
Tmax 
(h)  
AUC(0-tlast) 
(ng*h/mL)  
AUC(0-∞) 
(ng*h/mL)  
%AUC(0-tlast/∞) 
(%) 
T1/2 
(h) 
CL/F 
(L/h)  
VZ/F 
(L)  
Normal 
101 
 
 
 
 
 
 
 
 
… 
 
 
 
 
 
 
 
 
… 
 
 
 
 
 
 
 
 
… 
 
 
 
 
 
 
 
 
… 
 
 
 
 
 
 
 
 
… 
 
 
 
 
 
 
 
 
… 
 
 
 
 
 
 
 
 
108 
 
 
 
 
 
 
 
 
N 
 
 
 
 
 
 
 
 
Mean 
 
NC 
 
 
 
NC 
 
 
SD  
 
NC 
 
 
 
NC 
 
 
Min  
 
 
 
 
 
 
 
 
Median 
 
 
 
 
 
 
 
 
Max 
 
 
 
 
 
 
 
 
CV% 
 
NC 
 
 
 
NC 
 
 
 
Geometric Mean 
 
NC 
 
 
 
 
 
 
Geometric CV% 
 
NC 
 
 
 
 
 
 
Similar tables will be presented for all renal groups, for urine parameters and for all analytes. 
 
 


 
Research Protocol No CUD-P4-001 | Sponsor Project No COL MIG-113| Version FINAL 4.0| 2018/02/15 
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Elimination Parameters of Lasmiditan, Normal Renal Function, CUD-P4-001 
Renal Function 
Subject 
TLIN 
(h)  
TLQC 
(h)  
Number of Points 
R2 
λz 
(1/h)  
Normal 
101 
 
 
 
 
 
… 
 
 
 
 
 
… 
 
 
 
 
 
… 
 
 
 
 
 
… 
 
 
 
 
 
… 
 
 
 
 
 
… 
 
 
 
 
 
108 
 
 
 
 
 
N 
 
 
 
 
 
Mean 
 
 
 
 
 
SD  
 
 
 
 
 
Min  
 
 
 
 
 
 
Median 
 
 
 
 
 
Max 
 
 
 
 
 
CV% 
 
 
 
 
 
Geometric Mean 
 
 
 
 
 
Geometric CV% 
 
 
 
 
 
A similar table will be presented for all renal groups and for all analytes. 


 
Research Protocol No CUD-P4-001 | Sponsor Project No COL MIG-113| Version FINAL 4.0| 2018/02/15 
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Actual Sampling Time of Lasmiditan, Normal Renal Function, CUD-P4-001 

Time 
(h)  
0.00 
0.25 
0.50 
1.00 
… 
… 
… 
… 
… 
… 
… 
… 
… 
36.00 
Renal Function 
Subject 
Actual Time 
(h)  
Normal 
101 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
… 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
… 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
… 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
… 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
… 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
… 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
108 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
N 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Mean 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
SD  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Min  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Median 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Max 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
CV% 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Geometric Mean 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Geometric CV% 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
NC: Not Calculated 
A similar table will be presented for all renal groups and for all analytes. 
 
 


 
Research Protocol No CUD-P4-001 | Sponsor Project No COL MIG-113| Version FINAL 4.0| 2018/02/15 
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Pairwise Comparisons of Lasmiditan, CUD-P4-001 
Parameters 
Geometric LSmeansa 
Comparison 
Adjusted p-
value 
Ratio 
(%) 
90% Confidence Limits (%) 
Group 
 
Lower  
Upper 
Cmax 
Mild (n=x) 
 
Mild vs Normal 
 
 
 
 
Moderate (n=x) 
 
Moderate vs Normal 
 
 
 
 
Severe (n=x) 
 
Severe vs Normal 
 
 
 
 
Normal (n=x) 
 
Mild vs Moderate 
 
 
 
 
NA 
NA 
Mild vs Severe 
 
 
 
 
NA 
NA 
Moderate vs Severe 
 
 
 
 
AUC(0-tlast) 
Mild (n=x) 
 
Mild vs Normal 
 
 
 
 
Moderate (n=x) 
 
Moderate vs Normal 
 
 
 
 
Severe (n=x) 
 
Severe vs Normal 
 
 
 
 
Normal (n=x) 
 
Mild vs Moderate 
 
 
 
 
NA 
NA 
Mild vs Severe 
 
 
 
 
NA 
NA 
Moderate vs Severe 
 
 
 
 
AUC(0-∞) 
Mild (n=x) 
 
Mild vs Normal 
 
 
 
 
Moderate (n=x) 
 
Moderate vs Normal 
 
 
 
 
Severe (n=x) 
 
Severe vs Normal 
 
 
 
 
Normal (n=x) 
 
Mild vs Moderate 
 
 
 
 
NA 
NA 
Mild vs Severe 
 
 
 
 
NA 
NA 
Moderate vs Severe 
 
 
 
 
a Cmax is presented in ng/mL, AUC(0-tlast) and AUC(0-∞) are presented in ng*h/mL 


 
Research Protocol No CUD-P4-001 | Sponsor Project No COL MIG-113| Version FINAL 4.0| 2018/02/15 
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PHARMACOKINETIC FIGURES SHELLS  
Figure 1: Linear Profile of the Mean of Lasmiditan in Plasma 
 
 
The figure does not reflect the actual data of the study 
Figures will be presented for all analytes. 
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Research Protocol No CUD-P4-001 | Sponsor Project No COL MIG-113| Version FINAL 4.0| 2018/02/15 
54 
Figure 2: Logarithmic Profile of the Mean of Lasmiditan in Plasma 
 
 
The figure does not reflect the actual data of the study. 
Figures will be presented for all analytes. 
 
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Research Protocol No CUD-P4-001 | Sponsor Project No COL MIG-113| Version FINAL 4.0| 2018/02/15 
55 
 
 


 
Research Protocol No CUD-P4-001 | Sponsor Project No COL MIG-113| Version FINAL 4.0| 2018/02/15 
56 
Figures 2+1 to (2+1)+N: Individual Linear Profile of Lasmiditan in Plasma 
 
The figure does not reflect the actual data of the study 
Figures will be presented for all analytes. 
 
 
 
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Research Protocol No CUD-P4-001 | Sponsor Project No COL MIG-113| Version FINAL 4.0| 2018/02/15 
57 
Figure X: Individual Logarithmic Profile of Lasmiditan in Plasma 
 
 The figure does not reflect the actual data of the study. 
 
Figures will be presented for all analytes. 
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Research Protocol No CUD-P4-001 | Sponsor Project No COL MIG-113| Version FINAL 4.0| 2018/02/15 
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Figure 1: Linear Profile of the Mean of Lasmiditan in Urine 
 
 
The figure does not reflect the actual data of the study. 
Figures will be presented for all analytes. 
 
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Research Protocol No CUD-P4-001 | Sponsor Project No COL MIG-113| Version FINAL 4.0| 2018/02/15 
59 
 
Figure 2: Logarithmic Profile of the Mean of Lasmiditan in Urine 
 
 
The figure does not reflect the actual data of the study. 
Figures will be presented for all analytes. 
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Research Protocol No CUD-P4-001 | Sponsor Project No COL MIG-113| Version FINAL 4.0| 2018/02/15 
60 
 
Figures 2+1 to (2+1)+N: Individual Linear Profile of the Mean of Lasmiditan in Urine 
 
The figure does not reflect the actual data of the study 
Figures will be presented for all analytes. 
 
 
 
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Research Protocol No CUD-P4-001 | Sponsor Project No COL MIG-113| Version FINAL 4.0| 2018/02/15 
61 
Figure N: Individual Logarithmic Profile of the Mean of Lasmiditan in Urine 
 
 The figure does not reflect the actual data of the study 
Figures will be presented for all analytes. 

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Research Protocol No CUD-P4-001 | Sponsor Project No COL MIG-113| Version FINAL 4.0| 2018/02/15 
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Figure N: Individual Elimination Profiles 
 
The figure does not reflect the actual data of the study. 


 
Research Protocol No CUD-P4-001 | Sponsor Project No COL MIG-113| Version FINAL 4.0| 2018/02/15 
63 
In Text Figure: 
Figure 1: Linear Regression of ln-Transformed Cmax vs eGFR (Lasmiditan) 
 
The figure does not reflect the actual data of the study. Same graph will be presented for AUC(0-tlast) ,AUC(0-∞)  and CL/F. 
 
 
 


 
Research Protocol No CUD-P4-001 | Sponsor Project No COL MIG-113| Version FINAL 4.0| 2018/02/15 
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APPENDIX E 
LISTING SHELLS  
 
 


 
Research Protocol No CUD-P4-001 | Sponsor Project No COL MIG-113| Version FINAL 4.0| 2018/02/15 
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CoLucid Pharmaceuticals, Inc. 
Algorithme Pharma 
Project #  COL MIG-113/CUD-P4-001 
     Page 1 of x 
 
Listing 16.2.1 
Listing of Study Disposition 
 
 
Subject ID 
Date of Completion or 
Discontinuation 
Subject Status 
Specify 
AE # 
Date of Death 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
  
 
 
 
 
 
 
Date: VERSION – YYYY-MM-DD 
Data Source: XXXX 
Program Source:  XXXXX.sas 
 
 
 


 
Research Protocol No CUD-P4-001 | Sponsor Project No COL MIG-113| Version FINAL 4.0| 2018/02/15 
66 
CoLucid Pharmaceuticals, Inc. 
Algorithme Pharma 
Project #  COL MIG-113/CUD-P4-001 
     Page 1 of x 
 
Listing 16.2.2.1 
Listing of PK Blood Sampling Time Deviations 
 
 
Group 
 Elapsed 
Time (h) 
 Subject ID 
Scheduled 
Date/Time 
Actual 
Date/Time 
Deviation (min) 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
  
 
 
 
 
 
 
 
 
 
Date: VERSION – YYYY-MM-DD 
Data Source: XXXX 
Program Source:  XXXXX.sas 
 
 
 
 


 
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67 
CoLucid Pharmaceuticals, Inc. 
Algorithme Pharma 
Project #  COL MIG-113/CUD-P4-001 
     Page 1 of x 
 
Listing 16.2.2.2 
Listing of Protocol Deviations 
 
 
Group 
Subject ID 
Protocol Deviation Term      Start Date 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
  
 
 
 
 
 
 
 
 
 
Date: VERSION – YYYY-MM-DD 
Data Source: XXXX 
Program Source:  XXXXX.sas 
 
 


 
Research Protocol No CUD-P4-001 | Sponsor Project No COL MIG-113| Version FINAL 4.0| 2018/02/15 
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CoLucid Pharmaceuticals, Inc. 
Algorithme Pharma 
Project #  COL MIG-113/CUD-P4-001 
     Page 1 of x 
Listing 16.2.3 
Listing of Analysis Populations 
 
Subject ID 
Safety 
Population PK Population  Reason if Excluded from one Population 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
  
 
 
 
 
 
 
Date: VERSION – YYYY-MM-DD 
Data Source: XXXX 
Program Source:  XXXXX.sas 
 
 
 


 
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Listing 16.2.4.1 
Listing of Demographic Characteristics 
 
 
Subject ID 
Age Date of Birth Gender 
Ethnicity Race 
Other Race  
 
Weight (kg)  
Height (cm) 
BMI (kg/m2) 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
  
 
 
 
 
 
 
 
 
 
 
 
 
 
Date: VERSION – YYYY-MM-DD 
Data Source: XXXX 
Program Source:  XXXXX.sas 
 
 
 


 
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Listing 16.2.4.2 
Listing of Screen Failures 
 
 
Subject ID 
Date 
 
Specify Primary Reason 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
  
 
 
 
 
 
Date: VERSION – YYYY-MM-DD 
Data Source: XXXX 
Program Source:  XXXXX.sas 
 
 


 
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Listing 16.2.5 
Listing of Investigational Product Administration 
 
 
 
 
Subject ID 
Visit 
Start 
Date/Time 
 
Treatment 
Dose 
Administered (mg) 
Route 
 
If Any Dosing Issues, 
Specify 
  
 
 
 
 
 
 
 
 
 
  
 
 
 
 
 
 
 
  
  
 
 
 
 
 
 
 
 
 
  
 
 
 
 
 
 
 
 
 
  
 
 
 
 
 
 
 
 
 
  
 
 
 
 
 
 
 
 
 
  
 
 
 
 
 
 
 
 
 
  
 
 
 
 
 
 
 
 
 
  
 
 
 
 
 
 
 
 
 
  
 
 
 
 
 
 
 
 
 
  
 
 
 
 
 
 
 
 
 
  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
  
  
 
 
 
 
 
 
 
 
  
 
 
Date: VERSION – YYYY-MM-DD 
Data Source: XXXX 
Program Source:  XXXXX.sas 
 
 
 


 
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Listing 16.2.7  
Listing of Adverse Events 
 
 
Subject ID 
Visit/ 
Group/ 
AE # 
SOC 
  MedDRA 
Preferred Term 
    Description 
of AE 
Onset Date  
Time 
(Time since 
Last Dose) 
Resolution 
Date Time 
(Duration) 
I: Maximal 
Severity 
R: Causality 
Assessment 
O: Outcome 
S: Serious AE 
D: AE Leading To 
Discontinuation 
Action Taken With 
Study Treatment / 
Other Action(s) Taken 
/ Concomitant Given 
 
 
 
  
  
 
 
 
 
 
xxx 
xxxxx 
xxxxx 
xxxxxxxxxxxx 
  xxxxxxxxxxxx 
     
xxxxxxxxxxxx 
YYYY-MM-DD/ 
HH:MM 
(DD:HH:MM) 
YYYY-MM-DD/ 
HH:MM 
(DD:HH:MM) 
xxxxxx 
xxxxx 
xxxxxx 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
  
 
  
 
 
 
 
 
 
 
 
 
 


 
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Listing 16.2.8.1 
Listing of Blood Chemistry 
 
 
Subject ID 
Lab Test Name (Units) 
Reference Range 
Visit 
Date / Time   Value 
 
Out-of-Range 
Flag 
Assessment 
[1] 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
  
 
 
 
 
 
 
 
 
 
 
[1] NCS: Not Clinically Significant   /   CS: Clinically Significant   /   RPT: Repeated   /  TBC: To Be Controlled. 
 
Date: VERSION – YYYY-MM-DD 
Data Source: XXXX 
Program Source:  XXXXX.sas 
 
 
 


 
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Similar listing(s): 
 
L16.2.8.2 
 
Listing of Hematology 
L16.2.8.3 
 
Listing of Urinalysis 
L16.2.8.4 
 
Listing of Urine Drug Screen 
L16.2.8.5 
 
Listing of Pregnancy Test 
L16.2.8.5 
 
Listing of Serology  
 
  
 
 
 
 


 
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Listing 16.2.9.1 
Listing of Alcohol Habits 
 
 
Subject ID 
Intake Status 
Quantity 
Frequency 
Start Date 
End Date 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
  
 
 
 
 
 
 
 
 
Date: VERSION – YYYY-MM-DD 
Data Source: XXXX 
Program Source:  XXXXX.sas 
 
 
 


 
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Listing 16.2.9.2 
Listing of Smoking Habits 
 
 
Subject ID 
Intake Status 
Quantity 
Frequency 
Start Date 
End Date 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
  
 
 
 
 
 
 
 
 
Date: VERSION – YYYY-MM-DD 
Data Source: XXXX 
Program Source:  XXXXX.sas 
 
 
 
 
 


 
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Listing 16.2.9.3 
Listing of Prior Medication  
 
 
Subject ID 
#CM  
Related to 
AE#/MH# 
ATC / 
PT / 
Medication 
Name 
Indication 
Dose 
(unit) 
Frequency Formulation 
Total 
Daily 
Dose 
Route 
Start 
Date/ 
Time 
End  
Date/ 
Time 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Date: VERSION – YYYY-MM-DD 
Data Source: XXXX 
Program Source:  XXXXX.sas 
 
Similar Listing:  
 
Listing 16.2.9.4 Listing of Concomitant Medication 
 
 


 
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Listing 16.2.9.5 
Listing of Physical Examination 
 
 
Subject ID 
Visit  
 Date / Time 
 Body System Examined 
Result  (Abnormal Findings) 
 
 
 
 
 
 
 
 
 
  
 
 
 
 
 
  
 
 
 
 
 
  
 
 
 
 
 
  
 
 
 
 
 
  
 
 
 
 
 
  
 
 
 
 
 
  
 
 
 
 
 
  
 
 
 
 
 
  
 
 
 
 
 
  
 
 
 
 
 
  
 
 
 
  
 
 
 
 
 
 
 
 
Date: VERSION – YYYY-MM-DD 
Data Source: XXXX 
Program Source:  XXXXX.sas 
 
 
 


 
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Listing 16.2.9.6 
Listing of Vital Signs  
 
 
Subject ID 
Visit 
 
 
Elapsed Time 
 
Position 
Date / Time 
 
Assessment 
(Units)  
Value  
Safety 
Review  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
  
 
 
 
 
 
 
 
 
 
 
 
Date: VERSION – YYYY-MM-DD 
Data Source: XXXX 
Program Source:  XXXXX.sas 
 
 
 


 
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     Page 1 of x 
 
Listing 16.2.9.7 
Listing of ECG Assessments 
 
 
Subject ID 
Visit 
Time Point 
 Date / Time 
Position 
Safety Review Parameter (Unit) Value 
 
 
 
 
 
 
 
 
 
xxxxx 
xxxxxx 
 
 YYYY-MM-DD: HH:MM 
xxxxxx 
xxxxxx 
 
 
 
 
 
  
 
 
 
 
 
 
 
 YYYY-MM-DD: HH:MM 
xxxxxx 
xxxxxx 
 
 
 
 
 
 YYYY-MM-DD: HH:MM 
xxxxxx 
xxxxxx 
 
 
 
 
 
  
 
 
 
 
 
 
 
  
 
 
 
 
xxxxx 
xxxxxx 
 
 YYYY-MM-DD: HH:MM 
xxxxxx 
xxxxxx 
 
 
 
 
 
  
 
 
 
 
xxxxx 
xxxxxx 
 
 YYYY-MM-DD: HH:MM 
xxxxxx 
xxxxxx 
 
 
 
 
 
  
 
 
 
 
 
 
 
  
 
 
 
 
 
 
 
  
 
 
 
 
 
 
 
  
 
 
 
 
 
 
 
  
 
 
 
 
 
 
 
  
 
 
 
 
 
 
 
  
 
 
 
 
 
 
 
  
 
 
 
 
  
 
 
 
 
 
 
 
 
 
 
 
Date: VERSION – YYYY-MM-DD 
Data Source: XXXX 
Program Source:  XXXXX.sas 
 
 
 
 
 
 


 
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     Page 1 of x 
 
Listing 16.2.9.8 
Listing of Inclusion/Exclusion Criteria Summary 
 
 
Subject ID 
Has the participant met all 
screening eligibility criteria? 
Inclusion/Exclusion 
Failed Criterion Number 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
  
 
 
 
 
 
Date: VERSION – YYYY-MM-DD 
Data Source: XXXX 
Program Source:  XXXXX.sas 
 
 
 


 
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Listing 16.2.9.9 
Listing of Medical History 
 
 
Subject ID 
MH # System Organ Class 
MedDRA Preferred Term 
Description of Medical 
History 
Start Date 
End Date 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
          
 
Date: VERSION – YYYY-MM-DD 
Data Source: XXXX 
Program Source:  XXXXX.sas 
 
 


 
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CONFIDENTIAL 
Project #  COL MIG-113/CUD-P4-001 
     Page 1 of x 
 
Listing 16.2.9.10 
Listing of Columbia-Suicide Severity Rating Scale (C-SSRS) 
 
 
Subject ID 
Visit 
Category 
Question 
Answer 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Date: VERSION – YYYY-MM-DD 
Data Source: XXXX 
Program Source:  XXXXX.sas 
 
 


 
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contact@altasciences.com 
altasciences.com 
 
 
10103 Metcalf Ave. 
Overland Park, KS 66212
United States
913 696-1601
vinceandassociates.com 
575 Armand-Frappier Blvd.
Laval, Quebec 
Canada H7V 4B3
450 973-6077
algopharm.com 
4837 Amber Valley Parkway
Fargo, ND 58104
United States
701 551-3737 
algopharm.com 


, A1tasc1ences 
CLINICAL RESEARCH 
SUPPLEMENTARY INFORMATION REC 
ALGORITHME PHARMA 
SPONSOR PROJECT ND: COL MIG-113 
ALTASCIENCES PROJECT NO: CUD-P4-001 
Date 2018104/05 
CATEGORY 
Requested by: SRA Team, Algorithme Pharma 
Documents: 
.. Protocol -----------·---···] __ ( ) __ J SOP N°: ___________ JJ.J..l Regulatory documents---·--·--···--···-· i J J __ 
Other ( ,J) ), specify : SAP 
DESCRIPTION 
Description: 
This serves to clarify an error of date in SAP version Final 4.0 dated 2018/02/15. On the cover page(1 51 page) of 
SAP, the date reads 2017/02/15. In fact it should be 2018/02/15, as the footnote indicates. 
The clarifications described herein are judged to have no impact on the conduct of the study or on subjects' safety. 
Completed By: 
Date: 
Date: 
Page 1 of 1 
PPD


 
 
 
 
STATISTICAL ANALYSIS PLAN 
 
 
For: 
CoLucid Pharmaceuticals, Inc. 
 
SPONSOR PROTOCOL No. COL MIG-113 
 
A Phase I, Multicenter, Open-Label, Parallel-Group Adaptive 
Pharmacokinetic Single Dose Study of Oral Lasmiditan in Subjects 
with Normal and Impaired Renal Function 
 
Algorithme Project No. CUD-P4-001 
 
Prepared by:  
Algorithme Pharma 
575 Armand-Frappier 
Laval, Quebec 
Canada, H7V 4B3 
 
 
Version: Final 3.2 
Date: 2017/10/25 
 
 


...., Altasciences 
' 
CLINICAl RESEARCN 
'-.. 
AI.GORITHME PHARMA. 
STATISTICAL ANALYSIS PLAN APPROVAL 
We have carefully read this Statistical Analysis Plan and agree It contains the necessary information required to handle the 
statistical analysis of study data. 
On beha~ of the Sponsor: 
Date 
Date 
Research Protocol No CUD-P4-001 1 Sponsor Project No COL MlG-1131 Version FINAL 3.212017/10/25 
2 
PPD
PPD
PPD
PPD


 
Research Protocol No CUD-P4-001 | Sponsor Project No COL MIG-113| Version FINAL 3.2 | 2017/10/25 
3 
VERSION CONTROL 
 
Version 
Number 
Version Date Author 
Description of Significant Changes 
from  
Previous Approved Version 
DRAFT 0.1 
2017/04/28 
Sarah Vahey / Josée 
Michaud 
Not Applicable – First Version 
DRAFT 0.2 
2017/05/15 
Sarah Vahey / Josée 
Michaud 
Updated according to client comments 
DRAFT 0.3 
2017/05/25 
Sarah Vahey / Josée 
Michaud 
Updated according to client comments 
FINAL 1.0 
2017/06/07 
Sarah Vahey 
Updated version to Final 
FINAL 2.0 
2017/09/05 
Nolwenn Rondet/Jade 
Huguet  
Updated 
according 
FDA 
recommendations from final 1.0 to Final 
2.0  
FINAL 3.0 
2017/09/22 
Nolwenn 
Rondet/Josée  
Michaud  
Updated 
according 
FDA 
recommendations from final 1.0 to Final 
2.0  
FINAL 3.1 
2017/09/22 
Nolwenn Rondet  
Updated 
according 
FDA 
recommendations from final 1.0 to Final 
2.0 and client comments 
FINAL 3.2 
2017/10/25 
Nolwenn 
Rondet 
/ 
Josée Michaud 
Updated according client comments 
FINAL 3.3 
2017/10/28 
Katia 
Charland 
/ 
Josée Michaud 
Final Version  
 
 


 
Research Protocol No CUD-P4-001 | Sponsor Project No COL MIG-113| Version FINAL 3.2 | 2017/10/25 
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CONTENTS 
STATISTICAL ANALYSIS PLAN APPROVAL 
2 
VERSION CONTROL 
3 
ABBREVIATIONS 
6 
1. 
INTRODUCTION 
7 
2. 
STUDY OBJECTIVES 
8 
Primary Objectives 
8 
Secondary Objective 
8 
3. 
STUDY DESIGN 
9 
General Description 
9 
Study procedures 
9 
Randomization and Unblinding Procedure 
9 
4. 
STUDY ENDPOINTS 
10 
Pharmacokinetic Endpoints 
10 
Safety Endpoints 
10 
Sample Size Determination 
10 
5. 
ANALYSIS POPULATIONS 
11 
6. 
STATISTICAL METHODOLOGY 
12 
Analysis Time Points 
12 
Methods for Handling Missing Data 
12 
7. 
STUDY SUBJECTS 
13 
Disposition 
13 
Protocol Deviations 
13 
8. 
DEMOGRAPHIC AND OTHER BASELINE CHARACTERISTICS 
14 
Demographic and Background Characteristics 
14 
Lifestyle 
14 
Medical/Social history 
14 
Prior Medication 
14 
9. 
PHARMACOKINETICS AND STATISTICS 
15 
Pharmacokinetic Analysis 
15 
Statistical Analysis 
15 
10. 
SAFETY 
17 
Adverse Events 
17 
Concomitant Medications 
17 
Extent of Exposure 
17 
Clinical Laboratory Evaluations 
18 
Vital Signs 
18 
Electrocardiogram 
18 
Physical Examination Findings 
18 
Columbia-Suicide Severity Rating Scale (C-SSRS) 
18 
11. 
INTERIM ANALYSES AND DATA SAFETY MONITORING 
19 
12. 
CHANGES TO PROTOCOL-SPECIFIED ANALYSES 
20 
13. 
GENERAL INFORMATION RELATED TO DATA PRESENTATIONS 
21 


 
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PLANNED END-OF-TEXT TABLES 
23 
PLANNED LISTINGS 
25 
APPENDIX A 
28 
STUDY SCHEDULES 
28 
APPENDIX B 
30 
Pharmacokinetic Parameters 
30 
APPENDIX C 
31 
TABLE SHELLS 
31 
APPENDIX D 
47 
PHARMACOKINETIC OUTPUTS SHELLS 
47 
PHARMACOKINETIC FIGURES SHELLS 
53 
APPENDIX E 
64 
LISTING SHELLS 
64 
 
 
 


 
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ABBREVIATIONS 
AE 
Adverse Event 
ANOVA 
Analysis of Variance 
ATC 
AUC 
Anatomical/Therapeutic/Chemical 
Area Under Curve 
BMI 
Body Mass Index 
CI 
Confidence Interval 
CLCR 
Creatinine Clearance 
CNS 
Central Nervous System 
CRF 
Case Report Form 
CS 
Clinically Significant 
C-SSRS 
Columbia-Suicide Severity Rating Scale 
CSR 
Clinical Study Report 
eGRF 
Estimated Glomerular Filtration Rate 
EOS 
End of Study 
ICF 
Informed Consent Form 
MedDRA 
Medical Dictionary for Regulatory Activities 
NCS 
Not Clinically Significant 
PK 
Pharmacokinetic(s) 
SAE 
Serious Adverse Event 
SAP 
Statistical Analysis Plan 
SD 
Standard Deviation 
SE 
Standard Error 
SOC 
System Organ Class 
TEAE 
Treatment-Emergent Adverse Event 
TFLs 
Tables, Figures, and Listings 
WHO-DDE 
WHO Drug Dictionary Enhanced 
 
 
 


 
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1. 
INTRODUCTION 
 
This statistical analysis plan (SAP) provides a detailed description of the statistical methods and procedures to be implemented 
for the analyses of data from Protocol No. COL MIG-113. The analyses described in the SAP are based upon the final protocol 
(Amendment 1) dated 2017/01/06.   
 
 


 
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2. 
STUDY OBJECTIVES 
Primary Objectives 
The primary objective of this study is to evaluate the pharmacokinetic profile of lasmiditan following a single oral 200 mg dose in 
subjects with impaired renal function relative to matched, healthy controls with normal renal function. 
Secondary Objective 
The secondary objective of this study is to assess the safety and tolerability of a single oral 200 mg dose of lasmiditan in subjects 
with normal and impaired renal function.  
 


 
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3. 
STUDY DESIGN  
General Description 
This is a multi-center, open-label, non-randomized, parallel-group, adaptive, single dose study. 
This study will enroll up to 32 subjects using an adaptive design that can include up to 3 groups of 8 subjects with different 
degrees of renal impairment and one group of 8 control subjects with normal renal function. 
First, approximately 16 subjects will be enrolled with severe renal impairment and matched subjects with normal renal function. 
There will be 8 subjects in each of the following groups based on renal function at screening: 

Group 1: Healthy subjects with normal renal function (eGFR ≥ 90 mL/min/1.73m2) 

Group 2: Severe renal impairment subjects (eGFR < 30 mL/min/1.73m2) 
Based on safety and PK results from subjects with severe renal impairment (Group 2), Group 3 (Moderate Renal Impairment) 
and Group 4 (Mild Renal Impairment) will be enrolled if substantial change in the exposure of lasmiditan is observed in subjects 
with severe renal impairment. There will be 8 subjects in each of the following groups based on renal function at screening: 

Group 3: Moderate renal impairment subjects (eGFR 30-59 mL/min/1.73m2) 

Group 4: Mild renal impairment subjects (eGFR 60-89 mL/min/1.73m2) 
All subjects will participate in one treatment period and will receive a single dose of lasmiditan in the fasting state.  
The total duration of each subject’s participation in the study will be 3 days (Day –1 through the last PK sample taken on Day 2), 
not including the screening and follow-up phone call. The total duration of the study is expected to be 35 days, including the 
screening. 
The following treatment regimen will be used: 

Experimental treatment: Lasmiditan 200 mg 
Study procedures 
For complete details on the study assessments to be performed for the study, refer to Appendix A.  
Randomization and Unblinding Procedure 
No randomization will be performed for this study. Instead subjects will be categorized into either the control group of healthy 
volunteers with normal renal function, or into one of the three groups of subjects with varying degrees of renal impairment. 
 
Subjects who withdraw from the study may be replaced. Replacement subjects will not be enrolled for subjects who discontinue 
the study due to treatment-related toxicity.  
 
No unblinding procedure is required, as this in an open-label study. 
 
  
 


 
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4. 
STUDY ENDPOINTS 
Pharmacokinetic Endpoints 
The following plasma and urine PK parameters of lasmiditan will be calculated: Cmax, Tmax, AUC(0-tlast), AUC(0-∞), %AUC(tlast-), 
λz, T1/2, CL/F, Vz/F, Ae(0-t), fe, CLr. 
For all the metabolites [(S)-M8, (S,R)-M18, M7 and (S,S)-M18], the following PK parameters Cmax, Tmax, AUC(0-tlast), AUC(0-∞), 
%AUC(tlast-), λz, Thalf, Ae(0-t), CLr,met and individual metabolic ratio (metabolite AUC/parent AUC) will be calculated, if 
quantifiable. 
Safety Endpoints 
Safety endpoints include: 

Adverse Events   

Clinical Laboratory Tests (hematology, chemistry, urinalysis) 

Vital Signs 

Physical examination  

Concomitant medication 

ECGs 

C-SSRS 
The details of the safety endpoints’ assessment are presented in Section 10. 
Sample Size Determination 
There is no formal statistical sample size calculation for this study. A sample size of 32; including 8 subjects/patients for each 
renal function group (8 subjects with normal renal function, 8 patients with mildly impaired renal function, 8 patients with 
moderately impaired renal function, and 8 with severely impaired renal function) was chosen because it is considered typical for 
studies evaluating the effect of renal function on the pharmacokinetics of a drug. 
 


 
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5. 
ANALYSIS POPULATIONS 
 
Safety Population: 
All subjects who received a dose of study medication will be included in the safety population. This population will be used for all 
demography and safety analyses.  
Pharmacokinetics (PK) Population: 
All subjects who received lasmiditan, had no major protocol deviations, and completed the period with evaluable (sufficient and 
interpretable) data will be included in the PK population. 
If some subjects do not complete the sampling schedule resulting in an inadequately characterized some PK parameters (e.g. 
AUC, VZ/F, λZ), samples of these subjects could be included in the statistical pharmacokinetic analysis for only the evaluable 
parameters. 
 


 
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6. 
STATISTICAL METHODOLOGY 
 
All analyses will be conducted using the SAS software, version 9.4, or higher. Descriptive statistics of the PK data will be 
performed by  Phoenix® WinNonlin® version 6.3 or higher, Phoenix® ConnectTM version 1.3.1 or higher). 
Adverse events and medical history will be classified using the standard MedDRA terminology version 19.1.  
Prior and concomitant medications will be coded with the WHO-DDE dictionary version March 01, 2016. 
In general, all summary tables will be presented for safety population. Summaries will be presented by renal function group.  
In general, the data listings will include all enrolled subjects up to the point of study completion or discontinuation; exceptions will 
be listings pertaining to a subset of subjects only (e.g., subjects with blood sampling time deviations) or a subset of 
records/events (e.g., abnormal laboratory values). 
Categorical variables will be summarized using the PROC FREQ procedure. Continuous variables will be summarized using the 
PROC UNIVARIATE procedure. For log-transformed endpoints, geometric mean, and coefficient of variation will also be 
presented. 
The following general comments also apply to all statistical analyses and data presentations: 

Duration variables in days will be calculated using the general formula: (end date - start date) +1. 

Individual subject listings of all data represented on the CRFs will be provided to facilitate the investigation of 
tabulated values and to allow for the clinical review of all efficacy and safety parameters. 

When assessments are repeated for a given timepoint, only the result which is closes to the dosing time will 
be included in the summary tables. 
The analyses described in this plan are considered a priori, that they have been defined prior to database lock.  Any analyses 
performed subsequent to database lock will be considered post hoc and exploratory.  Post hoc analyses will be labeled as such 
in the corresponding statistical output and identified in the CSR. 
Analysis Time Points  
Unless otherwise specified, the baseline value will be defined as the last non-missing evaluation prior to the first dose of study 
medication. 
Methods for Handling Missing Data  
No imputations of values for missing data will be performed. All data recorded on the case report form will be included in the 
listings that will accompany the clinical study report.   
 
 


 
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7. 
STUDY SUBJECTS 
Disposition 
The subject disposition will be summarized for all subjects enrolled in this study, including: 

The number of subjects enrolled; 

The number of screen failure subjects; 

The number of subjects screened; 

The number and percentage of subjects who completed the study; 

The number and percentage of subjects discontinued from the study by primary reason for discontinuation and overall; 

The number and percentage of subjects included in each of the safety and PK populations. 
The percentages will be calculated using the number of subjects randomized as denominator. 
A listing of subject’s disposition will be provided. A listing of subjects included in each of the analysis populations will also be 
provided. Screen failure subjects will also be presented in a listing. 
Protocol Deviations 
Inclusion/exclusion criteria violations will be presented in a listing. 
All deviations from the scheduled PK sampling time of 2 minutes or more for post dose samples will be taken into consideration 
for the evaluation of PK parameters. 
 
 
 


 
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8. 
DEMOGRAPHIC AND OTHER BASELINE CHARACTERISTICS 
Demographic and Background Characteristics 
Demographic data and baseline characteristics will be presented in a data listing and summarized by renal function group in a 
table. Quantitative assessments to be summarized are age, height, body weight and body mass index (BMI) at screening. 
Subject demographics include sex, age, ethnicity, race and country. Baseline characteristics include height, weight, and BMI. 
Lifestyle 
Alcohol and smoking intake history will be recorded and presented in separate listings. 
Medical/Social history  
Any medical history findings will be recorded and presented in a listing. The listing will include the coding terms (e.g., SOC and 
Preferred Term).  
Prior Medication 
Any medications taken including prescription, nonprescription, OTC (cold and antacid medications), dietary supplements, 
vitamins or herbal medications from screening to the first dose of the study drug will be recorded and presented as prior 
medications in a listing. The listing will include the coding terms (e.g., ATC and Preferred Term).   
 
 
 


 
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9. 
PHARMACOKINETICS AND STATISTICS 
Pharmacokinetic Analysis 
The PK parameters are presented in Section 4 and Appendix B. All reported sampling time deviations (see Section 7) will be 
taken into consideration for evaluation of plasma PK parameters. 
Only quantifiable concentrations will be used to calculate PK parameters. An exception to this rule is made for concentrations 
below the quantification limit (BQL), which will be set to zero when all of the following conditions are met: 

The time points occur before the first quantifiable concentration. 
All other BQL concentrations will be treated as missing sample. 
The pharmacokinetic parameters will be estimated using a non-compartmental approach with a log-linear terminal phase 
assumption. The trapezoidal rule will be used to estimate the area under the curve, and the terminal phase will be estimated by 
maximizing the coefficient of determination estimated from the log-linear regression model. These parameters (AUC(0-∞), 
%AUC(tlast-), λZ, T1/2, CL/F and Vz/F) will be estimated for individual concentration-time profiles only when the terminal log-
linear phase cannot be reliably characterized using the following criteria: 

Phoenix® WinNonlin® Best fit range selection (if adequate):  

R2 of at least 80%  
In the case where less than 3 consecutive measurable plasma concentrations of lasmiditan or its metabolites [(S)-M8, (S,R)-
M18, M7 and (S,S)-M18] is observed, the AUC parameters will not be estimated for that particular analyte. 
Additional pharmacokinetic parameters may be calculated if deemed appropriate. 
Pharmacokinetic analyses and associated descriptive statistics will be generated using Phoenix® WinNonlin® Version 6.3 (or 
higher). 
 
Statistical Analysis  
The natural logarithmic transformation of Cmax, AUC(0-tlast), AUC(0-∞), , Ae(0-t), as well as the rank-transformation of Tmax will be 
used for all statistical inference for the parent (lasmiditan).and all metabolites [(S)-M8, (S,R)-M18, M7 and (S,S)-M18].  
Statistical analyses will be generated using validated SAS® (version 9.4 or higher) using the Reg (and Mixed, if applicable) 
procedure(s). 
The statistical analysis described in this section will be done using both eGFR and Cockcroft-Gault estimate of the creatinine 
clearance. However, analysis using the eGFR will be considered as the primary analysis and the analysis using the Cockcroft-
Gault estimate of the creatinine clearance will be considered as supportive. 
Regression Analysis 
The eGFR and Cockcroft-Gault estimate of creatinine clearance at baseline will be used as separate measures of renal function 
for a regression analysis to evaluate the relationships between estimated renal function and the PK parameters.  
For each log-transformed PK parameter, a regression analysis will be performed, using a model of the form α + β*eGFR+ ε 
where the errors (ε) will be assumed to be independent and normally distributed with mean zero and variance σ2. The parameter 
β represents the correlation between the relevant PK parameter and eGFR which will be treated as a continuous variable. 
The hypothesis of the slope of trend being different from zero will be assumed if the two-sided test of the nullity of the parameter 
β is statistically significant at the 5% level. 


 
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The regression analysis will be repeated for each log-transformed PK parameter with the Cockcroft-Gault estimate of creatinine 
clearance at baseline. 
Analysis of Variance 
 An analysis of variance (ANOVA) will be performed to assess the difference in the PK parameter among the renal function 
groups. 
The renal function (normal, mild, moderate and severe) will be entered as a fixed effect in the ANOVA model. Pairwise 
comparisons of renal function groups will be generated using the Tukey-Kramer’s procedure of adjustment for multiple 
comparisons (if more than 2 renal function groups) and statistical significance will be assessed at the two-sided 5% level. The 
ratio of geometric LS means (of each renal function group being compared), with a corresponding 90% confidence interval 
(adjusted using Tukey-Kramer’s procedure if applicable), will be computed. Heterogeneity of variance among groups will be 
assumed. 
 
 


 
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10. 
SAFETY 
Adverse Events 
An AE is defined as any untoward medical occurrence in a subject administered a medicinal product and which does not 
necessarily have to have a causal relationship with this treatment. An AE can therefore be any unfavorable and unintended sign 
(for example, an abnormal laboratory finding), symptom, or disease temporally associated with the use of a medicinal product, 
whether or not considered related to this medicinal product. 
A suspected adverse reaction is any AE for which there is a reasonable possibility that the drug caused the AE. ‘Reasonable 
possibility’ means there is evidence to suggest a causal relationship between the drug and the AE. A suspected adverse reaction 
implies a lesser degree of certainty about causality than adverse reaction, which means any AE caused by a drug.  
AEs occurring after the initiation of the treatment are referred to as treatment emergent adverse events (TEAEs). 
 
As an overall summary of AEs, the following will be presented by renal function group and overall: 

Number of reported AEs;  

Number of reported TEAEs;  

Number and percentage of subjects experiencing TEAEs;  

Number and percentage of subjects experiencing a drug-related TEAE (i.e. those with a relationship classified as 
reasonable possibility) 

Number and percentage of TEAEs by relationship to study treatment (i.e. reasonable possibility, no reasonable 
possibility);  

Number and percentage of TEAEs by severity;  

Number of reported SAEs (serious adverse events);  

Number and percentage of subjects experiencing SAEs;  

Number and percentage of subjects experiencing drug-related SAEs; 

Number and percentage of TEAEs leading to withdrawal; and 

SAEs with an outcome of death.  
Frequency tables will be presented by renal function group, system organ class and preferred term that summarize all Treatment 
Emergent Adverse Events (TEAEs) and all drug-related TEAEs.  
Subject listings of all Adverse Events (AEs) including severity and relationship to study drug will be provided. AEs leading to 
withdrawal and SAEs will also be presented in separate listings. 
Concomitant Medications 
Medications taken after the first dose of study drug until after discharge from the study will be recorded. Concomitant 
medications will be presented in a listing. The medication name, active ingredient, dose, units, formulation, route, indication or 
reason taken, code, date and time taken will be presented. The listing will also include the coding terms (e.g., ATC and Preferred 
Term). 
Extent of Exposure 
Details of drug dosing (actual treatment received, actual date and time of administration, dose administered, and route of 
administration) will be listed by subject. 
 
 


 
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Clinical Laboratory Evaluations 
Planned laboratory analyses include: 

General Biochemistry: Sodium, potassium, chloride, glucose, blood urea nitrogen (BUN), creatinine, eGFR, total 
bilirubin, alkaline phosphatase, AST, ALT and albumin; 

Hematology: White cell count with differential (absolute values of neutrophil, lymphocyte, monocyte, eosinophil, and 
basophil), red cell count, hemoglobin, hemoglobin A1c, hematocrit, mean corpuscular volume (MCV), and platelets 
count; 

Urinalysis: Color, appearance, specific gravity, pH, leukocyte, protein, glucose, ketones, bilirubin, blood, nitrite, 
urobilinogen. Microscopic examination will only be performed if the dipstick test is outside of the reference range for 
leukocyte, blood, nitrite or protein 

Other: serology urine drug screen and serum pregnancy. 
Hematology, chemistry and quantitative urinalysis laboratory test results will be summarized by renal function group, parameter 
and visit and will also be presented in a listing 
Separate listings of for serology, urine drug screen and serum pregnancy will also be provided. 
Subject listings of abnormal on-study laboratory values will be provided. Similarly, clinically significant on-study laboratory data 
will be presented in a second listing.   
Vital Signs 
Vital signs will include the measurement of blood pressure, heart rate, oral temperature, and orthostatic blood pressure.  
For all vital signs, raw values, at each time point will be summarized by renal function group, parameter and visit. Vital signs data 
will also be presented in a listing. 
Subject listing of abnormal on-study vital signs values (Out-of-Range – Not Clinically Significant (NCS) or Clinically Significant 
(CS)) will be provided. Similarly, CS on-study vital signs values (Out-of-Range – CS) will be presented in a second listing. 
Electrocardiogram 
A 12-lead ECG will be obtained throughout the study. In some cases, repeat abnormal ECGs may be obtained. 
Raw values at each time point will be summarized by renal function group, parameter and visit and will also be presented in a 
listing. Overall safety assessment will also be presented in the listing. 
A subject listing of abnormal on-study ECG assessments (Abnormal – NCS or Abnormal – CS) will be provided. Similarly, CS on-
study ECG assessments (Abnormal – CS) will be presented in a second listing. 
Physical Examination Findings 
A physical examination will be conducted and will be presented in a listing. 
Columbia-Suicide Severity Rating Scale (C-SSRS) 
The Columbia-Suicide Severity Rating Scale (C-SSRS) is a suicidal ideation rating scale. The scale identifies behaviors and 
thoughts that are associated with an increased risk of suicidal actions in the future.  
Subjects who answer ‘Yes’ to any of the questions on the C-SSRS questionnaire will be presented in a listing. 
 
 


 
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11. 
INTERIM ANALYSES AND DATA SAFETY MONITORING 
 
First, subjects with severe renal impairment and healthy subjects with normal renal function will be enrolled. Samples will be 
assayed and PK will be performed. If substantial changes in the exposure of lasmiditan are observed in subjects with severe 
renal impairment compared to subjects with normal renal function, subjects with mild and moderate renal impairment will be 
enrolled. 
Interim analysis of subjects with severe renal impairment and healthy subjects with normal renal function will be performed as 
described in the regression analysis paragraph of Section 9. 
 
 


 
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12. 
CHANGES TO PROTOCOL-SPECIFIED ANALYSES 
 
There is no change from the planned analysis described in the protocol.  The analyses described in the protocol was meant to be 
an overview.  The final analyses is per this statistical analysis plan. 
 
 


 
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13. 
GENERAL INFORMATION RELATED TO DATA PRESENTATIONS 
 
Safety  
 
All programs used to generate statistical analyses will be validated according to Algorithme Pharma’s standard operating 
procedures. 
TFLs will be displayed on letter size paper, 8 ½ inches by 11 inches, using the Courier New font.     
In general, summary statistics for raw variables (i.e., variables measured at the study site or central laboratory) will be displayed 
as follows: if required minima, maxima, means, quartiles, standard deviations and confidence limits will be displayed to the same 
number of decimal places as the raw data; if required medians will be displayed to one additional decimal place.   
Percentages will be displayed to one decimal place. Percentages between 0 and 0.1 (exclusive) will be displayed as ‘<0.1’.  P-
values will be displayed to 3 decimal places. P-values that are less than 0.001 will be displayed as ‘<0.001’.   
The numbers of decimal places for summary statistics of derived variables (i.e., variables that are not measured by the study site 
but are calculated for analysis based on other measured variables) will be determined on a case by case basis.  In general, 
minima and maxima will be displayed to the commonly used unit of precision for the parameter. Means, medians, quartiles, and 
confidence limits will be displayed to one additional decimal place and standard deviations will be displayed to two additional 
decimal places. 
The formats and layouts of TFLs are provided in subsequent sections.  Actual formats and layouts may be altered slightly from 
those presented in the templates as necessary to accommodate actual data or statistics.  Minor format changes will not require 
updates to the SAP. 
The tables and listings listed below are common data displays. Their numbering and general content follow the ICH E3 
guidelines.  Some of the tables and listings may not be applicable/appropriate/necessary for a particular study.  Additional tables 
and listings may be included, provided the numbering scheme remains consistent with ICH E3. 
PK Data 
 
All programs used to generate statistical analyses will be validated according to Algorithme Pharma’s standard operating 
procedures. 
 
TFLs will be displayed on letter size paper, 8 ½ inches by 11 inches, using Tahoma. 
 
Raw variables (i.e., variables measured at the study site or central laboratory) will be displayed with the same number of decimal 
places as received as per bioanalytical laboratory. Derived variables (i.e., variables that are not measured by the study site but 
are calculated for analysis based on other measured variables) will be displayed as follow: 
 

All calculated pharmacokinetic parameter values should be reported to three significant digits. 

Observed concentration data, e.g. Cmax, should be reported as received.  

Observed time data, e.g. Tmax, should be reported as received. 

N and percentage values should be reported as whole numbers, except for the %AUC(tlast-∞). 

Median values should be treated as an observed parameter and reported to the same number of decimal places 
as minimum and maximum values. 
 
Summary statistics of raw variables: minima, mean, geometric mean, median, maxima, and standard deviation, coefficient of 
variation will be displayed with the same number of decimal places as the raw data; 
 


 
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
The following summary statistics will be listed for all variables except Tmax and  T1/2, arithmetic mean, SD, and CV; 
geometric mean and CV; N, minimum, maximum, and median. 

Summary statistics for Tmax, and other discrete parameters, will be limited to N, minimum, maximum, and median.  
Report not calculated (NC) for other statistics 

Summary statistics for T1/2 will be limited to geometric mean and CV; N, minimum, maximum, and median. Report not 
calculated (NC) for other statistics. 
 
Summary statistics of derived variables will be displayed with the same number of decimal places as the derived variable. 


 
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PLANNED END-OF-TEXT TABLES 
 
Demographic Data 
Table 14.1.1 
Subject Disposition – All Subjects 
Table 14.1.2.1 
Summary of Demographic Characteristics (Safety Population) 
Table 14.1.2.2 
Summary of Demographic Characteristics (Pharmacokinetic Population) 
 
Pharmacokinetic Data  
Section 14.2.1.1 
Statistical Analysis – SAS output - Lasmiditan 
Section 14.2.1.2 
Statistical Analysis – SAS output - (S)-M8 
Section 14.2.1.3 
Statistical Analysis – SAS output - (S,R)-M18 
Section 14.2.1.4 
Statistical Analysis – SAS output – M7 
Section 14.2.1.5 
Statistical Analysis – SAS output - (S,S)-M18 
 
 
 
Safety Data 
Tables in this section are based on the safety population unless otherwise stated. 
Table 14.3.1.1 
Summary of Adverse Events  
Table 14.3.1.2 
Summary of Treatment Emergent Adverse Events by System Organ Class and MedDRA 
Preferred Term 
Table 14.3.1.3 
Summary of Drug-Related Treatment Emergent Adverse Events by System Organ Class and 
MedDRA Preferred Term 
Table 14.3.2.1 
Listing of Deaths, Other Serious and Significant Adverse Events 
Table 14.3.2.2 
Listing of Treatment Emergent Adverse Events Leading to Withdrawal 
Table 14.3.4.1 
Listing of Abnormal On-Study Laboratory Values 
Table 14.3.4.2 
Listing of Clinically Significant On-Study Laboratory Values 
Table 14.3.4.3 
Summary of Blood Chemistry 
Table 14.3.4.4 
Summary of Hematology 
Table 14.3.4.5 
Summary of Quantitative Urinalysis 
Table 14.3.5.1 
Listing of Abnormal On-Study Vital Signs Values 
Table 14.3.5.2 
Listing of Clinically Significant On-Study Vital Signs Values 
Table 14.3.5.3 
Summary of Vital Signs 
Table 14.3.6.1 
Listing of Abnormal On-Study ECG Assessments 
Table 14.3.6.2 
Listing of Clinically Significant On-Study ECG Assessments 
Table 14.3.6.3 
Summary of ECG Assessments 
 


 
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PLANNED IN-TEXT TABLES 
PK Parameters of Lasmiditan 
Summary of Statistical Analysis of Lasmiditan 
PK Parameters of (S)-M8 
Summary of Statistical Analysis of (S)-M8 
PK Parameters of (S,R)-M18 
Summary of Statistical Analysis of (S,R)-M18 
PK Parameters of M7 
Summary of Statistical Analysis of M7 
PK Parameters of (S,S)-M18 
Summary of Statistical Analysis of (S,S)-M18 
 
PLANNED IN-TEXT FIGURES 
Linear Profile of the Mean for Lasmiditan  
Logarithmic Profile of the Mean for Lasmiditan 
Linear Regression of ln-Transformed Cmax vs eGFR (Lasmiditan) 
Linear Regression of ln-Transformed AUC(0-tlast) vs eGFR (Lasmiditan) 
Linear Regression of ln-Transformed AUC(0-∞) vs eGFR (Lasmiditan) 
Linear Regression of ln-Transformed CL/F vs eGFR (Lasmiditan) 
Linear Profile of the Mean for (S)-M8  
Logarithmic Profile of the Mean for (S)-M8 
Linear Profile of the Mean for (S,R)-M18  
Logarithmic Profile of the Mean for (S,R)-M18 
Linear Profile of the Mean for M7  
Logarithmic Profile of the Mean for M7 
Linear Profile of the Mean for (S,S)-M18  
Logarithmic Profile of the Mean for (S,S)-M18 
 
 
 


 
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PLANNED LISTINGS 
 
Listing 16.2.1 
Listing of Study Disposition 
Listing 16.2.2.1 
Listing of PK Blood Sampling Time Deviations 
Listing 16.2.2.2 
Listing of PK Urine Sampling Time Deviations 
Listing 16.2.3 
Listing of Analysis Populations 
Listing 16.2.4.1 
Listing of Demographic Characteristics 
Listing 16.2.4.2 
Listing of Screen Failure Subjects 
Listing 16.2.5 
Listing of Investigational Product Administration 
Listing 16.2.7 
Listing of Adverse Events  
Listing 16.2.8.1 
Listing of Blood Chemistry 
Listing 16.2.8.2 
Listing of Hematology 
Listing 16.2.8.3 
Listing of Urinalysis 
Listing 16.2.8.4 
Listing of Urine Drug Screen 
Listing 16.2.8.5 
Listing of Pregnancy Test 
Listing 16.2.8.6 
Listing of Serology 
Listing 16.2.9.1 
Listing of Alcohol Habits 
Listing 16.2.9.2 
Listing of Smoking Habits 
Listing 16.2.9.3 
Listing of Prior Medication 
Listing 16.2.9.4 
Listing of Concomitant Medication 
Listing 16.2.9.5 
Listing of Physical Examination 
Listing 16.2.9.6 
Listing of Vital Signs 
Listing 16.2.9.7 
Listing of ECG Assessments 
Listing 16.2.9.8 
Listing of Inclusion/Exclusion Criteria Summary  
Listing 16.2.9.9 
Listing of Medical History 
Listing 16.2.9.10 
Listing of Columbia-Suicide Severity Rating Scale (C-SSRS) 
 
Pharmacokinetic Data 
Appendix 16.2.6 
PK Data 
Appendix 16.2.6.1 
Lasmiditan 
Appendix 16.2.6.1.1 
PK Tables – Plasma 

Table X. Measured Human Plasma Concentrations  

Table X. Cumulative Area Under the Curve  

Table X. Pharmacokinetic Parameters  

Table X. Elimination Parameters  

Table X. Actual Sampling Time 
Appendix 16.2.6.1.2 
PK Tables – Urine  

Table X. Measured Human Urine Concentrations  

Table X. Cumulative Amount by Collection Intervals  

Table X. Pharmacokinetic Parameters  
Appendix 16.2.6.1.3 
PK – Figures – Plasma 

Figure x: Linear Profile of the Mean 

Figure x: Logarithmic Profile of the Mean  

Figure x: Individual Linear Profile of Subject x  

Figure x: Individual Logarithmic Profile of Subject x 

Figure x: Individual Elimination Profiles  
Appendix 16.2.6.2 
(S)-M8 
Appendix 16.2.6.2.1 
PK Tables – Plasma 

Table X. Measured Human Plasma Concentrations  


 
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
Table X. Cumulative Area Under the Curve  

Table X. Pharmacokinetic Parameters  

Table X. Elimination Parameters  

Table X. Actual Sampling Time 
Appendix 16.2.6.2.2 
PK Tables – Urine Table X. Measured Human Urine Concentrations  

Table X. Cumulative Amount by Collection Intervals  

Table X. Pharmacokinetic Parameters  
Appendix 16.2.6.2.3 
PK – Figures – Plasma 

Figure x: Linear Profile of the Mean 

Figure x: Logarithmic Profile of the Mean  

Figure x: Individual Linear Profile of Subject x  

Figure x: Individual Logarithmic Profile of Subject x 

Figure x: Individual Elimination Profiles  
Appendix 16.2.6.3 
 (S,R)-M18 
Appendix 16.2.6.3.1 
PK Tables – Plasma 

Table X. Measured Human Plasma Concentrations  

Table X. Cumulative Area Under the Curve  

Table X. Pharmacokinetic Parameters  

Table X. Elimination Parameters  

Table X. Actual Sampling Time 
Appendix 16.2.6.3.2 
PK Tables – Urine Table X. Measured Human Urine Concentrations  

Table X. Cumulative Amount by Collection Intervals  

Table X. Pharmacokinetic Parameters  
Appendix 16.2.6.3.3 
PK – Figures – Plasma 

Figure x: Linear Profile of the Mean 

Figure x: Logarithmic Profile of the Mean  

Figure x: Individual Linear Profile of Subject x  

Figure x: Individual Logarithmic Profile of Subject x 

Figure x: Individual Elimination Profiles  
Appendix 16.2.6.4 
 (S,S)-M18 
Appendix 16.2.6.4.1 
PK Tables – Plasma 

Table X. Measured Human Plasma Concentrations  

Table X. Cumulative Area Under the Curve  

Table X. Pharmacokinetic Parameters  

Table X. Elimination Parameters  

Table X. Actual Sampling Time 
Appendix 16.2.6.4.2 
PK Tables – Urine Table X. Measured Human Urine Concentrations  

Table X. Cumulative Amount by Collection Intervals  

Table X. Pharmacokinetic Parameters  
Appendix 16.2.6.4.3 
PK – Figures – Plasma 

Figure x: Linear Profile of the Mean 

Figure x: Logarithmic Profile of the Mean  

Figure x: Individual Linear Profile of Subject x  

Figure x: Individual Logarithmic Profile of Subject x 

Figure x: Individual Elimination Profiles  
Appendix 16.2.6.5 
M7 
Appendix 16.2.6.5.1 
PK Tables – Plasma 

Table X. Measured Human Plasma Concentrations  

Table X. Cumulative Area Under the Curve  

Table X. Pharmacokinetic Parameters  

Table X. Elimination Parameters 

Table X. Actual Sampling Time 


 
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Appendix 16.2.6.5.2 
PK Tables – Urine Table X. Measured Human Urine Concentrations  

Table X. Cumulative Amount by Collection Intervals  
Table X. Pharmacokinetic Parameters  
Appendix 16.2.6.5.3 
PK – Figures – Plasma 

Figure x: Linear Profile of the Mean 

Figure x: Logarithmic Profile of the Mean  

Figure x: Individual Linear Profile of Subject x 

Figure x: Individual Logarithmic Profile of Subject x  

Figure x: Individual Elimination Profiles 
 
 
 
 


 
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APPENDIX A 
STUDY SCHEDULES 
  
a Early Termination (ET). 
b Vital signs will be measured prior to dosing and approximately 2 and 4 hours after study drug administration. 


 
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c 12-lead ECG will be performed prior to dosing and approximately 2 hours after study drug administration. 
d Clinical laboratory tests (hematology, biochemistry, and urinalysis) will be performed in the evening prior to drug administration. 
e PK blood and urine samples will be collected according to schedule of PK assessments.  
 


 
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APPENDIX B 
Pharmacokinetic Parameters 
PK Parameter 
Definition 
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* Not calculated for metabolites 
 
 


 
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APPENDIX C 
TABLE SHELLS 
 
 


 
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Table 14.1.1 
Subject Disposition 
(All Subjects) 
 
   
   
Healthy Renal 
Function 
(N=XX) 
 
Severe Renal 
Function 
(N=XX) 
Overall 
(N=XX) 
  
  
 
 
 
 
Subjects Enrolled 
 
 
 
 
xx 
 
 
 
 
 
 
Screen Fail Subjects 
 
 
 
 
xx 
 
 
 
 
 
 
Subjects Screened [N] 
 
 
 
 
xx (xx.x) 
 
 
 
 
 
 
Subjects Completed the Study [n(%)] 
YES 
 
 
 
xx (xx.x) 
 
NO 
 
 
 
xx (xx.x) 
 
 
 
 
 
 
If No, Reason of Study Discontinuation [n(%)] 
Reason 1 
 
 
 
xx (xx.x) 
 
Reason 2 
 
 
 
xx (xx.x) 
 
Reason 3 
 
 
 
xx (xx.x) 
 
Etc. 
 
 
 
xx (xx.x) 
 
 
 
 
 
 
Number of Subjects Included in Each Analysis 
Population [n(%)] 
Safety Population 
 
 
 
xx (xx.x) 
 
Pharmacokinetic Population 
 
 
 
xx (xx.x) 
 
 
 
 
 
 
Programming Note: Please add Moderate and Mild Renal Function Groups to the table if enrolled 
  
  
 
 
 
 
 
Note: The percentages are based on the number of subjects screened. 
 
 
 
Date: VERSION – YYYY-MM-DD 
Data Source: XXXX 
Program Source:  XXXXX.sas 
 
 
 
 


 
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Table 14.1.2.1 
Summary of Demographic Characteristics 
(Safety Population) 
 
   
   
Healthy Renal 
Function 
(N=XX) 
 
Severe Renal 
Function 
 (N=XX) 
Etc. 
Overall 
(N=XX) 
 
  
  
 
 
 
 
 Age (years) 
N 
xx 
xx 
xx 
xx 
  
Mean (SD) 
xx (xx.x) 
xx (xx.x) 
xx (xx.x) 
xx (xx.x) 
  
Median 
xx.x 
xx.x 
xx.x 
xx.x 
  
Min, Max 
xx, xx 
xx, xx 
xx, xx 
xx, xx 
  
 
 
 
 
 
 Gender [n(%)] 
MALE 
xx (xx.x) 
xx (xx.x) 
xx (xx.x) 
xx (xx.x) 
  
FEMALE 
 
 
 
 
  
 
 
 
 
 
 Ethnicity [n(%)] 
HISPANIC/LATINO 
xx (xx.x) 
xx (xx.x) 
xx (xx.x) 
xx (xx.x) 
  
NOT HISPANIC/NOT LATINO 
xx (xx.x) 
xx (xx.x) 
xx (xx.x) 
xx (xx.x) 
  
 
 
 
 
 
 Race [n(%)] 
RACE1 
xx (xx.x) 
xx (xx.x) 
xx (xx.x) 
xx (xx.x) 
  
RACE2 
xx (xx.x) 
xx (xx.x) 
xx (xx.x) 
xx (xx.x) 
  
Etc. 
xx (xx.x) 
xx (xx.x) 
xx (xx.x) 
xx (xx.x) 
  
 
 
 
 
 
 Weight (kg) 
N 
xx 
xx 
xx 
xx 
  
Mean (SD) 
xx (xx.x) 
xx (xx.x) 
xx (xx.x) 
xx (xx.x) 
  
Median 
xx.x 
xx.x 
xx.x 
xx.x 
  
Min, Max 
xx, xx 
xx, xx 
xx, xx 
xx, xx 
  
 
 
 
 
 
 Height (cm) 
N 
xx 
xx 
xx 
xx 
  
Mean (SD) 
xx (xx.x) 
xx (xx.x) 
xx (xx.x) 
xx (xx.x) 
  
Median 
xx.x 
xx.x 
xx.x 
xx.x 
  
Min, Max 
xx, xx 
xx, xx 
xx, xx 
xx, xx 
  
 
 
 
 
 
 Body Mass Index(kg/m2) 
N 
xx 
xx 
xx 
xx 
  
Mean (SD) 
xx (xx.x) 
xx (xx.x) 
xx (xx.x) 
xx (xx.x) 
  
Median 
xx.x 
xx.x 
xx.x 
xx.x 
  
Min, Max 
xx, xx 
xx, xx 
xx, xx 
xx, xx 
 Programming Note: Please add Moderate and Mild Renal Function Groups to the table if enrolled 
 
 
  
 
 
 
 
 
Date: VERSION – YYYY-MM-DD 
Data Source: XXXX 
Program Source:  XXXXX.sas 
 
 
 


 
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Similar Table: 
 
Table 14.1.2.2 Summary of Demographic Characteristics (Pharmacokinetic Population) 
 
 
 
 


 
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Table 14.3.1.1 
Summary of Adverse Events  
(Safety Population) 
 
   
 
 
 
 
 
 
Healthy Renal 
Function 
(N=XX) 
 
Severe Renal 
Function 
(N=XX) 
Etc. 
Overall 
(N=XX) 
 
 
  
  
 
 
 
 
 Adverse Events (AEs) Reported [n] 
 
 
 
xx 
 
 
 
 
 
 
 
 
 Treatment Emergent Adverse Events (TEAEs) Reported [n] 
xx 
xx 
xx 
xx 
 
 
 
 
 
 
 
 
Subjects With At Least One TEAE [n(%)]  [1] 
xx (xx.x) 
xx (xx.x) 
xx (xx.x) 
xx (xx.x) 
 
 
 
 
 
 
 
Subjects With At Least One Drug-Related TEAE [n(%)] [1] 
[3] 
xx (xx.x) 
xx (xx.x) 
xx (xx.x) 
xx (xx.x) 
 
 
 
 
 
 
 
TEAEs Relationship  [2] 
 
 
 
 
 
Related [n(%)] [3] 
xx (xx.x) 
xx (xx.x) 
xx (xx.x) 
xx (xx.x) 
 
Not Related [n(%)] 
xx (xx.x) 
xx (xx.x) 
xx (xx.x) 
xx (xx.x) 
 
 
 
 
 
 
 
TEAEs Severity/Intensity  [2] 
 
 
 
 
 
Mild [n(%)]   
xx (xx.x) 
xx (xx.x) 
xx (xx.x) 
xx (xx.x) 
 
Moderate [n(%)]   
xx (xx.x) 
xx (xx.x) 
xx (xx.x) 
xx (xx.x) 
 
Severe [n(%)]   
xx (xx.x) 
xx (xx.x) 
xx (xx.x) 
xx (xx.x) 
 
 Life-Threatening [n(%)] 
xx (xx.x) 
xx (xx.x) 
xx (xx.x) 
xx (xx.x) 
 
 
 
 
 
 
 
 Serious Adverse Events (SAEs) Reported [n] [2] 
xx 
xx 
xx 
xx 
 
 
 
 
 
 
 
Subjects With At Least One SAE [n(%)][1] 
xx (xx.x) 
xx (xx.x) 
xx (xx.x) 
xx (xx.x) 
 
 
 
 
 
 
 
Subject With an TEAE Leading to Withdrawal [n(%)] [1] 
xx (xx.x) 
xx (xx.x) 
xx (xx.x) 
xx (xx.x) 
 
 
 
 
 
 
 
Death [n(%)]  [1] 
xx (xx.x) 
xx (xx.x) 
xx (xx.x) 
xx (xx.x) 
 
  
 
  
 
 
 
 
 Programming Note: Please add Moderate and Mild Renal Function Groups to the table if enrolled 
 
[1] Percentages are based on the number of subjects in the Safety population in each treatment group. 
[2] Percentages are based on the total number of treatment emergent adverse events reported in each treatment group. 
[3] TEAE that was reported with a relationship of “reasonable possibility”. 
Date: VERSION – YYYY-MM-DD 
Data Source: XXXX 
Program Source:  XXXXX.sas 


 
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Table 14.3.1.2 
Summary of Treatment Emergent Adverse Events by System Organ Class and MedDRA Preferred Term 
(Safety Population) 
 
   
   
 
 
 
  SOC 
   MedDRA Preferred Term 
 Healthy Renal 
Function 
(N=XX) 
 
Severe Renal Function 
(N=XX) 
Etc. 
 
 
  
  
 
 
 
 
 
 
 
 
 
 Subjects With At Least One TEAE [n(%)] 
 
xx (xx.x) 
xx (xx.x) 
 
  
 
 
 
 
 System Organ Class 1 [n(%)] 
 
xx (xx.x) 
xx (xx.x) 
 
   MedDRA Term 11 [n(%)] 
 
xx (xx.x) 
xx (xx.x) 
 
   MedDRA Term 12 [n(%)] 
 
xx (xx.x) 
xx (xx.x) 
 
   MedDRA Term 13 [n(%)] 
 
xx (xx.x) 
xx (xx.x) 
 
  
 
 
 
 
 System Organ Class 2 [n(%)] 
 
xx (xx.x) 
xx (xx.x) 
 
   MedDRA Term 21 [n(%)] 
 
xx (xx.x) 
xx (xx.x) 
 
   MedDRA Term 22 [n(%)] 
 
xx (xx.x) 
xx (xx.x) 
 
   MedDRA Term 23 [n(%)] 
 
xx (xx.x) 
xx (xx.x) 
 
   Etc. 
 
xx (xx.x) 
xx (xx.x) 
 
  
 
 
 
 
 
 
  
 
 
 
 Programming Note: Please add Moderate and Mild Renal Function Groups to the table if enrolled 
 
 
Note: Each treatment emergent adverse event is counted only once for each subject within each System Organ Class and MedDRA 
Preferred Term. 
 
 
Date: VERSION – YYYY-MM-DD 
Data Source: XXXX 
Program Source:  XXXXX.sas 
 
 
Similar Table: Table 14.3.1.3 Summary of Drug-Related Treatment Emergent Adverse Events by System Organ Class and MedDRA Preferred Term 
 
 
 
 
 


 
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     Page 1 of x 
 
Table 14.3.2.1 
Listing of Deaths, Other Serious and Significant Adverse Events 
(Safety Population) 
 
Subject ID 
Day/ 
Group/ 
AE # 
SOC 
  MedDRA 
Preferred Term 
    Description 
of AE 
Onset Date  
Time 
(Time since 
Last Dose) 
Resolution 
Date Time 
(Duration) 
I: Maximal 
Intensity 
R: Causality 
Assessment 
O: Outcome 
S: Serious AE 
D: AE Lead To 
Discontinuation 
Action Taken With Study 
Treatment / Other 
Action(s) Taken / 
Concomitant Given 
 
 
 
  
  
 
 
 
 
 
xxx 
xxxxx 
xxxxx 
xxxxxxxxxxxx 
  xxxxxxxxxxxx 
     
xxxxxxxxxxxx 
YYYY-MM-DD/ 
HH:MM 
(DD:HH:MM) 
YYYY-MM-
DD/ 
HH:MM 
(DD:HH:MM) xxxxxx 
xxxxx 
xxxxxx 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
  
 
  
 
 
 
 
 
 
 
 
Date: VERSION – YYYY-MM-DD 
Data Source: XXXX 
Program Source:  XXXXX.sas 
 
 
Similar Tables:  
14.3.2.2  Listing of Adverse Events Leading to Withdrawal 
 
 
 


 
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Table 14.3.4.1 
Listing of Abnormal On-Study Laboratory Values 
(Safety Population) 
 
Category/ 
Parameter (Unit) 
Reference 
Range 
Subject ID 
Visit 
 
 
Date / Time 
 
Value 
 
Out-of-Range 
Flag 
Assessment [1] 
 
 
 
  
 
 
 
 
 
 
Lab Category 1 
 
 
 
 
  
  
 
  Lab Test 11 
xxx-xxx 
xxx 
xxxxxx 
xxxxxx 
 
xxx 
 
xxx 
xxx 
 
 
 
 
 
 
 
 
 
 
  Lab Test 12 
xxx-xxx 
xxx 
xxxxxx 
xxxxxx 
 
xxx 
 
xxx 
xxx 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Lab Category 2 
 
 
 
 
 
 
 
 
 
  Lab Test 21 
xxx-xxx 
xxx 
xxxxxx 
xxxxxx 
 
xxx 
 
xxx 
xxx 
 
 
 
 
 
 
 
 
 
 
  Lab Test 22 
xxx-xxx 
xxx 
xxxxxx 
xxxxxx 
 
xxx 
 
xxx 
xxx 
 
 
 
 
 
 
 
 
 
 
  Etc. 
xxx-xxx 
xxx 
xxxxxx 
xxxxxx 
 
xxx 
 
xxx 
xxx 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
  
 
 
 
 
 
 
 
 
 
 
 
[1] NCS: Not Clinically Significant   /   CS: Clinically Significant   /   RPT: Repeated   /  TBC: To Be Controlled. 
Note(s): Abnormal values are determined by applying the reference ranges to the results as reported by the external laboratory 
analysis. 
 
Date: VERSION – YYYY-MM-DD 
Data Source: XXXX 
Program Source:  XXXXX.sas 
 
 
 


 
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     Page 1 of x 
 
Table 14.3.4.2 
Listing of Clinically Significant On-Study Laboratory Values 
(Safety Population) 
 
Category/ 
Parameter (Unit) 
Reference Range 
Subject ID 
Visit 
 
 
Date / Time 
 
Value 
 
Out-of-
Range Flag  Assessment [1] 
 
 
 
  
 
 
 
 
 
 
Lab Category 1 
 
 
 
 
  
  
 
  Lab Test 11 
xxx-xxx 
xxx 
xxxxxx 
xxxxxx 
 
xxx 
 
xxx 
xxx 
 
 
 
 
 
 
 
 
 
 
  Lab Test 12 
xxx-xxx 
xxx 
xxxxxx 
xxxxxx 
 
xxx 
 
xxx 
xxx 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Lab Category 2 
 
 
 
 
 
 
 
 
 
  Lab Test 21 
xxx-xxx 
xxx 
xxxxxx 
xxxxxx 
 
xxx 
 
xxx 
xxx 
 
 
 
 
 
 
 
 
 
 
  Lab Test 22 
xxx-xxx 
xxx 
xxxxxx 
xxxxxx 
 
xxx 
 
xxx 
xxx 
 
 
 
 
 
 
 
 
 
 
  Etc. 
xxx-xxx 
xxx 
xxxxxx 
xxxxxx 
 
xxx 
 
xxx 
xxx 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
  
 
 
 
 
 
 
 
 
 
 
 
[1] CS: Clinically Significant   /   RPT: Repeated    /    TBC: To Be Controlled 
Note(s): Abnormal values are determined by applying the reference ranges to the results as reported by the external laboratory 
analysis. 
 
Date: VERSION – YYYY-MM-DD 
Data Source: XXXX 
Program Source:  XXXXX.sas 
 
 
 
 
 
 


 
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Table 14.3.4.3 
Summary of Blood Chemistry 
(Safety Population) 
 
   
 
 
   
 
 
 
 
Parameter (unit) 
Visit Name 
 
Statistic   
 Healthy Renal 
Function(N=XX) 
Severe Renal 
Function 
 (N=XX) 
Etc. (N=XX) 
 
 
 
 
 
 
 
 
 
xxx (xxx) 
Screening 
Value 
N 
xx 
xx 
xx 
xx 
 
 
 
Mean (SD) 
xx.x (xx.xx) 
xx.x (xx.xx) 
xx.x (xx.xx) 
xx.x (xx.xx) 
 
 
 
Median 
xx.x 
xx.x 
xx.x 
xx.x 
 
 
 
Min, Max 
xx, xx 
xx, xx 
xx, xx 
xx, xx 
 
 
 
 
 
 
 
 
 
Day -1 
Value 
N 
xx 
xx 
xx 
xx 
 
 
 
Mean (SD) 
xx.x (xx.xx) 
xx.x (xx.xx) 
xx.x (xx.xx) 
xx.x (xx.xx) 
 
 
 
Median 
xx.x 
xx.x 
xx.x 
xx.x 
 
 
 
Min, Max 
xx, xx 
xx, xx 
xx, xx 
xx, xx 
 
 
 
 
 
 
 
 
 
Etc. 
 
N 
xx 
xx 
xx 
xx 
 
 
 
Mean (SD) 
xx.x (xx.xx) 
xx.x (xx.xx) 
xx.x (xx.xx) 
xx.x (xx.xx) 
 
 
 
Median 
xx.x 
xx.x 
xx.x 
xx.x 
 
 
 
Min, Max 
xx, xx 
xx, xx 
xx, xx 
xx, xx 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Programming Note: Please add Moderate and Mild Renal Function Groups to the table if enrolled 
 
 
 
 
 
 
 
 
 
 
Date: VERSION – YYYY-MM-DD 
Data Source: XXXX 
Program Source:  XXXXX.sas 
 
Similar Tables:  
14.3.4.4  Summary of Hematology 
14.3.4.5   Summary of Quantitative Urinalysis 
 
 


 
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Table 14.3.5.1 
Listing of Abnormal On-Study Vital Signs Values 
(Safety Population) 
Assessment (Units) Subject ID 
Visit 
 
Elapsed 
Time 
 
Position 
Date / Time 
 Value 
Safety Review 
 
 
  
 
 
 
 
 
 
 
 
 
 
 
 
 
  
 
Vital Sign Test 1 
xxx 
xxxxxx 
 
xxxxxx 
xxxxxx 
YYYY-MM-DD:XX:XX 
 
xxx 
xxx 
 
 
 
 
 
 
 
 
 
 
xxx 
xxxxxx 
 
xxxxxx 
xxxxxx 
YYYY-MM-DD:XX:XX 
 
xxx 
xxx 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Vital Sign Test 2 
xxx 
xxxxxx 
 
xxxxxx 
xxxxxx 
YYYY-MM-DD:XX:XX 
 
xxx 
xxx 
 
 
 
 
 
 
 
 
 
xxx 
xxxxxx 
 
xxxxxx 
xxxxxx 
YYYY-MM-DD:XX:XX 
 
xxx 
xxx 
 
 
 
 
 
 
 
 
 
Etc. 
xxx 
xxxxxx 
 
xxxxxx 
xxxxxx 
YYYY-MM-DD:XX:XX 
 
xxx 
xxx 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
  
 
 
 
 
 
 
 
 
 
Date: VERSION – YYYY-MM-DD 
Data Source: XXXX 
Program Source:  XXXXX.sas 
 
 
 


 
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     Page 1 of x 
Table 14.3.5.2 
Listing of Clinically Significant On-Study Vital Signs Values 
(Safety Population) 
Assessment (Units) Subject ID 
Visit 
 
Elapsed 
Time 
 
Position 
Date / Time 
 Value 
Safety Review 
 
 
  
 
 
 
 
 
 
 
 
 
 
 
 
 
  
 
Vital Sign Test 1 
xxx 
xxxxxx 
 
xxxxxx 
xxxxxx 
YYYY-MM-DD:XX:XX 
 
xxx 
xxx 
 
 
 
 
 
 
 
 
 
 
xxx 
xxxxxx 
 
xxxxxx 
xxxxxx 
YYYY-MM-DD:XX:XX 
 
xxx 
xxx 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Vital Sign Test 2 
xxx 
xxxxxx 
 
xxxxxx 
xxxxxx 
YYYY-MM-DD:XX:XX 
 
xxx 
xxx 
 
 
 
 
 
 
 
 
 
xxx 
xxxxxx 
 
xxxxxx 
xxxxxx 
YYYY-MM-DD:XX:XX 
 
xxx 
xxx 
 
 
 
 
 
 
 
 
 
Etc. 
xxx 
xxxxxx 
 
xxxxxx 
xxxxxx 
YYYY-MM-DD:XX:XX 
 
xxx 
xxx 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
  
 
 
 
 
 
 
 
 
 
Date: VERSION – YYYY-MM-DD 
Data Source: XXXX 
Program Source:  XXXXX.sas 
 
 
 
 


 
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     Page 1 of x 
Table 14.3.5.3 
Summary of Vital Signs 
(Safety Population) 
 
 
 
 
 
 
 
 
 
 
Parameter (unit) 
 
Visit 
Timepoint 
 
Statistic 
Healthy Renal 
Function 
(N=XX) 
Severe Renal 
Function 
(N=XX) 
Etc. 
(N=XX) 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Vital Sign Test 1 
 
 
 
 
 
 
 
 
Screening 
 
Value 
N 
 
 
xx 
 
 
 
 
Mean (SD) 
 
 
xx (xx.x) 
 
 
 
 
Median 
 
 
xx.x 
 
 
 
 
Min, Max 
 
 
xx, xx 
 
Day 1 
2 Hours 
Value 
 
 
 
 
 
 
 
 
N 
xx 
xx 
xx 
 
 
 
 
Mean (SD) 
xx (xx.x) 
xx (xx.x) 
xx (xx.x) 
 
 
 
 
Median 
xx.x 
xx.x 
xx.x 
 
 
 
 
Min, Max 
xx, xx 
xx, xx 
xx, xx 
 
 
 
 
 
 
 
 
 
Day 1 
4 Hours 
Value 
 
 
 
 
 
 
 
 
N 
xx 
xx 
xx 
 
 
 
 
Mean (SD) 
xx (xx.x) 
xx (xx.x) 
xx (xx.x) 
 
 
 
 
Median 
xx.x 
xx.x 
xx.x 
 
 
 
 
Min, Max 
xx, xx 
xx, xx 
xx, xx 
 
 
 
 
 
 
 
 
Etc. 
Etc. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
PROGRAMMING NOTE:  All visits outlined in Appendix A will be included. Please add Moderate and Mild Renal Function Groups to 
the table if enrolled 
  
 
  
 
 
 
 
 
 
Date: VERSION – YYYY-MM-DD 
Data Source: XXXX 
Program Source:  XXXXX.sas 
 
 


 
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     Page 1 of x 
 
Table 14.3.6.1 
Listing of Abnormal On-Study ECG Assessments 
(Safety Population) 
 
Subject ID 
Visit 
Time Point 
Date / Time 
  Position 
Safety Review Parameter (Unit) 
Value 
 
 
 
 
  
 
 
 
 
xxxxx 
xxxxxx 
xxx 
YYYY-MM-DD: HH:MM   xxxxxx 
xxxxxx 
 
 
 
 
 
 
   
 
 
 
 
xxxxxx 
xxx 
YYYY-MM-DD: HH:MM   xxxxxx 
xxxxxx 
 
 
 
xxxxxx 
xxx 
YYYY-MM-DD: HH:MM   xxxxxx 
xxxxxx 
 
 
 
 
 
 
   
 
 
 
 
 
 
 
   
 
 
 
xxxxx 
xxxxxx 
xxx 
YYYY-MM-DD: HH:MM   xxxxxx 
xxxxxx 
 
 
 
 
 
 
   
 
 
 
xxxxx 
xxxxxx 
xxx 
YYYY-MM-DD: HH:MM   xxxxxx 
xxxxxx 
 
 
 
 
 
 
   
 
 
 
 
 
 
 
   
 
 
 
 
 
 
 
   
 
 
 
 
 
 
 
   
 
 
 
 
 
 
 
  
 
 
 
 
 
 
 
 
  
 
 
 
 
 
 
 
 
  
 
 
 
 
 
 
 
 
  
 
 
 
 
  
 
 
 
  
 
 
 
 
 
 
 
Date: VERSION – YYYY-MM-DD 
Data Source: XXXX 
Program Source:  XXXXX.sas 
 
 
 


 
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Table 14.3.6.2 
Listing of Clinically On-Study ECG Assessments 
(Safety Population) 
 
Subject ID 
Visit 
Time Point 
Date / Time 
  
Position 
Safety Review Parameter (Unit) 
Value 
 
 
 
 
 
 
 
 
 
 
xxxxx 
xxxxxx 
xxx 
YYYY-MM-DD: HH:MM 
  
xxxxxx 
xxxxxx 
 
 
 
 
 
 
  
 
 
 
 
xxxxx 
xxxxxx 
xxx 
YYYY-MM-DD: HH:MM 
  
xxxxxx 
xxxxxx 
 
 
xxxxx 
xxxxxx 
xxx 
YYYY-MM-DD: HH:MM 
  
xxxxxx 
xxxxxx 
 
 
 
 
 
 
  
 
 
 
 
 
 
 
 
  
 
 
 
 
xxxxx 
xxxxxx 
xxx 
YYYY-MM-DD: HH:MM 
  
xxxxxx 
xxxxxx 
 
 
 
 
 
 
  
 
 
 
 
xxxxx 
xxxxxx 
xxx 
YYYY-MM-DD: HH:MM 
  
xxxxxx 
xxxxxx 
 
 
 
 
 
 
  
 
 
 
 
 
 
 
 
  
 
 
 
 
 
 
 
 
  
 
 
 
 
 
 
 
 
  
 
 
 
 
 
 
 
 
  
 
 
 
 
 
 
 
 
  
 
 
 
 
 
 
 
 
  
 
 
 
 
 
 
 
 
  
 
 
 
 
  
 
 
 
 
 
 
 
 
 
 
 
 
Date: VERSION – YYYY-MM-DD 
Data Source: XXXX 
Program Source:  XXXXX.sas 
 
 


 
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Table 14.3.6.3 
Summary of ECG Assessments 
(Safety Population) 
 
 
 
 
 
 
 
 
 
 
Parameter (unit) 
 
Visit 
Timepoint 
 
Statistic 
Healthy Renal 
Function 
(N=XX) 
Severe Renal 
Function 
(N=XX) 
Etc. 
(N=XX) 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
ECG Assessment Test 1 
 
 
 
 
 
 
 
 
Screening 
 
Value 
N 
 
 
xx 
 
 
 
 
Mean (SD) 
 
 
xx (xx.x) 
 
 
 
 
Median 
 
 
xx.x 
 
 
 
 
Min, Max 
 
 
xx, xx 
 
Day -1 
 
Value 
 
 
 
 
 
 
 
 
N 
xx 
xx 
xx 
 
 
 
 
Mean (SD) 
xx (xx.x) 
xx (xx.x) 
xx (xx.x) 
 
 
 
 
Median 
xx.x 
xx.x 
xx.x 
 
 
 
 
Min, Max 
xx, xx 
xx, xx 
xx, xx 
 
 
 
 
 
 
 
 
 
Day 1 
Pre-dose 
Value 
 
 
 
 
 
 
 
 
N 
xx 
xx 
xx 
 
 
 
 
Mean (SD) 
xx (xx.x) 
xx (xx.x) 
xx (xx.x) 
 
 
 
 
Median 
xx.x 
xx.x 
xx.x 
 
 
 
 
Min, Max 
xx, xx 
xx, xx 
xx, xx 
 
 
 
 
 
 
 
 
Etc. 
Etc. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
PROGRAMMING NOTE:  All visits outlined in Appendix A will be included. Please add Moderate and Mild Renal Function Groups to 
the table if enrolled 
  
 
  
 
 
 
 
 
 
Date: VERSION – YYYY-MM-DD 
Data Source: XXXX 
Program Source:  XXXXX.sas 
 
 
 
 


 
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APPENDIX D 
PHARMACOKINETIC OUTPUTS SHELLS  
Measured Human Plasma Concentrations of Lasmiditan, Normal Renal Function, CUD-P4-001 

Time 
(h)  
0.00 
0.25 
0.50 
1.00 
… 
… 
… 
… 
… 
36.00 
Renal Function 
Subject 
Concentration 
(ng/mL)  
Normal 
101 
 
 
 
 
 
 
 
 
 
 
… 
 
 
 
 
 
 
 
 
 
 
… 
 
 
 
 
 
 
 
 
 
 
… 
 
 
 
 
 
 
 
 
 
 
… 
 
 
 
 
 
 
 
 
 
 
… 
 
 
 
 
 
 
 
 
 
 
… 
 
 
 
 
 
 
 
 
 
 
108 
 
 
 
 
 
 
 
 
 
 
N 
 
 
 
 
 
 
 
 
 
 
Mean 
 
 
 
 
 
 
 
 
 
 
SD  
 
 
 
 
 
 
 
 
 
 
 
Min  
 
 
 
 
 
 
 
 
 
 
Median 
 
 
 
 
 
 
 
 
 
 
Max 
 
 
 
 
 
 
 
 
 
 
CV% 
 
 
 
 
 
 
 
 
 
 
Geometric Mean 
 
 
 
 
 
 
 
 
 
 
Geometric CV% 
 
 
 
 
 
 
 
 
 
 
BLQ : Below Limit of Quantitation 
NC: Not Calculated 
 
Similar tables will be presented for all renal groups, for urine concentrations and for all analytes. 


 
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Cumulative Area Under the Curve of Lasmiditan, Normal Renal Function, CUD-P4-001 

Time 
(h)  
0.00 
0.25 
0.50 
1.00 
… 
… 
… 
… 
… 
36.00 
Renal Function 
Subject 
Cumulative AUC 
(ng*h/mL)  
Normal 
101 
 
 
 
 
 
 
 
 
 
 
… 
 
 
 
 
 
 
 
 
 
 
… 
 
 
 
 
 
 
 
 
 
 
… 
 
 
 
 
 
 
 
 
 
 
… 
 
 
 
 
 
 
 
 
 
 
… 
 
 
 
 
 
 
 
 
 
 
… 
 
 
 
 
 
 
 
 
 
 
108 
 
 
 
 
 
 
 
 
 
 
N 
 
 
 
 
 
 
 
 
 
 
Mean 
 
 
 
 
 
 
 
 
 
 
SD  
 
 
 
 
 
 
 
 
 
 
Min  
 
 
 
 
 
 
 
 
 
 
Median 
 
 
 
 
 
 
 
 
 
 
Max 
 
 
 
 
 
 
 
 
 
 
 
CV% 
 
 
 
 
 
 
 
 
 
 
Geometric Mean 
 
 
 
 
 
 
 
 
 
 
Geometric CV% 
 
 
 
 
 
 
 
 
 
 
NC: Not Calculated 
 
Similar tables will be presented for all renal groups, for urine data by intervals and for all analytes. 
 


 
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Pharmacokinetic Parameters of Lasmiditan, Normal Renal Function, CUD-P4-001 
Renal Function 
Subject 
Cmax 
(ng/mL)  
Tmax 
(h)  
AUC(0-tlast) 
(ng*h/mL)  
AUC(0-∞) 
(ng*h/mL)  
%AUC(0-tlast/∞) 
(%) 
T1/2 
(h) 
CL/F 
(L/h)  
VZ/F 
(L)  
Normal 
101 
 
 
 
 
 
 
 
 
… 
 
 
 
 
 
 
 
 
… 
 
 
 
 
 
 
 
 
… 
 
 
 
 
 
 
 
 
… 
 
 
 
 
 
 
 
 
… 
 
 
 
 
 
 
 
 
… 
 
 
 
 
 
 
 
 
108 
 
 
 
 
 
 
 
 
N 
 
 
 
 
 
 
 
 
Mean 
 
NC 
 
 
 
NC 
 
 
SD  
 
NC 
 
 
 
NC 
 
 
Min  
 
 
 
 
 
 
 
 
Median 
 
 
 
 
 
 
 
 
Max 
 
 
 
 
 
 
 
 
CV% 
 
NC 
 
 
 
NC 
 
 
 
Geometric Mean 
 
NC 
 
 
 
 
 
 
Geometric CV% 
 
NC 
 
 
 
 
 
 
Similar tables will be presented for all renal groups, for urine parameters and for all analytes. 
 
 


 
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Elimination Parameters of Lasmiditan, Normal Renal Function, CUD-P4-001 
Renal Function 
Subject 
TLIN 
(h)  
TLQC 
(h)  
Number of Points 
R2 
λz 
(1/h)  
Normal 
101 
 
 
 
 
 
… 
 
 
 
 
 
… 
 
 
 
 
 
… 
 
 
 
 
 
… 
 
 
 
 
 
… 
 
 
 
 
 
… 
 
 
 
 
 
108 
 
 
 
 
 
N 
 
 
 
 
 
Mean 
 
 
 
 
 
SD  
 
 
 
 
 
Min  
 
 
 
 
 
 
Median 
 
 
 
 
 
Max 
 
 
 
 
 
CV% 
 
 
 
 
 
Geometric Mean 
 
 
 
 
 
Geometric CV% 
 
 
 
 
 
A similar table will be presented for all renal groups and for all analytes. 


 
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Actual Sampling Time of Lasmiditan, Normal Renal Function, CUD-P4-001 

Time 
(h)  
0.00 
0.25 
0.50 
1.00 
… 
… 
… 
… 
… 
… 
… 
… 
… 
36.00 
Renal Function 
Subject 
Actual Time 
(h)  
Normal 
101 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
… 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
… 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
… 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
… 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
… 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
… 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
108 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
N 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Mean 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
SD  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Min  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Median 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Max 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
CV% 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Geometric Mean 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Geometric CV% 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
NC: Not Calculated 
A similar table will be presented for all renal groups and for all analytes. 
 
 


 
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Pairwise Comparisons of Lasmiditan, CUD-P4-001 
Parameters 
Geometric LSmeansa 
Comparison 
Adjusted p-
value 
Ratio 
(%) 
90% Confidence Limits (%) 
Group 
 
Lower  
Upper 
Cmax 
Mild (n=x) 
 
Mild vs Normal 
 
 
 
 
Moderate (n=x) 
 
Moderate vs Normal 
 
 
 
 
Severe (n=x) 
 
Severe vs Normal 
 
 
 
 
Normal (n=x) 
 
Mild vs Moderate 
 
 
 
 
NA 
NA 
Mild vs Severe 
 
 
 
 
NA 
NA 
Moderate vs Severe 
 
 
 
 
AUC(0-tlast) 
Mild (n=x) 
 
Mild vs Normal 
 
 
 
 
Moderate (n=x) 
 
Moderate vs Normal 
 
 
 
 
Severe (n=x) 
 
Severe vs Normal 
 
 
 
 
Normal (n=x) 
 
Mild vs Moderate 
 
 
 
 
NA 
NA 
Mild vs Severe 
 
 
 
 
NA 
NA 
Moderate vs Severe 
 
 
 
 
AUC(0-∞) 
Mild (n=x) 
 
Mild vs Normal 
 
 
 
 
Moderate (n=x) 
 
Moderate vs Normal 
 
 
 
 
Severe (n=x) 
 
Severe vs Normal 
 
 
 
 
Normal (n=x) 
 
Mild vs Moderate 
 
 
 
 
NA 
NA 
Mild vs Severe 
 
 
 
 
NA 
NA 
Moderate vs Severe 
 
 
 
 
a Cmax is presented in ng/mL, AUC(0-tlast) and AUC(0-∞) are presented in ng*h/mL 


 
Research Protocol No CUD-P4-001 | Sponsor Project No COL MIG-113| Version FINAL 3.2 | 2017/10/25 
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PHARMACOKINETIC FIGURES SHELLS  
Figure 1: Linear Profile of the Mean of Lasmiditan in Plasma 
 
 
The figure does not reflect the actual data of the study 
Figures will be presented for all analytes. 
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Research Protocol No CUD-P4-001 | Sponsor Project No COL MIG-113| Version FINAL 3.2 | 2017/10/25 
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Figure 2: Logarithmic Profile of the Mean of Lasmiditan in Plasma 
 
 
The figure does not reflect the actual data of the study. 
Figures will be presented for all analytes. 
 
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Research Protocol No CUD-P4-001 | Sponsor Project No COL MIG-113| Version FINAL 3.2 | 2017/10/25 
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Figures 2+1 to (2+1)+N: Individual Linear Profile of Lasmiditan in Plasma 
 
The figure does not reflect the actual data of the study 
Figures will be presented for all analytes. 
 
 
 
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Research Protocol No CUD-P4-001 | Sponsor Project No COL MIG-113| Version FINAL 3.2 | 2017/10/25 
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Figure X: Individual Logarithmic Profile of Lasmiditan in Plasma 
 
 The figure does not reflect the actual data of the study. 
 
Figures will be presented for all analytes. 
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Research Protocol No CUD-P4-001 | Sponsor Project No COL MIG-113| Version FINAL 3.2 | 2017/10/25 
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Figure 1: Linear Profile of the Mean of Lasmiditan in Urine 
 
 
The figure does not reflect the actual data of the study. 
Figures will be presented for all analytes. 
 
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Research Protocol No CUD-P4-001 | Sponsor Project No COL MIG-113| Version FINAL 3.2 | 2017/10/25 
59 
 
Figure 2: Logarithmic Profile of the Mean of Lasmiditan in Urine 
 
 
The figure does not reflect the actual data of the study. 
Figures will be presented for all analytes. 
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Research Protocol No CUD-P4-001 | Sponsor Project No COL MIG-113| Version FINAL 3.2 | 2017/10/25 
60 
 
Figures 2+1 to (2+1)+N: Individual Linear Profile of the Mean of Lasmiditan in Urine 
 
The figure does not reflect the actual data of the study 
Figures will be presented for all analytes. 
 
 
 
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Research Protocol No CUD-P4-001 | Sponsor Project No COL MIG-113| Version FINAL 3.2 | 2017/10/25 
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Figure N: Individual Logarithmic Profile of the Mean of Lasmiditan in Urine 
 
 The figure does not reflect the actual data of the study 
Figures will be presented for all analytes. 
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Research Protocol No CUD-P4-001 | Sponsor Project No COL MIG-113| Version FINAL 3.2 | 2017/10/25 
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Figure N: Individual Elimination Profiles 
 
The figure does not reflect the actual data of the study. 


 
Research Protocol No CUD-P4-001 | Sponsor Project No COL MIG-113| Version FINAL 3.2 | 2017/10/25 
63 
In Text Figure: 
Figure 1: Linear Regression of ln-Transformed Cmax vs eGFR (Lasmiditan) 
 
The figure does not reflect the actual data of the study. Same graph will be presented for AUC(0-tlast) ,AUC(0-∞)  and CL/F. 
 
 
 


 
Research Protocol No CUD-P4-001 | Sponsor Project No COL MIG-113| Version FINAL 3.2 | 2017/10/25 
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APPENDIX E 
LISTING SHELLS  
 
 


 
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CoLucid Pharmaceuticals, Inc. 
Algorithme Pharma 
Project #  COL MIG-113/CUD-P4-001 
     Page 1 of x 
 
Listing 16.2.1 
Listing of Study Disposition 
 
 
Subject ID 
Date of Completion or 
Discontinuation 
Subject Status 
Specify 
AE # 
Date of Death 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
  
 
 
 
 
 
 
Date: VERSION – YYYY-MM-DD 
Data Source: XXXX 
Program Source:  XXXXX.sas 
 
 
 


 
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CoLucid Pharmaceuticals, Inc. 
Algorithme Pharma 
Project #  COL MIG-113/CUD-P4-001 
     Page 1 of x 
 
Listing 16.2.2.1 
Listing of PK Blood Sampling Time Deviations 
 
 
Group 
 Elapsed 
Time (h) 
 Subject ID 
Scheduled 
Date/Time 
Actual 
Date/Time 
Deviation (min) 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
  
 
 
 
 
 
 
 
 
 
Date: VERSION – YYYY-MM-DD 
Data Source: XXXX 
Program Source:  XXXXX.sas 
 
Similar Listing: Listing 16.2.2.2 Listing of PK Urine Sampling Time Deviations 
 
 


 
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CoLucid Pharmaceuticals, Inc. 
Algorithme Pharma 
Project #  COL MIG-113/CUD-P4-001 
     Page 1 of x 
Listing 16.2.3 
Listing of Analysis Populations 
 
Subject ID 
Safety 
Population PK Population  Reason if Excluded from one Population 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
  
 
 
 
 
 
 
Date: VERSION – YYYY-MM-DD 
Data Source: XXXX 
Program Source:  XXXXX.sas 
 
 
 


 
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CoLucid Pharmaceuticals, Inc. 
Algorithme Pharma 
Project #  COL MIG-113/CUD-P4-001 
     Page 1 of x 
 
Listing 16.2.4.1 
Listing of Demographic Characteristics 
 
 
Subject ID 
Age Date of Birth Gender 
Ethnicity Race 
Other Race  
 
Weight (kg)  
Height (cm) 
BMI (kg/m2) 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
  
 
 
 
 
 
 
 
 
 
 
 
 
 
Date: VERSION – YYYY-MM-DD 
Data Source: XXXX 
Program Source:  XXXXX.sas 
 
 
 


 
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CoLucid Pharmaceuticals, Inc. 
Algorithme Pharma 
Project #  COL MIG-113/CUD-P4-001 
     Page 1 of x 
 
Listing 16.2.4.2 
Listing of Screen Failures 
 
 
Subject ID 
Date 
 
Specify Primary Reason 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
  
 
 
 
 
 
Date: VERSION – YYYY-MM-DD 
Data Source: XXXX 
Program Source:  XXXXX.sas 
 
 


 
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CoLucid Pharmaceuticals, Inc. 
Algorithme Pharma 
Project #  COL MIG-113/CUD-P4-001 
     Page 1 of x 
 
Listing 16.2.5 
Listing of Investigational Product Administration 
 
 
 
 
Subject ID 
Visit 
Start 
Date/Time 
 
Treatment 
Dose 
Administered (mg) 
Route 
 
If Any Dosing Issues, 
Specify 
  
 
 
 
 
 
 
 
 
 
  
 
 
 
 
 
 
 
  
  
 
 
 
 
 
 
 
 
 
  
 
 
 
 
 
 
 
 
 
  
 
 
 
 
 
 
 
 
 
  
 
 
 
 
 
 
 
 
 
  
 
 
 
 
 
 
 
 
 
  
 
 
 
 
 
 
 
 
 
  
 
 
 
 
 
 
 
 
 
  
 
 
 
 
 
 
 
 
 
  
 
 
 
 
 
 
 
 
 
  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
  
  
 
 
 
 
 
 
 
 
  
 
 
Date: VERSION – YYYY-MM-DD 
Data Source: XXXX 
Program Source:  XXXXX.sas 
 
 
 


 
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CoLucid Pharmaceuticals, Inc. 
Algorithme Pharma 
Project #  COL MIG-113/CUD-P4-001 
     Page 1 of x 
 
Listing 16.2.7  
Listing of Adverse Events 
 
 
Subject ID 
Visit/ 
Group/ 
AE # 
SOC 
  MedDRA 
Preferred Term 
    Description 
of AE 
Onset Date  
Time 
(Time since 
Last Dose) 
Resolution 
Date Time 
(Duration) 
I: Maximal 
Severity 
R: Causality 
Assessment 
O: Outcome 
S: Serious AE 
D: AE Leading To 
Discontinuation 
Action Taken With 
Study Treatment / 
Other Action(s) Taken 
/ Concomitant Given 
 
 
 
  
  
 
 
 
 
 
xxx 
xxxxx 
xxxxx 
xxxxxxxxxxxx 
  xxxxxxxxxxxx 
     
xxxxxxxxxxxx 
YYYY-MM-DD/ 
HH:MM 
(DD:HH:MM) 
YYYY-MM-DD/ 
HH:MM 
(DD:HH:MM) 
xxxxxx 
xxxxx 
xxxxxx 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
  
 
  
 
 
 
 
 
 
 
 
 
 


 
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CoLucid Pharmaceuticals, Inc. 
Algorithme Pharma 
Project #  COL MIG-113/CUD-P4-001 
     Page 1 of x 
 
Listing 16.2.8.1 
Listing of Blood Chemistry 
 
 
Subject ID 
Lab Test Name (Units) 
Reference Range 
Visit 
Date / Time   Value 
 
Out-of-Range 
Flag 
Assessment 
[1] 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
  
 
 
 
 
 
 
 
 
 
 
[1] NCS: Not Clinically Significant   /   CS: Clinically Significant   /   RPT: Repeated   /  TBC: To Be Controlled. 
 
Date: VERSION – YYYY-MM-DD 
Data Source: XXXX 
Program Source:  XXXXX.sas 
 
 
 


 
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Similar listing(s): 
 
L16.2.8.2 
 
Listing of Hematology 
L16.2.8.3 
 
Listing of Urinalysis 
L16.2.8.4 
 
Listing of Urine Drug Screen 
L16.2.8.5 
 
Listing of Pregnancy Test 
L16.2.8.5 
 
Listing of Serology  
 
  
 
 
 
 


 
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CoLucid Pharmaceuticals, Inc. 
Algorithme Pharma 
Project #  COL MIG-113/CUD-P4-001 
     Page 1 of x 
 
Listing 16.2.9.1 
Listing of Alcohol Habits 
 
 
Subject ID 
Intake Status 
Quantity 
Frequency 
Start Date 
End Date 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
  
 
 
 
 
 
 
 
 
Date: VERSION – YYYY-MM-DD 
Data Source: XXXX 
Program Source:  XXXXX.sas 
 
 
 


 
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CoLucid Pharmaceuticals, Inc. 
Algorithme Pharma 
Project #  COL MIG-113/CUD-P4-001 
     Page 1 of x 
 
Listing 16.2.9.2 
Listing of Smoking Habits 
 
 
Subject ID 
Intake Status 
Quantity 
Frequency 
Start Date 
End Date 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
  
 
 
 
 
 
 
 
 
Date: VERSION – YYYY-MM-DD 
Data Source: XXXX 
Program Source:  XXXXX.sas 
 
 
 
 
 


 
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CoLucid Pharmaceuticals, Inc. 
Algorithme Pharma 
Project #  COL MIG-113/CUD-P4-001 
     Page 1 of x 
 
Listing 16.2.9.3 
Listing of Prior Medication  
 
 
Subject ID 
#CM  
Related to 
AE#/MH# 
ATC / 
PT / 
Medication 
Name 
Indication 
Dose 
(unit) 
Frequency Formulation 
Total 
Daily 
Dose 
Route 
Start 
Date/ 
Time 
End  
Date/ 
Time 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Date: VERSION – YYYY-MM-DD 
Data Source: XXXX 
Program Source:  XXXXX.sas 
 
Similar Listing:  
 
Listing 16.2.9.4 Listing of Concomitant Medication 
 
 


 
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CoLucid Pharmaceuticals, Inc. 
Algorithme Pharma 
Project #  COL MIG-113/CUD-P4-001 
     Page 1 of x 
 
Listing 16.2.9.5 
Listing of Physical Examination 
 
 
Subject ID 
Visit  
 Date / Time 
 Body System Examined 
Result  (Abnormal Findings) 
 
 
 
 
 
 
 
 
 
  
 
 
 
 
 
  
 
 
 
 
 
  
 
 
 
 
 
  
 
 
 
 
 
  
 
 
 
 
 
  
 
 
 
 
 
  
 
 
 
 
 
  
 
 
 
 
 
  
 
 
 
 
 
  
 
 
 
 
 
  
 
 
 
  
 
 
 
 
 
 
 
 
Date: VERSION – YYYY-MM-DD 
Data Source: XXXX 
Program Source:  XXXXX.sas 
 
 
 


 
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CoLucid Pharmaceuticals, Inc. 
Algorithme Pharma 
Project #  COL MIG-113/CUD-P4-001 
     Page 1 of x 
 
Listing 16.2.9.6 
Listing of Vital Signs  
 
 
Subject ID 
Visit 
 
 
Elapsed Time 
 
Position 
Date / Time 
 
Assessment 
(Units)  
Value  
Safety 
Review  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
  
 
 
 
 
 
 
 
 
 
 
 
Date: VERSION – YYYY-MM-DD 
Data Source: XXXX 
Program Source:  XXXXX.sas 
 
 
 


 
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Algorithme Pharma 
Project #  COL MIG-113/CUD-P4-001 
     Page 1 of x 
 
Listing 16.2.9.7 
Listing of ECG Assessments 
 
 
Subject ID 
Visit 
Time Point 
 Date / Time 
Position 
Safety Review Parameter (Unit) Value 
 
 
 
 
 
 
 
 
 
xxxxx 
xxxxxx 
 
 YYYY-MM-DD: HH:MM 
xxxxxx 
xxxxxx 
 
 
 
 
 
  
 
 
 
 
 
 
 
 YYYY-MM-DD: HH:MM 
xxxxxx 
xxxxxx 
 
 
 
 
 
 YYYY-MM-DD: HH:MM 
xxxxxx 
xxxxxx 
 
 
 
 
 
  
 
 
 
 
 
 
 
  
 
 
 
 
xxxxx 
xxxxxx 
 
 YYYY-MM-DD: HH:MM 
xxxxxx 
xxxxxx 
 
 
 
 
 
  
 
 
 
 
xxxxx 
xxxxxx 
 
 YYYY-MM-DD: HH:MM 
xxxxxx 
xxxxxx 
 
 
 
 
 
  
 
 
 
 
 
 
 
  
 
 
 
 
 
 
 
  
 
 
 
 
 
 
 
  
 
 
 
 
 
 
 
  
 
 
 
 
 
 
 
  
 
 
 
 
 
 
 
  
 
 
 
 
 
 
 
  
 
 
 
 
  
 
 
 
 
 
 
 
 
 
 
 
Date: VERSION – YYYY-MM-DD 
Data Source: XXXX 
Program Source:  XXXXX.sas 
 
 
 
 
 
 


 
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Algorithme Pharma 
Project #  COL MIG-113/CUD-P4-001 
     Page 1 of x 
 
Listing 16.2.9.8 
Listing of Inclusion/Exclusion Criteria Summary 
 
 
Subject ID 
Has the participant met all 
screening eligibility criteria? 
Inclusion/Exclusion 
Failed Criterion Number 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
  
 
 
 
 
 
Date: VERSION – YYYY-MM-DD 
Data Source: XXXX 
Program Source:  XXXXX.sas 
 
 
 


 
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CoLucid Pharmaceuticals, Inc. 
Algorithme Pharma 
Project #  COL MIG-113/CUD-P4-001 
     Page 1 of x 
 
Listing 16.2.9.9 
Listing of Medical History 
 
 
Subject ID 
MH # System Organ Class 
MedDRA Preferred Term 
Description of Medical 
History 
Start Date 
End Date 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
          
 
Date: VERSION – YYYY-MM-DD 
Data Source: XXXX 
Program Source:  XXXXX.sas 
 
 


 
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CoLucid Pharmaceuticals, Inc. 
CONFIDENTIAL 
Project #  COL MIG-113/CUD-P4-001 
     Page 1 of x 
 
Listing 16.2.9.10 
Listing of Columbia-Suicide Severity Rating Scale (C-SSRS) 
 
 
Subject ID 
Visit 
Category 
Question 
Answer 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Date: VERSION – YYYY-MM-DD 
Data Source: XXXX 
Program Source:  XXXXX.sas 
 
 


 
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contact@altasciences.com 
altasciences.com 
 
 
10103 Metcalf Ave. 
Overland Park, KS 66212
United States
913 696-1601
vinceandassociates.com 
575 Armand-Frappier Blvd.
Laval, Quebec 
Canada H7V 4B3
450 973-6077
algopharm.com 
4837 Amber Valley Parkway
Fargo, ND 58104
United States
701 551-3737 
algopharm.com 


Clinical Study Report  
Project No COL MIG-113/H8H-CD-LAHN 
 
16.1.9.2 Documentation of statistical analysis – SAS® output of Lasmiditan 
 
Legend:  
AUCinf= AUC(0−∞) 
AUCT=AUC(0-tlast) 
Vz_F= VZ/F 
CL_F= CL/F 
LambdaZ = λZ 
lCmax= ln(Cmax) 
lAUCT= ln(AUC(0-tlast)) 
lAUCinf= ln(AUC(0−∞)) 
lCLF= ln(CL/F) 
lLambdaZ = ln(λZ) 
lVz_F= ln(VZ/F) 
RkTmax= Rank of Tmax 


11:18 Monday, February 12, 2018
1
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - Lasmiditan
(Healthy vs Severe)
ANOVA analysis
RAW DATA
--------------------- SUMMARY REPORT ---------------------
11:18 Monday, February 12, 2018
1
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - Lasmiditan
(Healthy vs Severe)
ANOVA analysis
RAW DATA
--------------------- SUMMARY REPORT ---------------------
Renal Function Group=Normal
Obs Subject
Cmax
Tmax
AUCT
Thalf
Ae
fe
CLr
Vz_F
Cl_F
AUCinf
Res_Area
 1 101
288.00000 2.00000 1742.02000 5.05210 4.46677 2.23338 2564.12957
832.41956 114.20774 1751.19483
0.52392
 2 102
303.00000 3.00000 2269.41500 5.89140 6.98788 3.49394 3079.15256
741.32912
87.22046 2293.04005
1.03029
 3 103
514.00000 1.25000 2253.80500 3.57464 7.23717 3.61858 3211.08792
455.15651
88.25795 2266.08474
0.54189
 4 104
326.00000 2.50000 1829.20892 3.54085 3.12512 1.56256 1708.45439
552.42749 108.14168 1849.42566
1.09314
 5 105
126.00000 1.00000
618.34750 3.51372 2.74783 1.37392 4443.82811 1623.58102 320.28197
624.44976
0.97722
 6 106
276.00000 2.50000 1514.40000 3.02245 4.12476 2.06238 2723.68991
572.82872 131.36837 1522.43647
0.52787
 7 107
173.00000 3.00000 1327.93883 4.05010 4.73839 2.36919 3568.22610
863.25825 147.74065 1353.72355
1.90473
 8 108
232.00000 2.50000 1955.87600 5.89271 5.64905 2.82453 2888.24547
859.21551 101.06779 1978.86981
1.16197
Obs Lambda_z lnCmax
lnAUCT lnAUCinf
lnAe
lnCLr
lnLambda_z lnCl_F
lnfe
lnVz_F RkTmax
eGFR
CrCL
 1 
0.13720 5.66296 7.46280
7.46805 1.49666 7.84937
-1.98632 4.73802 0.80352 6.72434
8.0 115.00000 163.85000
 2 
0.11765 5.71373 7.72728
7.73763 1.94418 8.03241
-2.14001 4.46844 1.25103 6.60844
14.5 102.00000 152.84000
 3 
0.19391 6.24222 7.72038
7.72581 1.97923 8.07437
-1.64038 4.48026 1.28608 6.12064
5.0
94.00000 100.45000
 4 
0.19576 5.78690 7.51164
7.52263 1.13947 7.44334
-1.63088 4.68344 0.44633 6.31432
10.0 109.00000 124.34000
 5 
0.19727 4.83628 6.42705
6.43687 1.01081 8.39927
-1.62319 5.76920 0.31766 7.39239
3.5 102.00000 155.18000
 6 
0.22933 5.62040 7.32277
7.32807 1.41701 7.90974
-1.47258 4.87801 0.72386 6.35059
10.0 116.00000 120.18000
 7 
0.17114 5.15329 7.19138
7.21061 1.55570 8.17982
-1.76526 4.99546 0.86255 6.76071
14.5
98.00000 116.39000
 8 
0.11763 5.44674 7.57859
7.59028 1.73149 7.96840
-2.14023 4.61579 1.03834 6.75602
10.0 118.00000 147.36000


11:18 Monday, February 12, 2018
2
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - Lasmiditan
(Healthy vs Severe)
ANOVA analysis
RAW DATA
--------------------- SUMMARY REPORT ---------------------
11:18 Monday, February 12, 2018
2
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - Lasmiditan
(Healthy vs Severe)
ANOVA analysis
RAW DATA
--------------------- SUMMARY REPORT ---------------------
Renal Function Group=Severe
Obs Subject
Cmax
Tmax
AUCT
Thalf
Ae
fe
CLr
Vz_F
Cl_F
AUCinf
Res_Area
 9 201
341.00000 0.75000 2224.39000 6.29100 1.96752 0.98376
884.51935 806.25652
88.83396 2251.39127
1.19932
 10 202
163.00000 3.00000 1103.70000 3.41530 1.47176 0.73588 1333.47377 884.24501 179.46073 1114.44994
0.96460
 11 203
235.00000 3.00000 2075.78225 6.68086 3.55816 1.77908 1714.12729 910.20931
94.43528 2117.85268
1.98647
 12 204
294.00000 1.81667 1762.09667 3.32045 0.99397 0.49698
564.08143 539.37588 112.59515 1776.27542
0.79823
 13 205
424.00000 1.75000 3325.83000 6.47006 2.65410 1.32705
798.02636 553.25258
59.27081 3374.34231
1.43768
 14 206
470.00000 0.75000 1825.62167 3.16277 1.13428 0.56714
621.31329 497.02008 108.92594 1836.10995
0.57122
 15 207
263.00000 1.00000 1555.42500 4.26959 2.25069 1.12534 1446.99037 777.65537 126.24861 1584.17584
1.81488
 16 208
269.00000 2.56667 1728.08917 3.55680 1.98568 0.99284 1149.06108 587.07806 114.40937 1748.10852
1.14520
Obs Lambda_z lnCmax
lnAUCT lnAUCinf
lnAe
lnCLr
lnLambda_z lnCl_F
lnfe
lnVz_F RkTmax
eGFR
CrCL
 9 
0.11018 5.83188 7.70724
7.71930
0.67677 6.78504
-2.20563 4.48677 -0.01638 6.69240
1.5 26.00000 40.09000
 10 
0.20295 5.09375 7.00642
7.01612
0.38646 7.19554
-1.59478 5.18996 -0.30669 6.78473
14.5 23.00000 29.51000
 11 
0.10375 5.45959 7.63809
7.65816
1.26924 7.44666
-2.26576 4.54791
0.57609 6.81367
14.5 26.00000 43.68000
 12 
0.20875 5.68358 7.47426
7.48227 -0.00605 6.33520
-1.56661 4.72380 -0.69920 6.29041
7.0 19.00000 30.22000
 13 
0.10713 6.04973 8.10947
8.12396
0.97611 6.68214
-2.23370 4.08212
0.28296 6.31581
6.0 27.00000 26.90000
 14 
0.21916 6.15273 7.50968
7.51540
0.12600 6.43184
-1.51796 4.69067 -0.56715 6.20863
1.5 16.00000 20.27000
 15 
0.16235 5.57215 7.34950
7.36782
0.81123 7.27724
-1.81803 4.83825
0.11809 6.65628
3.5 21.00000 30.33000
 16 
0.19488 5.59471 7.45477
7.46629
0.68596 7.04670
-1.63537 4.73978 -0.00719 6.37516
12.0 28.00000 65.77000


11:18 Monday, February 12, 2018
3
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - Lasmiditan
(Healthy vs Severe)
ANOVA analysis
DESCRIPTIVE RESULTS (OVERALL)
--------------------- SUMMARY REPORT ---------------------
11:18 Monday, February 12, 2018
3
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - Lasmiditan
(Healthy vs Severe)
ANOVA analysis
DESCRIPTIVE RESULTS (OVERALL)
--------------------- SUMMARY REPORT ---------------------
Parameter
Renal
Function
Group
n
Min
Mean
Geometric
Mean
Median
Max
Standard
Deviation
Coefficient
of
Variation
Cmax
Normal
8
126.00000
279.75000
259.25593
282.00000
514.00000 116.46551
41.632
Cmax
Severe
8
163.00000
307.37500
292.88094
281.50000
470.00000 100.62794
32.738
Tmax
Normal
8
1.00000
2.21875
2.08090
2.50000
3.00000
0.74926
33.769
Tmax
Severe
8
0.75000
1.82917
1.59223
1.78333
3.00000
0.94934
51.900
AUCT
Normal
8
618.34750 1688.87641 1584.04463 1785.61446 2269.41500 542.04977
32.095
AUCT
Severe
8 1103.70000 1950.11684 1865.30538 1793.85917 3325.83000 649.83012
33.323
Thalf
Normal
8
3.02245
4.31725
4.19268
3.81237
5.89271
1.13690
26.334
Thalf
Severe
8
3.16277
4.64585
4.42920
3.91320
6.68086
1.55718
33.518
Ae
Normal
8
2.74783
4.88462
4.63816
4.60258
7.23717
1.64654
33.709
Ae
Severe
8
0.99397
2.00202
1.85098
1.97660
3.55816
0.84180
42.048
fe
Normal
8
1.37392
2.44231
2.31908
2.30129
3.61858
0.82327
33.709
fe
Severe
8
0.49698
1.00101
0.92549
0.98830
1.77908
0.42090
42.048
CLr
Normal
8 1708.45439 3023.35175 2928.05019 2983.69901 4443.82811 792.90521
26.226
CLr
Severe
8
564.08143 1063.94912
992.31982 1016.79021 1714.12729 413.70175
38.884
Vz_F
Normal
8
455.15651
812.52702
756.29525
786.87434 1623.58102 362.69776
44.638
Vz_F
Severe
8
497.02008
694.38660
676.63956
682.36672
910.20931 167.54105
24.128
Cl_F
Normal
8
87.22046
137.28583
125.03299
111.17471
320.28197
76.75183
55.907
Cl_F
Severe
8
59.27081
110.52248
105.89071
110.76055
179.46073
34.59494
31.301
AUCinf
Normal
8
624.44976 1704.90311 1599.57784 1800.31024 2293.04005 545.49033
31.995
AUCinf
Severe
8 1114.44994 1975.33824 1888.73988 1806.19268 3374.34231 661.00665
33.463
Res_Area
Normal
8
0.52392
0.97013
0.88165
1.00376
1.90473
0.46401
47.830
Res_Area
Severe
8
0.57122
1.23970
1.15335
1.17226
1.98647
0.48634
39.230
Lambda_z
Normal
8
0.11763
0.16999
0.16532
0.18252
0.22933
0.04151
24.417
Lambda_z
Severe
8
0.10375
0.16364
0.15649
0.17861
0.21916
0.04968
30.360
lnCmax
Normal
8
4.83628
5.55782
5.64168
6.24222
0.42372
7.624
lnCmax
Severe
8
5.09375
5.67977
5.63915
6.15273
0.33688
5.931
lnAUCT
Normal
8
6.42705
7.36774
7.48722
7.72728
0.42187
5.726
lnAUCT
Severe
8
7.00642
7.53118
7.49197
8.10947
0.31504
4.183
lnAUCinf
Normal
8
6.43687
7.37750
7.49534
7.73763
0.42099
5.706
lnAUCinf
Severe
8
7.01612
7.54367
7.49884
8.12396
0.31634
4.193
lnAe
Normal
8
1.01081
1.53432
1.52618
1.97923
0.34855
22.717
lnAe
Severe
8
-0.00605
0.61571
0.68137
1.26924
0.42809
69.528
lnCLr
Normal
8
7.44334
7.98209
8.00041
8.39927
0.27709
3.471
lnCLr
Severe
8
6.33520
6.90005
6.91587
7.44666
0.40512
5.871
lnLambda_z Normal
8
-2.14023
-1.79985
-1.70282
-1.47258
0.25630
-14.240
lnLambda_z Severe
8
-2.26576
-1.85473
-1.72670
-1.51796
0.32714
-17.638
lnCl_F
Normal
8
4.46844
4.82858
4.71073
5.76920
0.42099
8.719
lnCl_F
Severe
8
4.08212
4.66241
4.70723
5.18996
0.31634
6.785
lnfe
Normal
8
0.31766
0.84117
0.83303
1.28608
0.34855
41.436
lnfe
Severe
8
-0.69920
-0.07743
-0.01178
0.57609
0.42809
-552.861
lnVz_F
Normal
8
6.12064
6.62843
6.66639
7.39239
0.38927
5.873
lnVz_F
Severe
8
6.20863
6.51714
6.51572
6.81367
0.24404
3.745
RkTmax
Normal
8
3.50000
9.43750
8.58239
10.00000
14.50000
3.95002
41.855
RkTmax
Severe
8
1.50000
7.56250
5.49765
6.50000
14.50000
5.46049
72.205


11:18 Monday, February 12, 2018
4
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - Lasmiditan
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:18 Monday, February 12, 2018
4
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - Lasmiditan
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=13 Param=lnCmax
 Number of Observations Read 16
 Number of Observations Used 16
Analysis of Variance
Source
DF Sum of
Squares
Mean
Square
F Value Pr > F
 Model 
1 0.07015 0.07015
0.48 0.4992
 Error 
14 2.04054 0.14575
 Corrected Total 15 2.11069
 Root MSE 
0.38178  R-Square 
0.0332
 Dependent Mean 5.61879  Adj R-Sq -0.0358
 Coeff Var 
6.79463    
Parameter Estimates
Variable
Label
DF Parameter
Estimate
Standard
Error
t Value Pr > |t|
95%
Confidence
Limits
 Intercept Intercept
1
5.72061
0.17508
32.67
<.0001
5.34511 6.09611
 eGFR 
eGFR
1
-0.00157
0.00226
-0.69
0.4992 -0.00641 0.00328


11:18 Monday, February 12, 2018
5
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - Lasmiditan
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:18 Monday, February 12, 2018
5
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - Lasmiditan
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=13 Param=lnCmax
Output Statistics
Obs
Dependent
Variable
Predicted
Value
Std Error
Mean Predict
Residual Std Error
Residual
Student
Residual
-2-1 0 1 2
Cook's
D
        1 
5.6630
5.5405
0.1478
0.1225
0.352
0.348  |      |      | 
0.011
        2 
5.7137
5.5608
0.1268
0.1529
0.360
0.425  |      |      | 
0.011
        3 
6.2422
5.5734
0.1157
0.6689
0.364
1.839  |      |***   | 
0.171
        4 
5.7869
5.5499
0.1378
0.2370
0.356
0.666  |      |*     | 
0.033
        5 
4.8363
5.5608
0.1268
-0.7245
0.360
-2.012  |  ****|      | 
0.251
        6 
5.6204
5.5389
0.1496
0.0815
0.351
0.232  |      |      | 
0.005
        7 
5.1533
5.5671
0.1211
-0.4138
0.362
-1.143  |    **|      | 
0.073
        8 
5.4467
5.5358
0.1531
-0.0890
0.350
-0.255  |      |      | 
0.006
        9 
5.8319
5.6799
0.1299
0.1520
0.359
0.423  |      |      | 
0.012
       10 
5.0938
5.6846
0.1346
-0.5908
0.357
-1.654  |   ***|      | 
0.194
       11 
5.4596
5.6799
0.1299
-0.2203
0.359
-0.614  |     *|      | 
0.025
       12 
5.6836
5.6908
0.1411 -0.007270
0.355
-0.0205  |      |      | 
0.000
       13 
6.0497
5.6783
0.1283
0.3714
0.360
1.033  |      |**    | 
0.068
       14 
6.1527
5.6955
0.1461
0.4572
0.353
1.296  |      |**    | 
0.144
       15 
5.5722
5.6877
0.1378
-0.1156
0.356
-0.325  |      |      | 
0.008
       16 
5.5947
5.6768
0.1268
-0.0820
0.360
-0.228  |      |      | 
0.003
 Sum of Residuals 
0
 Sum of Squared Residuals 
2.04054
 Predicted Residual SS (PRESS) 2.59787


11:18 Monday, February 12, 2018
6
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - Lasmiditan
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:18 Monday, February 12, 2018
6
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - Lasmiditan
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=14 Param=lnAUCT
 Number of Observations Read 16
 Number of Observations Used 16
Analysis of Variance
Source
DF Sum of
Squares
Mean
Square
F Value Pr > F
 Model 
1 0.08126 0.08126
0.58 0.4595
 Error 
14 1.96620 0.14044
 Corrected Total 15 2.04746
 Root MSE 
0.37476  R-Square 
0.0397
 Dependent Mean 7.44946  Adj R-Sq -0.0289
 Coeff Var 
5.03067    
Parameter Estimates
Variable
Label
DF Parameter
Estimate
Standard
Error
t Value Pr > |t|
95%
Confidence
Limits
 Intercept Intercept
1
7.55905
0.17186
43.98
<.0001
7.19045 7.92765
 eGFR 
eGFR
1
-0.00169
0.00222
-0.76
0.4595 -0.00644 0.00307


11:18 Monday, February 12, 2018
7
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - Lasmiditan
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:18 Monday, February 12, 2018
7
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - Lasmiditan
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=14 Param=lnAUCT
Output Statistics
Obs
Dependent
Variable
Predicted
Value
Std Error
Mean Predict
Residual Std Error
Residual
Student
Residual
-2-1 0 1 2
Cook's
D
        1 
7.4628
7.3652
0.1451
0.0976
0.346
0.283  |      |      | 
0.007
        2 
7.7273
7.3871
0.1245
0.3402
0.353
0.962  |      |*     | 
0.057
        3 
7.7204
7.4006
0.1136
0.3198
0.357
0.896  |      |*     | 
0.041
        4 
7.5116
7.3753
0.1352
0.1364
0.350
0.390  |      |      | 
0.011
        5 
6.4271
7.3871
0.1245
-0.9600
0.353
-2.716  | *****|      | 
0.458
        6 
7.3228
7.3635
0.1468
-0.0407
0.345
-0.118  |      |      | 
0.001
        7 
7.1914
7.3938
0.1189
-0.2024
0.355
-0.570  |     *|      | 
0.018
        8 
7.5786
7.3601
0.1503
0.2185
0.343
0.636  |      |*     | 
0.039
        9 
7.7072
7.5152
0.1275
0.1920
0.352
0.545  |      |*     | 
0.019
       10 
7.0064
7.5203
0.1321
-0.5138
0.351
-1.465  |    **|      | 
0.152
       11 
7.6381
7.5152
0.1275
0.1229
0.352
0.349  |      |      | 
0.008
       12 
7.4743
7.5270
0.1385
-0.0528
0.348
-0.151  |      |      | 
0.002
       13 
8.1095
7.5135
0.1260
0.5959
0.353
1.688  |      |***   | 
0.182
       14 
7.5097
7.5321
0.1434
-0.0224
0.346
-0.0647  |      |      | 
0.000
       15 
7.3495
7.5236
0.1352
-0.1741
0.350
-0.498  |      |      | 
0.019
       16 
7.4548
7.5118
0.1245
-0.0571
0.353
-0.161  |      |      | 
0.002
 Sum of Residuals 
0
 Sum of Squared Residuals 
1.96620
 Predicted Residual SS (PRESS) 2.50413


11:18 Monday, February 12, 2018
8
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - Lasmiditan
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:18 Monday, February 12, 2018
8
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - Lasmiditan
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=15 Param=lnAUCinf
 Number of Observations Read 16
 Number of Observations Used 16
Analysis of Variance
Source
DF Sum of
Squares
Mean
Square
F Value Pr > F
 Model 
1 0.08438 0.08438
0.60 0.4513
 Error 
14 1.96718 0.14051
 Corrected Total 15 2.05156
 Root MSE 
0.37485  R-Square 
0.0411
 Dependent Mean 7.46058  Adj R-Sq -0.0274
 Coeff Var 
5.02441    
Parameter Estimates
Variable
Label
DF Parameter
Estimate
Standard
Error
t Value Pr > |t|
95%
Confidence
Limits
 Intercept Intercept
1
7.57226
0.17190
44.05
<.0001
7.20357 7.94095
 eGFR 
eGFR
1
-0.00172
0.00222
-0.77
0.4513 -0.00647 0.00304


11:18 Monday, February 12, 2018
9
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - Lasmiditan
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:18 Monday, February 12, 2018
9
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - Lasmiditan
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=15 Param=lnAUCinf
Output Statistics
Obs
Dependent
Variable
Predicted
Value
Std Error
Mean Predict
Residual Std Error
Residual
Student
Residual
-2-1 0 1 2
Cook's
D
        1 
7.4681
7.3747
0.1452
0.0934
0.346
0.270  |      |      | 
0.006
        2 
7.7376
7.3970
0.1245
0.3406
0.354
0.963  |      |*     | 
0.058
        3 
7.7258
7.4108
0.1136
0.3151
0.357
0.882  |      |*     | 
0.039
        4 
7.5226
7.3850
0.1353
0.1376
0.350
0.394  |      |      | 
0.012
        5 
6.4369
7.3970
0.1245
-0.9601
0.354
-2.716  | *****|      | 
0.458
        6 
7.3281
7.3730
0.1469
-0.0449
0.345
-0.130  |      |      | 
0.002
        7 
7.2106
7.4039
0.1189
-0.1933
0.355
-0.544  |     *|      | 
0.017
        8 
7.5903
7.3695
0.1503
0.2208
0.343
0.643  |      |*     | 
0.040
        9 
7.7193
7.5276
0.1275
0.1917
0.352
0.544  |      |*     | 
0.019
       10 
7.0161
7.5327
0.1321
-0.5166
0.351
-1.473  |    **|      | 
0.154
       11 
7.6582
7.5276
0.1275
0.1306
0.352
0.370  |      |      | 
0.009
       12 
7.4823
7.5396
0.1385
-0.0573
0.348
-0.165  |      |      | 
0.002
       13 
8.1240
7.5259
0.1260
0.5981
0.353
1.694  |      |***   | 
0.183
       14 
7.5154
7.5448
0.1435
-0.0294
0.346
-0.0848  |      |      | 
0.001
       15 
7.3678
7.5362
0.1353
-0.1684
0.350
-0.482  |      |      | 
0.017
       16 
7.4663
7.5242
0.1245
-0.0579
0.354
-0.164  |      |      | 
0.002
 Sum of Residuals 
0
 Sum of Squared Residuals 
1.96718
 Predicted Residual SS (PRESS) 2.50586


11:18 Monday, February 12, 2018
10
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - Lasmiditan
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:18 Monday, February 12, 2018
10
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - Lasmiditan
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=16 Param=lnAe
 Number of Observations Read 16
 Number of Observations Used 16
Analysis of Variance
Source
DF Sum of
Squares
Mean
Square
F Value Pr > F
 Model 
1 3.38108 3.38108
22.25 0.0003
 Error 
14 2.12750 0.15196
 Corrected Total 15 5.50858
 Root MSE 
0.38983  R-Square 0.6138
 Dependent Mean 
1.07502  Adj R-Sq 0.5862
 Coeff Var 
36.26232    
Parameter Estimates
Variable
Label
DF Parameter
Estimate
Standard
Error
t Value Pr > |t|
95%
Confidence
Limits
 Intercept Intercept
1
0.36811
0.17877
2.06
0.0586 -0.01531 0.75153
 eGFR 
eGFR
1
0.01088
0.00231
4.72
0.0003
0.00593 0.01582


11:18 Monday, February 12, 2018
11
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - Lasmiditan
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:18 Monday, February 12, 2018
11
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - Lasmiditan
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=16 Param=lnAe
Output Statistics
Obs
Dependent
Variable
Predicted
Value
Std Error
Mean Predict
Residual Std Error
Residual
Student
Residual
-2-1 0 1 2
Cook's
D
        1 
1.4967
1.6188
0.1510
-0.1221
0.359
-0.340  |      |      | 
0.010
        2 
1.9442
1.4774
0.1295
0.4668
0.368
1.269  |      |**    | 
0.100
        3 
1.9792
1.3904
0.1182
0.5888
0.371
1.585  |      |***   | 
0.127
        4 
1.1395
1.5535
0.1407
-0.4141
0.364
-1.139  |    **|      | 
0.097
        5 
1.0108
1.4774
0.1295
-0.4666
0.368
-1.269  |    **|      | 
0.100
        6 
1.4170
1.6297
0.1527
-0.2127
0.359
-0.593  |     *|      | 
0.032
        7 
1.5557
1.4339
0.1236
0.1218
0.370
0.329  |      |      | 
0.006
        8 
1.7315
1.6514
0.1563
0.0801
0.357
0.224  |      |      | 
0.005
        9 
0.6768
0.6509
0.1326
0.0259
0.367
0.0707  |      |      | 
0.000
       10 
0.3865
0.6182
0.1374
-0.2318
0.365
-0.635  |     *|      | 
0.029
       11 
1.2692
0.6509
0.1326
0.6184
0.367
1.687  |      |***   | 
0.186
       12 -0.006052
0.5747
0.1440
-0.5808
0.362
-1.603  |   ***|      | 
0.203
       13 
0.9761
0.6617
0.1311
0.3144
0.367
0.856  |      |*     | 
0.047
       14 
0.1260
0.5421
0.1492
-0.4161
0.360
-1.155  |    **|      | 
0.115
       15 
0.8112
0.5965
0.1407
0.2147
0.364
0.591  |      |*     | 
0.026
       16 
0.6860
0.6726
0.1295
0.0133
0.368
0.0363  |      |      | 
0.000
 Sum of Residuals 
0
 Sum of Squared Residuals 
2.12750
 Predicted Residual SS (PRESS) 2.74548


11:18 Monday, February 12, 2018
12
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - Lasmiditan
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:18 Monday, February 12, 2018
12
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - Lasmiditan
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=17 Param=lnCLr
 Number of Observations Read 16
 Number of Observations Used 16
Analysis of Variance
Source
DF Sum of
Squares
Mean
Square
F Value Pr > F
 Model 
1 4.51067 4.51067
33.97 <.0001
 Error 
14 1.85897 0.13278
 Corrected Total 15 6.36964
 Root MSE 
0.36439  R-Square 0.7082
 Dependent Mean 7.44107  Adj R-Sq 0.6873
 Coeff Var 
4.89707    
Parameter Estimates
Variable
Label
DF Parameter
Estimate
Standard
Error
t Value Pr > |t|
95%
Confidence
Limits
 Intercept Intercept
1
6.62457
0.16711
39.64
<.0001 6.26616 6.98297
 eGFR 
eGFR
1
0.01256
0.00216
5.83
<.0001 0.00794 0.01718


11:18 Monday, February 12, 2018
13
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - Lasmiditan
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:18 Monday, February 12, 2018
13
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - Lasmiditan
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=17 Param=lnCLr
Output Statistics
Obs
Dependent
Variable
Predicted
Value
Std Error
Mean Predict
Residual Std Error
Residual
Student
Residual
-2-1 0 1 2
Cook's
D
        1 
7.8494
8.0691
0.1411
-0.2198
0.336
-0.654  |     *|      | 
0.038
        2 
8.0324
7.9058
0.1211
0.1266
0.344
0.368  |      |      | 
0.008
        3 
8.0744
7.8054
0.1105
0.2690
0.347
0.775  |      |*     | 
0.030
        4 
7.4433
7.9938
0.1315
-0.5504
0.340
-1.620  |   ***|      | 
0.196
        5 
8.3993
7.9058
0.1211
0.4934
0.344
1.436  |      |**    | 
0.128
        6 
7.9097
8.0817
0.1428
-0.1720
0.335
-0.513  |     *|      | 
0.024
        7 
8.1798
7.8556
0.1156
0.3242
0.346
0.938  |      |*     | 
0.049
        8 
7.9684
8.1068
0.1461
-0.1384
0.334
-0.415  |      |      | 
0.016
        9 
6.7850
6.9512
0.1240
-0.1661
0.343
-0.485  |      |      | 
0.015
       10 
7.1955
6.9135
0.1284
0.2821
0.341
0.827  |      |*     | 
0.049
       11 
7.4467
6.9512
0.1240
0.4955
0.343
1.446  |      |**    | 
0.137
       12 
6.3352
6.8632
0.1346
-0.5280
0.339
-1.559  |   ***|      | 
0.192
       13 
6.6821
6.9637
0.1225
-0.2816
0.343
-0.821  |     *|      | 
0.043
       14 
6.4318
6.8256
0.1395
-0.3937
0.337
-1.170  |    **|      | 
0.117
       15 
7.2772
6.8884
0.1315
0.3889
0.340
1.144  |      |**    | 
0.098
       16 
7.0467
6.9763
0.1211
0.0704
0.344
0.205  |      |      | 
0.003
 Sum of Residuals 
0
 Sum of Squared Residuals 
1.85897
 Predicted Residual SS (PRESS) 2.42809


11:18 Monday, February 12, 2018
14
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - Lasmiditan
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:18 Monday, February 12, 2018
14
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - Lasmiditan
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=18 Param=lnLambda_z
 Number of Observations Read 16
 Number of Observations Used 16
Analysis of Variance
Source
DF Sum of
Squares
Mean
Square
F Value Pr > F
 Model 
1 0.00254 0.00254
0.03 0.8668
 Error 
14 1.21849 0.08703
 Corrected Total 15 1.22103
 Root MSE 
0.29502  R-Square 
0.0021
 Dependent Mean 
-1.82729  Adj R-Sq -0.0692
 Coeff Var 
-16.14503    
Parameter Estimates
Variable
Label
DF Parameter
Estimate
Standard
Error
t Value Pr > |t|
95%
Confidence
Limits
 Intercept Intercept
1
-1.84667
0.13529
-13.65
<.0001 -2.13684 -1.55650
 eGFR 
eGFR
1 0.00029809
0.00174
0.17
0.8668 -0.00344
0.00404


11:18 Monday, February 12, 2018
15
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - Lasmiditan
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:18 Monday, February 12, 2018
15
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - Lasmiditan
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=18 Param=lnLambda_z
Output Statistics
Obs
Dependent
Variable
Predicted
Value
Std Error
Mean Predict
Residual Std Error
Residual
Student
Residual
-2-1 0 1 2
Cook's
D
        1 
-1.9863
-1.8124
0.1142
-0.1739
0.272
-0.639  |     *|      | 
0.036
        2 
-2.1400
-1.8163
0.0980
-0.3237
0.278
-1.163  |    **|      | 
0.084
        3 
-1.6404
-1.8186
0.0894
0.1783
0.281
0.634  |      |*     | 
0.020
        4 
-1.6309
-1.8142
0.1065
0.1833
0.275
0.666  |      |*     | 
0.033
        5 
-1.6232
-1.8163
0.0980
0.1931
0.278
0.694  |      |*     | 
0.030
        6 
-1.4726
-1.8121
0.1156
0.3395
0.271
1.251  |      |**    | 
0.142
        7 
-1.7653
-1.8175
0.0936
0.0522
0.280
0.187  |      |      | 
0.002
        8 
-2.1402
-1.8115
0.1183
-0.3287
0.270
-1.216  |    **|      | 
0.142
        9 
-2.2056
-1.8389
0.1004
-0.3667
0.277
-1.322  |    **|      | 
0.114
       10 
-1.5948
-1.8398
0.1040
0.2450
0.276
0.888  |      |*     | 
0.056
       11 
-2.2658
-1.8389
0.1004
-0.4268
0.277
-1.539  |   ***|      | 
0.155
       12 
-1.5666
-1.8410
0.1090
0.2744
0.274
1.001  |      |**    | 
0.079
       13 
-2.2337
-1.8386
0.0992
-0.3951
0.278
-1.422  |    **|      | 
0.129
       14 
-1.5180
-1.8419
0.1129
0.3239
0.273
1.189  |      |**    | 
0.121
       15 
-1.8180
-1.8404
0.1065
0.0224
0.275
0.0813  |      |      | 
0.000
       16 
-1.6354
-1.8383
0.0980
0.2029
0.278
0.729  |      |*     | 
0.033
 Sum of Residuals 
0
 Sum of Squared Residuals 
1.21849
 Predicted Residual SS (PRESS) 1.60139


11:18 Monday, February 12, 2018
16
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - Lasmiditan
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:18 Monday, February 12, 2018
16
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - Lasmiditan
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=19 Param=lnCl_F
 Number of Observations Read 16
 Number of Observations Used 16
Analysis of Variance
Source
DF Sum of
Squares
Mean
Square
F Value Pr > F
 Model 
1 0.08438 0.08438
0.60 0.4513
 Error 
14 1.96718 0.14051
 Corrected Total 15 2.05156
 Root MSE 
0.37485  R-Square 
0.0411
 Dependent Mean 4.74549  Adj R-Sq -0.0274
 Coeff Var 
7.89908    
Parameter Estimates
Variable
Label
DF Parameter
Estimate
Standard
Error
t Value Pr > |t|
95%
Confidence
Limits
 Intercept Intercept
1
4.63381
0.17190
26.96
<.0001
4.26512 5.00250
 eGFR 
eGFR
1
0.00172
0.00222
0.77
0.4513 -0.00304 0.00647


11:18 Monday, February 12, 2018
17
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - Lasmiditan
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:18 Monday, February 12, 2018
17
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - Lasmiditan
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=19 Param=lnCl_F
Output Statistics
Obs
Dependent
Variable
Predicted
Value
Std Error
Mean Predict
Residual Std Error
Residual
Student
Residual
-2-1 0 1 2
Cook's
D
        1 
4.7380
4.8314
0.1452
-0.0934
0.346
-0.270  |      |      | 
0.006
        2 
4.4684
4.8091
0.1245
-0.3406
0.354
-0.963  |     *|      | 
0.058
        3 
4.4803
4.7953
0.1136
-0.3151
0.357
-0.882  |     *|      | 
0.039
        4 
4.6834
4.8211
0.1353
-0.1376
0.350
-0.394  |      |      | 
0.012
        5 
5.7692
4.8091
0.1245
0.9601
0.354
2.716  |      |***** | 
0.458
        6 
4.8780
4.8331
0.1469
0.0449
0.345
0.130  |      |      | 
0.002
        7 
4.9955
4.8022
0.1189
0.1933
0.355
0.544  |      |*     | 
0.017
        8 
4.6158
4.8366
0.1503
-0.2208
0.343
-0.643  |     *|      | 
0.040
        9 
4.4868
4.6785
0.1275
-0.1917
0.352
-0.544  |     *|      | 
0.019
       10 
5.1900
4.6733
0.1321
0.5166
0.351
1.473  |      |**    | 
0.154
       11 
4.5479
4.6785
0.1275
-0.1306
0.352
-0.370  |      |      | 
0.009
       12 
4.7238
4.6665
0.1385
0.0573
0.348
0.165  |      |      | 
0.002
       13 
4.0821
4.6802
0.1260
-0.5981
0.353
-1.694  |   ***|      | 
0.183
       14 
4.6907
4.6613
0.1435
0.0294
0.346
0.0848  |      |      | 
0.001
       15 
4.8383
4.6699
0.1353
0.1684
0.350
0.482  |      |      | 
0.017
       16 
4.7398
4.6819
0.1245
0.0579
0.354
0.164  |      |      | 
0.002
 Sum of Residuals 
0
 Sum of Squared Residuals 
1.96718
 Predicted Residual SS (PRESS) 2.50586


11:18 Monday, February 12, 2018
18
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - Lasmiditan
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:18 Monday, February 12, 2018
18
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - Lasmiditan
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=20 Param=lnfe
 Number of Observations Read 16
 Number of Observations Used 16
Analysis of Variance
Source
DF Sum of
Squares
Mean
Square
F Value Pr > F
 Model 
1 3.38108 3.38108
22.25 0.0003
 Error 
14 2.12750 0.15196
 Corrected Total 15 5.50858
 Root MSE 
0.38983  R-Square 0.6138
 Dependent Mean 
0.38187  Adj R-Sq 0.5862
 Coeff Var 
102.08357    
Parameter Estimates
Variable
Label
DF Parameter
Estimate
Standard
Error
t Value Pr > |t|
95%
Confidence
Limits
 Intercept Intercept
1
-0.32504
0.17877
-1.82
0.0905 -0.70846 0.05838
 eGFR 
eGFR
1
0.01088
0.00231
4.72
0.0003
0.00593 0.01582


11:18 Monday, February 12, 2018
19
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - Lasmiditan
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:18 Monday, February 12, 2018
19
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - Lasmiditan
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=20 Param=lnfe
Output Statistics
Obs
Dependent
Variable
Predicted
Value
Std Error
Mean Predict
Residual Std Error
Residual
Student
Residual
-2-1 0 1 2
Cook's
D
        1 
0.8035
0.9256
0.1510
-0.1221
0.359
-0.340  |      |      | 
0.010
        2 
1.2510
0.7843
0.1295
0.4668
0.368
1.269  |      |**    | 
0.100
        3 
1.2861
0.6973
0.1182
0.5888
0.371
1.585  |      |***   | 
0.127
        4 
0.4463
0.8604
0.1407
-0.4141
0.364
-1.139  |    **|      | 
0.097
        5 
0.3177
0.7843
0.1295
-0.4666
0.368
-1.269  |    **|      | 
0.100
        6 
0.7239
0.9365
0.1527
-0.2127
0.359
-0.593  |     *|      | 
0.032
        7 
0.8625
0.7408
0.1236
0.1218
0.370
0.329  |      |      | 
0.006
        8 
1.0383
0.9583
0.1563
0.0801
0.357
0.224  |      |      | 
0.005
        9 
-0.0164
-0.0423
0.1326
0.0259
0.367
0.0707  |      |      | 
0.000
       10 
-0.3067
-0.0749
0.1374
-0.2318
0.365
-0.635  |     *|      | 
0.029
       11 
0.5761
-0.0423
0.1326
0.6184
0.367
1.687  |      |***   | 
0.186
       12 
-0.6992
-0.1184
0.1440
-0.5808
0.362
-1.603  |   ***|      | 
0.203
       13 
0.2830
-0.0314
0.1311
0.3144
0.367
0.856  |      |*     | 
0.047
       14 
-0.5671
-0.1510
0.1492
-0.4161
0.360
-1.155  |    **|      | 
0.115
       15 
0.1181
-0.0967
0.1407
0.2147
0.364
0.591  |      |*     | 
0.026
       16 -0.007186
-0.0205
0.1295
0.0133
0.368
0.0363  |      |      | 
0.000
 Sum of Residuals 
0
 Sum of Squared Residuals 
2.12750
 Predicted Residual SS (PRESS) 2.74548


11:18 Monday, February 12, 2018
20
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - Lasmiditan
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:18 Monday, February 12, 2018
20
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - Lasmiditan
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=21 Param=lnVz_F
 Number of Observations Read 16
 Number of Observations Used 16
Analysis of Variance
Source
DF Sum of
Squares
Mean
Square
F Value Pr > F
 Model 
1 0.05764 0.05764
0.55 0.4709
 Error 
14 1.46951 0.10497
 Corrected Total 15 1.52716
 Root MSE 
0.32398  R-Square 
0.0377
 Dependent Mean 6.57279  Adj R-Sq -0.0310
 Coeff Var 
4.92916    
Parameter Estimates
Variable
Label
DF Parameter
Estimate
Standard
Error
t Value Pr > |t|
95%
Confidence
Limits
 Intercept Intercept
1
6.48048
0.14857
43.62
<.0001
6.16182 6.79914
 eGFR 
eGFR
1
0.00142
0.00192
0.74
0.4709 -0.00269 0.00553


11:18 Monday, February 12, 2018
21
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - Lasmiditan
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:18 Monday, February 12, 2018
21
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - Lasmiditan
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=21 Param=lnVz_F
Output Statistics
Obs
Dependent
Variable
Predicted
Value
Std Error
Mean Predict
Residual Std Error
Residual
Student
Residual
-2-1 0 1 2
Cook's
D
        1 
6.7243
6.6438
0.1255
0.0805
0.299
0.270  |      |      | 
0.006
        2 
6.6084
6.6253
0.1076
-0.0169
0.306
-0.0552  |      |      | 
0.000
        3 
6.1206
6.6140
0.0982
-0.4933
0.309
-1.598  |   ***|      | 
0.129
        4 
6.3143
6.6353
0.1169
-0.3209
0.302
-1.062  |    **|      | 
0.084
        5 
7.3924
6.6253
0.1076
0.7671
0.306
2.510  |      |***** | 
0.391
        6 
6.3506
6.6452
0.1269
-0.2946
0.298
-0.988  |     *|      | 
0.089
        7 
6.7607
6.6196
0.1028
0.1411
0.307
0.459  |      |      | 
0.012
        8 
6.7560
6.6480
0.1299
0.1080
0.297
0.364  |      |      | 
0.013
        9 
6.6924
6.5174
0.1102
0.1750
0.305
0.574  |      |*     | 
0.022
       10 
6.7847
6.5131
0.1142
0.2716
0.303
0.896  |      |*     | 
0.057
       11 
6.8137
6.5174
0.1102
0.2963
0.305
0.972  |      |*     | 
0.062
       12 
6.2904
6.5075
0.1197
-0.2171
0.301
-0.721  |     *|      | 
0.041
       13 
6.3158
6.5188
0.1089
-0.2030
0.305
-0.665  |     *|      | 
0.028
       14 
6.2086
6.5032
0.1240
-0.2946
0.299
-0.984  |     *|      | 
0.083
       15 
6.6563
6.5103
0.1169
0.1460
0.302
0.483  |      |      | 
0.017
       16 
6.3752
6.5202
0.1076
-0.1451
0.306
-0.475  |      |      | 
0.014
 Sum of Residuals 
0
 Sum of Squared Residuals 
1.46951
 Predicted Residual SS (PRESS) 1.88342


11:18 Monday, February 12, 2018
22
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - Lasmiditan
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:18 Monday, February 12, 2018
22
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - Lasmiditan
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=22 Param=RkTmax
 Number of Observations Read 16
 Number of Observations Used 16
Analysis of Variance
Source
DF
Sum of
Squares
Mean
Square
F Value Pr > F
 Model 
1
17.88375 17.88375
0.80 0.3871
 Error 
14 314.11625 22.43687
 Corrected Total 15 332.00000
 Root MSE 
4.73676  R-Square 
0.0539
 Dependent Mean 
8.50000  Adj R-Sq -0.0137
 Coeff Var 
55.72656    
Parameter Estimates
Variable
Label
DF Parameter
Estimate
Standard
Error
t Value Pr > |t|
95%
Confidence
Limits
 Intercept Intercept
1
6.87420
2.17220
3.16
0.0069
2.21529 11.53312
 eGFR 
eGFR
1
0.02501
0.02802
0.89
0.3871 -0.03508
0.08510


11:18 Monday, February 12, 2018
23
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - Lasmiditan
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:18 Monday, February 12, 2018
23
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - Lasmiditan
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=22 Param=RkTmax
Output Statistics
Obs
Dependent
Variable
Predicted
Value
Std Error
Mean Predict
Residual Std Error
Residual
Student
Residual
-2-1 0 1 2
Cook's
D
        1 
8.0000
9.7506
1.8343
-1.7506
4.367
-0.401  |      |      | 
0.014
        2 
14.5000
9.4255
1.5738
5.0745
4.468
1.136  |      |**    | 
0.080
        3 
5.0000
9.2254
1.4361
-4.2254
4.514
-0.936  |     *|      | 
0.044
        4 
10.0000
9.6005
1.7093
0.3995
4.418
0.0904  |      |      | 
0.001
        5 
3.5000
9.4255
1.5738
-5.9255
4.468
-1.326  |    **|      | 
0.109
        6 
10.0000
9.7756
1.8557
0.2244
4.358
0.0515  |      |      | 
0.000
        7 
14.5000
9.3254
1.5023
5.1746
4.492
1.152  |      |**    | 
0.074
        8 
10.0000
9.8256
1.8992
0.1744
4.339
0.0402  |      |      | 
0.000
        9 
1.5000
7.5245
1.6112
-6.0245
4.454
-1.353  |    **|      | 
0.120
       10 
14.5000
7.4495
1.6694
7.0505
4.433
1.591  |      |***   | 
0.179
       11 
14.5000
7.5245
1.6112
6.9755
4.454
1.566  |      |***   | 
0.160
       12 
7.0000
7.3494
1.7502
-0.3494
4.402
-0.0794  |      |      | 
0.000
       13 
6.0000
7.5495
1.5924
-1.5495
4.461
-0.347  |      |      | 
0.008
       14 
1.5000
7.2744
1.8130
-5.7744
4.376
-1.320  |    **|      | 
0.149
       15 
3.5000
7.3995
1.7093
-3.8995
4.418
-0.883  |     *|      | 
0.058
       16 
12.0000
7.5745
1.5738
4.4255
4.468
0.991  |      |*     | 
0.061
 Sum of Residuals 
0
 Sum of Squared Residuals 
314.11625
 Predicted Residual SS (PRESS) 403.50373


11:18 Monday, February 12, 2018
24
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - Lasmiditan
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:18 Monday, February 12, 2018
24
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - Lasmiditan
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=13 Param=lnCmax
 Number of Observations Read 16
 Number of Observations Used 16
Analysis of Variance
Source
DF Sum of
Squares
Mean
Square
F Value Pr > F
 Model 
1 0.17464 0.17464
1.26 0.2800
 Error 
14 1.93605 0.13829
 Corrected Total 15 2.11069
 Root MSE 
0.37187  R-Square 0.0827
 Dependent Mean 5.61879  Adj R-Sq 0.0172
 Coeff Var 
6.61837    
Parameter Estimates
Variable
Label
DF Parameter
Estimate
Standard
Error
t Value Pr > |t|
95%
Confidence
Limits
 Intercept Intercept
1
5.78834
0.17722
32.66
<.0001
5.40824 6.16844
 CrCL 
CrCL
1
-0.00198
0.00177
-1.12
0.2800 -0.00577 0.00180


11:18 Monday, February 12, 2018
25
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - Lasmiditan
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:18 Monday, February 12, 2018
25
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - Lasmiditan
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=13 Param=lnCmax
Output Statistics
Obs
Dependent
Variable
Predicted
Value
Std Error
Mean Predict
Residual Std Error
Residual
Student
Residual
-2-1 0 1 2
Cook's
D
        1 
5.6630
5.4633
0.1667
0.1997
0.332
0.601  |      |*     | 
0.045
        2 
5.7137
5.4851
0.1510
0.2286
0.340
0.673  |      |*     | 
0.045
        3 
6.2422
5.5891
0.0967
0.6532
0.359
1.819  |      |***   | 
0.120
        4 
5.7869
5.5417
0.1156
0.2452
0.353
0.694  |      |*     | 
0.026
        5 
4.8363
5.4805
0.1543
-0.6442
0.338
-1.904  |   ***|      | 
0.377
        6 
5.6204
5.5499
0.1114
0.0705
0.355
0.199  |      |      | 
0.002
        7 
5.1533
5.5574
0.1078
-0.4041
0.356
-1.136  |    **|      | 
0.059
        8 
5.4467
5.4960
0.1435
-0.0492
0.343
-0.144  |      |      | 
0.002
        9 
5.8319
5.7088
0.1227
0.1231
0.351
0.351  |      |      | 
0.008
       10 
5.0938
5.7298
0.1356
-0.6360
0.346
-1.837  |   ***|      | 
0.259
       11 
5.4596
5.7017
0.1187
-0.2421
0.352
-0.687  |     *|      | 
0.027
       12 
5.6836
5.7284
0.1347
-0.0448
0.347
-0.129  |      |      | 
0.001
       13 
6.0497
5.7350
0.1390
0.3148
0.345
0.913  |      |*     | 
0.068
       14 
6.1527
5.7481
0.1479
0.4046
0.341
1.186  |      |**    | 
0.132
       15 
5.5722
5.7282
0.1346
-0.1560
0.347
-0.450  |      |      | 
0.015
       16 
5.5947
5.6579
0.0993
-0.0631
0.358
-0.176  |      |      | 
0.001
 Sum of Residuals 
0
 Sum of Squared Residuals 
1.93605
 Predicted Residual SS (PRESS) 2.54565


11:18 Monday, February 12, 2018
26
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - Lasmiditan
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:18 Monday, February 12, 2018
26
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - Lasmiditan
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=14 Param=lnAUCT
 Number of Observations Read 16
 Number of Observations Used 16
Analysis of Variance
Source
DF Sum of
Squares
Mean
Square
F Value Pr > F
 Model 
1 0.15435 0.15435
1.14 0.3034
 Error 
14 1.89311 0.13522
 Corrected Total 15 2.04746
 Root MSE 
0.36773  R-Square 0.0754
 Dependent Mean 7.44946  Adj R-Sq 0.0093
 Coeff Var 
4.93627    
Parameter Estimates
Variable
Label
DF Parameter
Estimate
Standard
Error
t Value Pr > |t|
95%
Confidence
Limits
 Intercept Intercept
1
7.60886
0.17524
43.42
<.0001
7.23300 7.98472
 CrCL 
CrCL
1
-0.00187
0.00175
-1.07
0.3034 -0.00561 0.00188


11:18 Monday, February 12, 2018
27
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - Lasmiditan
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:18 Monday, February 12, 2018
27
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - Lasmiditan
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=14 Param=lnAUCT
Output Statistics
Obs
Dependent
Variable
Predicted
Value
Std Error
Mean Predict
Residual Std Error
Residual
Student
Residual
-2-1 0 1 2
Cook's
D
        1 
7.4628
7.3032
0.1649
0.1596
0.329
0.485  |      |      | 
0.030
        2 
7.7273
7.3238
0.1493
0.4035
0.336
1.201  |      |**    | 
0.142
        3 
7.7204
7.4215
0.0956
0.2989
0.355
0.842  |      |*     | 
0.026
        4 
7.5116
7.3769
0.1143
0.1347
0.350
0.385  |      |      | 
0.008
        5 
6.4271
7.3194
0.1525
-0.8924
0.335
-2.667  | *****|      | 
0.739
        6 
7.3228
7.3847
0.1101
-0.0619
0.351
-0.176  |      |      | 
0.002
        7 
7.1914
7.3918
0.1066
-0.2004
0.352
-0.569  |     *|      | 
0.015
        8 
7.5786
7.3340
0.1419
0.2446
0.339
0.721  |      |*     | 
0.045
        9 
7.7072
7.5341
0.1213
0.1732
0.347
0.499  |      |      | 
0.015
       10 
7.0064
7.5538
0.1341
-0.5474
0.342
-1.599  |   ***|      | 
0.196
       11 
7.6381
7.5274
0.1174
0.1107
0.348
0.318  |      |      | 
0.006
       12 
7.4743
7.5525
0.1332
-0.0782
0.343
-0.228  |      |      | 
0.004
       13 
8.1095
7.5587
0.1375
0.5508
0.341
1.615  |      |***   | 
0.212
       14 
7.5097
7.5711
0.1463
-0.0614
0.337
-0.182  |      |      | 
0.003
       15 
7.3495
7.5523
0.1331
-0.2028
0.343
-0.592  |     *|      | 
0.026
       16 
7.4548
7.4862
0.0981
-0.0314
0.354
-0.0886  |      |      | 
0.000
 Sum of Residuals 
0
 Sum of Squared Residuals 
1.89311
 Predicted Residual SS (PRESS) 2.62564


11:18 Monday, February 12, 2018
28
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - Lasmiditan
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:18 Monday, February 12, 2018
28
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - Lasmiditan
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=15 Param=lnAUCinf
 Number of Observations Read 16
 Number of Observations Used 16
Analysis of Variance
Source
DF Sum of
Squares
Mean
Square
F Value Pr > F
 Model 
1 0.15820 0.15820
1.17 0.2977
 Error 
14 1.89336 0.13524
 Corrected Total 15 2.05156
 Root MSE 
0.36775  R-Square 0.0771
 Dependent Mean 7.46058  Adj R-Sq 0.0112
 Coeff Var 
4.92925    
Parameter Estimates
Variable
Label
DF Parameter
Estimate
Standard
Error
t Value Pr > |t|
95%
Confidence
Limits
 Intercept Intercept
1
7.62195
0.17526
43.49
<.0001
7.24607 7.99784
 CrCL 
CrCL
1
-0.00189
0.00175
-1.08
0.2977 -0.00563 0.00186


11:18 Monday, February 12, 2018
29
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - Lasmiditan
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:18 Monday, February 12, 2018
29
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - Lasmiditan
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=15 Param=lnAUCinf
Output Statistics
Obs
Dependent
Variable
Predicted
Value
Std Error
Mean Predict
Residual Std Error
Residual
Student
Residual
-2-1 0 1 2
Cook's
D
        1 
7.4681
7.3126
0.1649
0.1555
0.329
0.473  |      |      | 
0.028
        2 
7.7376
7.3333
0.1493
0.4043
0.336
1.203  |      |**    | 
0.143
        3 
7.7258
7.4323
0.0956
0.2935
0.355
0.827  |      |*     | 
0.025
        4 
7.5226
7.3872
0.1143
0.1355
0.350
0.388  |      |      | 
0.008
        5 
6.4369
7.3289
0.1525
-0.8921
0.335
-2.666  | *****|      | 
0.738
        6 
7.3281
7.3950
0.1101
-0.0670
0.351
-0.191  |      |      | 
0.002
        7 
7.2106
7.4022
0.1066
-0.1916
0.352
-0.544  |     *|      | 
0.014
        8 
7.5903
7.3437
0.1419
0.2466
0.339
0.727  |      |*     | 
0.046
        9 
7.7193
7.5463
0.1214
0.1731
0.347
0.498  |      |      | 
0.015
       10 
7.0161
7.5662
0.1341
-0.5501
0.342
-1.607  |   ***|      | 
0.198
       11 
7.6582
7.5395
0.1174
0.1187
0.349
0.341  |      |      | 
0.007
       12 
7.4823
7.5649
0.1332
-0.0826
0.343
-0.241  |      |      | 
0.004
       13 
8.1240
7.5712
0.1375
0.5528
0.341
1.621  |      |***   | 
0.213
       14 
7.5154
7.5837
0.1463
-0.0683
0.337
-0.202  |      |      | 
0.004
       15 
7.3678
7.5647
0.1331
-0.1969
0.343
-0.574  |     *|      | 
0.025
       16 
7.4663
7.4978
0.0982
-0.0315
0.354
-0.0888  |      |      | 
0.000
 Sum of Residuals 
0
 Sum of Squared Residuals 
1.89336
 Predicted Residual SS (PRESS) 2.62664


11:18 Monday, February 12, 2018
30
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - Lasmiditan
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:18 Monday, February 12, 2018
30
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - Lasmiditan
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=16 Param=lnAe
 Number of Observations Read 16
 Number of Observations Used 16
Analysis of Variance
Source
DF Sum of
Squares
Mean
Square
F Value Pr > F
 Model 
1 3.06285 3.06285
17.53 0.0009
 Error 
14 2.44572 0.17469
 Corrected Total 15 5.50858
 Root MSE 
0.41796  R-Square 0.5560
 Dependent Mean 
1.07502  Adj R-Sq 0.5243
 Coeff Var 
38.87985    
Parameter Estimates
Variable
Label
DF Parameter
Estimate
Standard
Error
t Value Pr > |t|
95%
Confidence
Limits
 Intercept Intercept
1
0.36496
0.19919
1.83
0.0883 -0.06225 0.79217
 CrCL 
CrCL
1
0.00831
0.00198
4.19
0.0009
0.00405 0.01256


11:18 Monday, February 12, 2018
31
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - Lasmiditan
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:18 Monday, February 12, 2018
31
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - Lasmiditan
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=16 Param=lnAe
Output Statistics
Obs
Dependent
Variable
Predicted
Value
Std Error
Mean Predict
Residual Std Error
Residual
Student
Residual
-2-1 0 1 2
Cook's
D
        1 
1.4967
1.7263
0.1874
-0.2297
0.374
-0.615  |     *|      | 
0.048
        2 
1.9442
1.6349
0.1697
0.3093
0.382
0.810  |      |*     | 
0.065
        3 
1.9792
1.1996
0.1086
0.7797
0.404
1.932  |      |***   | 
0.135
        4 
1.1395
1.3981
0.1299
-0.2586
0.397
-0.651  |     *|      | 
0.023
        5 
1.0108
1.6543
0.1734
-0.6435
0.380
-1.692  |   ***|      | 
0.297
        6 
1.4170
1.3635
0.1252
0.0535
0.399
0.134  |      |      | 
0.001
        7 
1.5557
1.3320
0.1212
0.2237
0.400
0.559  |      |*     | 
0.014
        8 
1.7315
1.5893
0.1613
0.1422
0.386
0.369  |      |      | 
0.012
        9 
0.6768
0.6981
0.1379
-0.0213
0.395
-0.0539  |      |      | 
0.000
       10 
0.3865
0.6101
0.1525
-0.2237
0.389
-0.575  |     *|      | 
0.025
       11 
1.2692
0.7279
0.1334
0.5414
0.396
1.367  |      |**    | 
0.106
       12 -0.006052
0.6160
0.1514
-0.6221
0.390
-1.597  |   ***|      | 
0.193
       13 
0.9761
0.5885
0.1563
0.3876
0.388
1.000  |      |*     | 
0.081
       14 
0.1260
0.5334
0.1663
-0.4074
0.383
-1.062  |    **|      | 
0.106
       15 
0.8112
0.6170
0.1513
0.1943
0.390
0.499  |      |      | 
0.019
       16 
0.6860
0.9114
0.1116
-0.2255
0.403
-0.560  |     *|      | 
0.012
 Sum of Residuals 
0
 Sum of Squared Residuals 
2.44572
 Predicted Residual SS (PRESS) 3.18542


11:18 Monday, February 12, 2018
32
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - Lasmiditan
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:18 Monday, February 12, 2018
32
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - Lasmiditan
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=17 Param=lnCLr
 Number of Observations Read 16
 Number of Observations Used 16
Analysis of Variance
Source
DF Sum of
Squares
Mean
Square
F Value Pr > F
 Model 
1 4.59236 4.59236
36.18 <.0001
 Error 
14 1.77728 0.12695
 Corrected Total 15 6.36964
 Root MSE 
0.35630  R-Square 0.7210
 Dependent Mean 7.44107  Adj R-Sq 0.7010
 Coeff Var 
4.78827    
Parameter Estimates
Variable
Label
DF Parameter
Estimate
Standard
Error
t Value Pr > |t|
95%
Confidence
Limits
 Intercept Intercept
1
6.57162
0.16980
38.70
<.0001 6.20744 6.93580
 CrCL 
CrCL
1
0.01017
0.00169
6.01
<.0001 0.00655 0.01380


11:18 Monday, February 12, 2018
33
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - Lasmiditan
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:18 Monday, February 12, 2018
33
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - Lasmiditan
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=17 Param=lnCLr
Output Statistics
Obs
Dependent
Variable
Predicted
Value
Std Error
Mean Predict
Residual Std Error
Residual
Student
Residual
-2-1 0 1 2
Cook's
D
        1 
7.8494
8.2386
0.1597
-0.3892
0.318
-1.222  |    **|      | 
0.188
        2 
8.0324
8.1266
0.1447
-0.0942
0.326
-0.289  |      |      | 
0.008
        3 
8.0744
7.5936
0.0926
0.4808
0.344
1.397  |      |**    | 
0.071
        4 
7.4433
7.8366
0.1107
-0.3933
0.339
-1.161  |    **|      | 
0.072
        5 
8.3993
8.1504
0.1478
0.2489
0.324
0.768  |      |*     | 
0.061
        6 
7.9097
7.7943
0.1067
0.1154
0.340
0.340  |      |      | 
0.006
        7 
8.1798
7.7557
0.1033
0.4241
0.341
1.244  |      |**    | 
0.071
        8 
7.9684
8.0708
0.1375
-0.1024
0.329
-0.312  |      |      | 
0.008
        9 
6.7850
6.9795
0.1176
-0.1944
0.336
-0.578  |     *|      | 
0.020
       10 
7.1955
6.8718
0.1300
0.3237
0.332
0.976  |      |*     | 
0.073
       11 
7.4467
7.0160
0.1137
0.4307
0.338
1.275  |      |**    | 
0.092
       12 
6.3352
6.8791
0.1291
-0.5439
0.332
-1.638  |   ***|      | 
0.203
       13 
6.6821
6.8453
0.1332
-0.1631
0.330
-0.494  |      |      | 
0.020
       14 
6.4318
6.7778
0.1418
-0.3460
0.327
-1.058  |    **|      | 
0.105
       15 
7.2772
6.8802
0.1290
0.3971
0.332
1.195  |      |**    | 
0.108
       16 
7.0467
7.2407
0.0951
-0.1940
0.343
-0.565  |     *|      | 
0.012
 Sum of Residuals 
0
 Sum of Squared Residuals 
1.77728
 Predicted Residual SS (PRESS) 2.30693


11:18 Monday, February 12, 2018
34
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - Lasmiditan
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:18 Monday, February 12, 2018
34
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - Lasmiditan
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=18 Param=lnLambda_z
 Number of Observations Read 16
 Number of Observations Used 16
Analysis of Variance
Source
DF
Sum of
Squares
Mean
Square
F Value Pr > F
 Model 
1 0.00097722 0.00097722
0.01 0.9172
 Error 
14
1.22005
0.08715
 Corrected Total 15
1.22103
 Root MSE 
0.29521  R-Square 
0.0008
 Dependent Mean 
-1.82729  Adj R-Sq -0.0706
 Coeff Var 
-16.15538    
Parameter Estimates
Variable
Label
DF
Parameter
Estimate
Standard
Error
t Value Pr > |t|
95%
Confidence
Limits
 Intercept Intercept
1
-1.81461
0.14068
-12.90
<.0001 -2.11635 -1.51287
 CrCL 
CrCL
1 -0.00014841
0.00140
-0.11
0.9172 -0.00315
0.00286


11:18 Monday, February 12, 2018
35
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - Lasmiditan
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:18 Monday, February 12, 2018
35
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - Lasmiditan
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=18 Param=lnLambda_z
Output Statistics
Obs
Dependent
Variable
Predicted
Value
Std Error
Mean Predict
Residual Std Error
Residual
Student
Residual
-2-1 0 1 2
Cook's
D
        1 
-1.9863
-1.8389
0.1324
-0.1474
0.264
-0.559  |     *|      | 
0.039
        2 
-2.1400
-1.8373
0.1199
-0.3027
0.270
-1.122  |    **|      | 
0.124
        3 
-1.6404
-1.8295
0.0767
0.1891
0.285
0.664  |      |*     | 
0.016
        4 
-1.6309
-1.8331
0.0917
0.2022
0.281
0.721  |      |*     | 
0.028
        5 
-1.6232
-1.8376
0.1225
0.2145
0.269
0.798  |      |*     | 
0.066
        6 
-1.4726
-1.8324
0.0884
0.3599
0.282
1.278  |      |**    | 
0.080
        7 
-1.7653
-1.8319
0.0856
0.0666
0.283
0.236  |      |      | 
0.003
        8 
-2.1402
-1.8365
0.1139
-0.3037
0.272
-1.115  |    **|      | 
0.109
        9 
-2.2056
-1.8206
0.0974
-0.3851
0.279
-1.382  |    **|      | 
0.117
       10 
-1.5948
-1.8190
0.1077
0.2242
0.275
0.816  |      |*     | 
0.051
       11 
-2.2658
-1.8211
0.0942
-0.4447
0.280
-1.589  |   ***|      | 
0.143
       12 
-1.5666
-1.8191
0.1070
0.2525
0.275
0.918  |      |*     | 
0.064
       13 
-2.2337
-1.8186
0.1104
-0.4151
0.274
-1.516  |   ***|      | 
0.187
       14 
-1.5180
-1.8176
0.1174
0.2997
0.271
1.106  |      |**    | 
0.115
       15 
-1.8180
-1.8191
0.1068 0.001081
0.275
0.00393  |      |      | 
0.000
       16 
-1.6354
-1.8244
0.0788
0.1890
0.284
0.664  |      |*     | 
0.017
 Sum of Residuals 
0
 Sum of Squared Residuals 
1.22005
 Predicted Residual SS (PRESS) 1.59686


11:18 Monday, February 12, 2018
36
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - Lasmiditan
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:18 Monday, February 12, 2018
36
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - Lasmiditan
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=19 Param=lnCl_F
 Number of Observations Read 16
 Number of Observations Used 16
Analysis of Variance
Source
DF Sum of
Squares
Mean
Square
F Value Pr > F
 Model 
1 0.15820 0.15820
1.17 0.2977
 Error 
14 1.89336 0.13524
 Corrected Total 15 2.05156
 Root MSE 
0.36775  R-Square 0.0771
 Dependent Mean 4.74549  Adj R-Sq 0.0112
 Coeff Var 
7.74947    
Parameter Estimates
Variable
Label
DF Parameter
Estimate
Standard
Error
t Value Pr > |t|
95%
Confidence
Limits
 Intercept Intercept
1
4.58412
0.17526
26.16
<.0001
4.20824 4.96001
 CrCL 
CrCL
1
0.00189
0.00175
1.08
0.2977 -0.00186 0.00563


11:18 Monday, February 12, 2018
37
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - Lasmiditan
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:18 Monday, February 12, 2018
37
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - Lasmiditan
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=19 Param=lnCl_F
Output Statistics
Obs
Dependent
Variable
Predicted
Value
Std Error
Mean Predict
Residual Std Error
Residual
Student
Residual
-2-1 0 1 2
Cook's
D
        1 
4.7380
4.8935
0.1649
-0.1555
0.329
-0.473  |      |      | 
0.028
        2 
4.4684
4.8727
0.1493
-0.4043
0.336
-1.203  |    **|      | 
0.143
        3 
4.4803
4.7738
0.0956
-0.2935
0.355
-0.827  |     *|      | 
0.025
        4 
4.6834
4.8189
0.1143
-0.1355
0.350
-0.388  |      |      | 
0.008
        5 
5.7692
4.8771
0.1525
0.8921
0.335
2.666  |      |***** | 
0.738
        6 
4.8780
4.8111
0.1101
0.0670
0.351
0.191  |      |      | 
0.002
        7 
4.9955
4.8039
0.1066
0.1916
0.352
0.544  |      |*     | 
0.014
        8 
4.6158
4.8624
0.1419
-0.2466
0.339
-0.727  |     *|      | 
0.046
        9 
4.4868
4.6598
0.1214
-0.1731
0.347
-0.498  |      |      | 
0.015
       10 
5.1900
4.6398
0.1341
0.5501
0.342
1.607  |      |***   | 
0.198
       11 
4.5479
4.6666
0.1174
-0.1187
0.349
-0.341  |      |      | 
0.007
       12 
4.7238
4.6412
0.1332
0.0826
0.343
0.241  |      |      | 
0.004
       13 
4.0821
4.6349
0.1375
-0.5528
0.341
-1.621  |   ***|      | 
0.213
       14 
4.6907
4.6224
0.1463
0.0683
0.337
0.202  |      |      | 
0.004
       15 
4.8383
4.6414
0.1331
0.1969
0.343
0.574  |      |*     | 
0.025
       16 
4.7398
4.7083
0.0982
0.0315
0.354
0.0888  |      |      | 
0.000
 Sum of Residuals 
0
 Sum of Squared Residuals 
1.89336
 Predicted Residual SS (PRESS) 2.62664


11:18 Monday, February 12, 2018
38
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - Lasmiditan
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:18 Monday, February 12, 2018
38
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - Lasmiditan
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=20 Param=lnfe
 Number of Observations Read 16
 Number of Observations Used 16
Analysis of Variance
Source
DF Sum of
Squares
Mean
Square
F Value Pr > F
 Model 
1 3.06285 3.06285
17.53 0.0009
 Error 
14 2.44572 0.17469
 Corrected Total 15 5.50858
 Root MSE 
0.41796  R-Square 0.5560
 Dependent Mean 
0.38187  Adj R-Sq 0.5243
 Coeff Var 
109.45229    
Parameter Estimates
Variable
Label
DF Parameter
Estimate
Standard
Error
t Value Pr > |t|
95%
Confidence
Limits
 Intercept Intercept
1
-0.32818
0.19919
-1.65
0.1217 -0.75540 0.09903
 CrCL 
CrCL
1
0.00831
0.00198
4.19
0.0009
0.00405 0.01256


11:18 Monday, February 12, 2018
39
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - Lasmiditan
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:18 Monday, February 12, 2018
39
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - Lasmiditan
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=20 Param=lnfe
Output Statistics
Obs
Dependent
Variable
Predicted
Value
Std Error
Mean Predict
Residual Std Error
Residual
Student
Residual
-2-1 0 1 2
Cook's
D
        1 
0.8035
1.0332
0.1874
-0.2297
0.374
-0.615  |     *|      | 
0.048
        2 
1.2510
0.9417
0.1697
0.3093
0.382
0.810  |      |*     | 
0.065
        3 
1.2861
0.5064
0.1086
0.7797
0.404
1.932  |      |***   | 
0.135
        4 
0.4463
0.7049
0.1299
-0.2586
0.397
-0.651  |     *|      | 
0.023
        5 
0.3177
0.9611
0.1734
-0.6435
0.380
-1.692  |   ***|      | 
0.297
        6 
0.7239
0.6703
0.1252
0.0535
0.399
0.134  |      |      | 
0.001
        7 
0.8625
0.6389
0.1212
0.2237
0.400
0.559  |      |*     | 
0.014
        8 
1.0383
0.8962
0.1613
0.1422
0.386
0.369  |      |      | 
0.012
        9 
-0.0164
0.004908
0.1379
-0.0213
0.395
-0.0539  |      |      | 
0.000
       10 
-0.3067
-0.0830
0.1525
-0.2237
0.389
-0.575  |     *|      | 
0.025
       11 
0.5761
0.0347
0.1334
0.5414
0.396
1.367  |      |**    | 
0.106
       12 
-0.6992
-0.0771
0.1514
-0.6221
0.390
-1.597  |   ***|      | 
0.193
       13 
0.2830
-0.1047
0.1563
0.3876
0.388
1.000  |      |*     | 
0.081
       14 
-0.5671
-0.1598
0.1663
-0.4074
0.383
-1.062  |    **|      | 
0.106
       15 
0.1181
-0.0762
0.1513
0.1943
0.390
0.499  |      |      | 
0.019
       16 -0.007186
0.2183
0.1116
-0.2255
0.403
-0.560  |     *|      | 
0.012
 Sum of Residuals 
0
 Sum of Squared Residuals 
2.44572
 Predicted Residual SS (PRESS) 3.18542


11:18 Monday, February 12, 2018
40
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - Lasmiditan
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:18 Monday, February 12, 2018
40
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - Lasmiditan
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=21 Param=lnVz_F
 Number of Observations Read 16
 Number of Observations Used 16
Analysis of Variance
Source
DF Sum of
Squares
Mean
Square
F Value Pr > F
 Model 
1 0.18404 0.18404
1.92 0.1877
 Error 
14 1.34312 0.09594
 Corrected Total 15 1.52716
 Root MSE 
0.30974  R-Square 0.1205
 Dependent Mean 6.57279  Adj R-Sq 0.0577
 Coeff Var 
4.71241    
Parameter Estimates
Variable
Label
DF Parameter
Estimate
Standard
Error
t Value Pr > |t|
95%
Confidence
Limits
 Intercept Intercept
1
6.39873
0.14761
43.35
<.0001
6.08214 6.71532
 CrCL 
CrCL
1
0.00204
0.00147
1.39
0.1877 -0.00112 0.00519


11:18 Monday, February 12, 2018
41
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - Lasmiditan
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:18 Monday, February 12, 2018
41
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - Lasmiditan
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=21 Param=lnVz_F
Output Statistics
Obs
Dependent
Variable
Predicted
Value
Std Error
Mean Predict
Residual Std Error
Residual
Student
Residual
-2-1 0 1 2
Cook's
D
        1 
6.7243
6.7324
0.1389 -0.008103
0.277
-0.0293  |      |      | 
0.000
        2 
6.6084
6.7100
0.1257
-0.1016
0.283
-0.359  |      |      | 
0.013
        3 
6.1206
6.6033
0.0805
-0.4827
0.299
-1.614  |   ***|      | 
0.094
        4 
6.3143
6.6520
0.0963
-0.3376
0.294
-1.147  |    **|      | 
0.070
        5 
7.3924
6.7148
0.1285
0.6776
0.282
2.404  |      |****  | 
0.601
        6 
6.3506
6.6435
0.0928
-0.2929
0.296
-0.991  |     *|      | 
0.048
        7 
6.7607
6.6358
0.0898
0.1249
0.296
0.421  |      |      | 
0.008
        8 
6.7560
6.6989
0.1195
0.0572
0.286
0.200  |      |      | 
0.003
        9 
6.6924
6.4804
0.1022
0.2120
0.292
0.725  |      |*     | 
0.032
       10 
6.7847
6.4588
0.1130
0.3259
0.288
1.130  |      |**    | 
0.098
       11 
6.8137
6.4877
0.0988
0.3260
0.294
1.111  |      |**    | 
0.070
       12 
6.2904
6.4603
0.1122
-0.1699
0.289
-0.588  |     *|      | 
0.026
       13 
6.3158
6.4535
0.1158
-0.1377
0.287
-0.479  |      |      | 
0.019
       14 
6.2086
6.4400
0.1232
-0.2314
0.284
-0.814  |     *|      | 
0.062
       15 
6.6563
6.4605
0.1121
0.1958
0.289
0.678  |      |*     | 
0.035
       16 
6.3752
6.5327
0.0827
-0.1575
0.299
-0.528  |     *|      | 
0.011
 Sum of Residuals 
0
 Sum of Squared Residuals 
1.34312
 Predicted Residual SS (PRESS) 1.76761


11:18 Monday, February 12, 2018
42
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - Lasmiditan
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:18 Monday, February 12, 2018
42
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - Lasmiditan
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=22 Param=RkTmax
 Number of Observations Read 16
 Number of Observations Used 16
Analysis of Variance
Source
DF
Sum of
Squares
Mean
Square
F Value Pr > F
 Model 
1
21.48686 21.48686
0.97 0.3417
 Error 
14 310.51314 22.17951
 Corrected Total 15 332.00000
 Root MSE 
4.70951  R-Square 
0.0647
 Dependent Mean 
8.50000  Adj R-Sq -0.0021
 Coeff Var 
55.40603    
Parameter Estimates
Variable
Label
DF Parameter
Estimate
Standard
Error
t Value Pr > |t|
95%
Confidence
Limits
 Intercept Intercept
1
6.61932
2.24437
2.95
0.0106
1.80563 11.43301
 CrCL 
CrCL
1
0.02201
0.02236
0.98
0.3417 -0.02595
0.06996


11:18 Monday, February 12, 2018
43
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - Lasmiditan
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:18 Monday, February 12, 2018
43
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - Lasmiditan
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=22 Param=RkTmax
Output Statistics
Obs
Dependent
Variable
Predicted
Value
Std Error
Mean Predict
Residual Std Error
Residual
Student
Residual
-2-1 0 1 2
Cook's
D
        1 
8.0000
10.2251
2.1114
-2.2251
4.210
-0.529  |     *|      | 
0.035
        2 
14.5000
9.9828
1.9120
4.5172
4.304
1.050  |      |**    | 
0.109
        3 
5.0000
8.8299
1.2242
-3.8299
4.548
-0.842  |     *|      | 
0.026
        4 
10.0000
9.3556
1.4635
0.6444
4.476
0.144  |      |      | 
0.001
        5 
3.5000
10.0343
1.9535
-6.5343
4.285
-1.525  |   ***|      | 
0.242
        6 
10.0000
9.2641
1.4103
0.7359
4.493
0.164  |      |      | 
0.001
        7 
14.5000
9.1807
1.3655
5.3193
4.507
1.180  |      |**    | 
0.064
        8 
10.0000
9.8622
1.8170
0.1378
4.345
0.0317  |      |      | 
0.000
        9 
1.5000
7.5016
1.5541
-6.0016
4.446
-1.350  |    **|      | 
0.111
       10 
14.5000
7.2687
1.7179
7.2313
4.385
1.649  |      |***   | 
0.209
       11 
14.5000
7.5806
1.5029
6.9194
4.463
1.550  |      |***   | 
0.136
       12 
7.0000
7.2844
1.7064
-0.2844
4.390
-0.0648  |      |      | 
0.000
       13 
6.0000
7.2113
1.7608
-1.2113
4.368
-0.277  |      |      | 
0.006
       14 
1.5000
7.0654
1.8737
-5.5654
4.321
-1.288  |    **|      | 
0.156
       15 
3.5000
7.2868
1.7046
-3.7868
4.390
-0.863  |     *|      | 
0.056
       16 
12.0000
8.0667
1.2570
3.9333
4.539
0.867  |      |*     | 
0.029
 Sum of Residuals 
0
 Sum of Squared Residuals 
310.51314
 Predicted Residual SS (PRESS) 408.10127


11:18 Monday, February 12, 2018
44
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - Lasmiditan
(Healthy vs Severe)
ANOVA analysis
NON-PARAMETRIC TEST OF FIXED EFFECT for Tmax parameter
--------------------- SUMMARY REPORT ---------------------
The NPAR1WAY Procedure
11:18 Monday, February 12, 2018
44
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - Lasmiditan
(Healthy vs Severe)
ANOVA analysis
NON-PARAMETRIC TEST OF FIXED EFFECT for Tmax parameter
--------------------- SUMMARY REPORT ---------------------
The NPAR1WAY Procedure
Wilcoxon Scores (Rank Sums) for Variable Value
Classified by Variable Group
Group
N
Sum of
Scores
Expected
Under H0
Std Dev
Under H0
Mean
Score
 1 
8
75.50
68.0 9.409215 9.43750
 2 
8
60.50
68.0 9.409215 7.56250
Average scores were used for ties.
Wilcoxon Two-Sample Test
 Statistic 
75.5000
   
 Normal Approximation 
 Z 
0.7440
 One-Sided Pr >  Z 
0.2285
 Two-Sided Pr > |Z| 
0.4569
   
 t Approximation 
 One-Sided Pr >  Z 
0.2342
 Two-Sided Pr > |Z| 
0.4684
Z includes a continuity correction of 0.5.
Kruskal-Wallis Test
 Chi-Square 
0.6354
 DF 
1
 Pr > Chi-Square 
0.4254
Hodges-Lehmann Estimation
Location Shift (1 - 2)    0.3417
Type
90%
Confidence
Limits
Interval
Midpoint
Asymptotic
Standard Error
 Asymptotic (Moses) -0.5000 1.2500
0.3750
0.5320
 Exact 
-0.5000 1.2500
0.3750


10:06 Monday, January 22, 2018
1
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - Lasmiditan - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
RAW DATA
--------------------- SUMMARY REPORT ---------------------
10:06 Monday, January 22, 2018
1
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - Lasmiditan - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
RAW DATA
--------------------- SUMMARY REPORT ---------------------
Renal Function Group=Normal
Obs Subject
Cmax
Tmax
AUCT
Thalf
AUCinf
Ae
CLr
Lambda_z
Cl_F
Vz_F
fe
 1 101
288.00000 2.00000 1742.02000 5.05210 1751.19483 4.46677 2564.12957
0.13720 114.20774
832.41956 2.23338
 2 102
303.00000 3.00000 2269.41500 5.89140 2293.04005 6.98788 3079.15256
0.11765
87.22046
741.32912 3.49394
 3 103
514.00000 1.25000 2253.80500 3.57464 2266.08474 7.23717 3211.08792
0.19391
88.25795
455.15651 3.61858
 4 104
326.00000 2.50000 1829.20892 3.54085 1849.42566 3.12512 1708.45439
0.19576 108.14168
552.42749 1.56256
 5 105
126.00000 1.00000
618.34750 3.51372
624.44976 2.74783 4443.82811
0.19727 320.28197 1623.58102 1.37392
 6 106
276.00000 2.50000 1514.40000 3.02245 1522.43647 4.12476 2723.68991
0.22933 131.36837
572.82872 2.06238
 7 107
173.00000 3.00000 1327.93883 4.05010 1353.72355 4.73839 3568.22610
0.17114 147.74065
863.25825 2.36919
 8 108
232.00000 2.50000 1955.87600 5.89271 1978.86981 5.64905 2888.24547
0.11763 101.06779
859.21551 2.82453
Obs lnCmax
lnAUCT lnAUCinf
lnAe
lnCLr
lnLambda_z lnCl_F
lnfe
lnVz_F RkTmax
eGFR
CrCL
 1 5.66296 7.46280
7.46805 1.49666 7.84937
-1.98632 4.73802 0.80352 6.72434
8.0 115.00000 163.85000
 2 5.71373 7.72728
7.73763 1.94418 8.03241
-2.14001 4.46844 1.25103 6.60844
14.5 102.00000 152.84000
 3 6.24222 7.72038
7.72581 1.97923 8.07437
-1.64038 4.48026 1.28608 6.12064
5.0
94.00000 100.45000
 4 5.78690 7.51164
7.52263 1.13947 7.44334
-1.63088 4.68344 0.44633 6.31432
10.0 109.00000 124.34000
 5 4.83628 6.42705
6.43687 1.01081 8.39927
-1.62319 5.76920 0.31766 7.39239
3.5 102.00000 155.18000
 6 5.62040 7.32277
7.32807 1.41701 7.90974
-1.47258 4.87801 0.72386 6.35059
10.0 116.00000 120.18000
 7 5.15329 7.19138
7.21061 1.55570 8.17982
-1.76526 4.99546 0.86255 6.76071
14.5
98.00000 116.39000
 8 5.44674 7.57859
7.59028 1.73149 7.96840
-2.14023 4.61579 1.03834 6.75602
10.0 118.00000 147.36000


10:06 Monday, January 22, 2018
2
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - Lasmiditan - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
RAW DATA
--------------------- SUMMARY REPORT ---------------------
10:06 Monday, January 22, 2018
2
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - Lasmiditan - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
RAW DATA
--------------------- SUMMARY REPORT ---------------------
Renal Function Group=Severe
Obs Subject
Cmax
Tmax
AUCT
Thalf
AUCinf
Ae
CLr
Lambda_z
Cl_F
Vz_F
fe
 9 013-01
163.00000 3.00000 1103.70000 3.41530 1114.44994 1.47176 1333.47377
0.20295 179.46073 884.24501 0.73588
 10 013-02
424.00000 1.75000 3325.83000 6.47006 3374.34231 2.65410
798.02636
0.10713
59.27081 553.25258 1.32705
 11 013-03
235.00000 3.00000 2075.78225 6.68086 2117.85268 3.55816 1714.12729
0.10375
94.43528 910.20931 1.77908
 12 013-04
269.00000 2.56667 1728.08917 3.55680 1748.10852 1.98568 1149.06108
0.19488 114.40937 587.07806 0.99284
 13 013-05
470.00000 0.75000 1825.62167 3.16277 1836.10995 1.13428
621.31329
0.21916 108.92594 497.02008 0.56714
 14 013-06
341.00000 0.75000 2224.39000 6.29100 2251.39127 1.96752
884.51935
0.11018
88.83396 806.25652 0.98376
 15 013-07
294.00000 1.81667 1762.09667 3.32045 1776.27542 0.99397
564.08143
0.20875 112.59515 539.37588 0.49698
 16 013-08
263.00000 1.00000 1555.42500 4.26959 1584.17584 2.25069 1446.99037
0.16235 126.24861 777.65537 1.12534
Obs
lnCmax
lnAUCT lnAUCinf
lnAe
lnCLr
lnLambda_z lnCl_F
lnfe
lnVz_F RkTmax
eGFR
CrCL
 9 5.09375 7.00642
7.01612
0.38646 7.19554
-1.59478 5.18996 -0.30669 6.78473
14.5 23.00000 29.51000
 10 6.04973 8.10947
8.12396
0.97611 6.68214
-2.23370 4.08212
0.28296 6.31581
6.0 27.00000 26.90000
 11 5.45959 7.63809
7.65816
1.26924 7.44666
-2.26576 4.54791
0.57609 6.81367
14.5 26.00000 43.68000
 12 5.59471 7.45477
7.46629
0.68596 7.04670
-1.63537 4.73978 -0.00719 6.37516
12.0 28.00000 65.77000
 13 6.15273 7.50968
7.51540
0.12600 6.43184
-1.51796 4.69067 -0.56715 6.20863
1.5 16.00000 20.27000
 14 5.83188 7.70724
7.71930
0.67677 6.78504
-2.20563 4.48677 -0.01638 6.69240
1.5 26.00000 40.09000
 15 5.68358 7.47426
7.48227 -0.00605 6.33520
-1.56661 4.72380 -0.69920 6.29041
7.0 19.00000 30.22000
 16 5.57215 7.34950
7.36782
0.81123 7.27724
-1.81803 4.83825
0.11809 6.65628
3.5 21.00000 30.33000


10:06 Monday, January 22, 2018
3
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - Lasmiditan - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
DESCRIPTIVE RESULTS (OVERALL)
--------------------- SUMMARY REPORT ---------------------
10:06 Monday, January 22, 2018
3
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - Lasmiditan - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
DESCRIPTIVE RESULTS (OVERALL)
--------------------- SUMMARY REPORT ---------------------
Parameter
Renal
Function
Group
n
Min
Mean
Geometric
Mean
Median
Max
Standard
Deviation
Coefficient
of
Variation
Cmax
Normal
8
126.00000
279.75000
259.25593
282.00000
514.00000 116.46551
41.632
Cmax
Severe
8
163.00000
307.37500
292.88094
281.50000
470.00000 100.62794
32.738
Tmax
Normal
8
1.00000
2.21875
2.08090
2.50000
3.00000
0.74926
33.769
Tmax
Severe
8
0.75000
1.82917
1.59223
1.78333
3.00000
0.94934
51.900
AUCT
Normal
8
618.34750 1688.87641 1584.04463 1785.61446 2269.41500 542.04977
32.095
AUCT
Severe
8 1103.70000 1950.11684 1865.30538 1793.85917 3325.83000 649.83012
33.323
Thalf
Normal
8
3.02245
4.31725
4.19268
3.81237
5.89271
1.13690
26.334
Thalf
Severe
8
3.16277
4.64585
4.42920
3.91320
6.68086
1.55718
33.518
AUCinf
Normal
8
624.44976 1704.90311 1599.57784 1800.31024 2293.04005 545.49033
31.995
AUCinf
Severe
8 1114.44994 1975.33824 1888.73988 1806.19268 3374.34231 661.00665
33.463
Ae
Normal
8
2.74783
4.88462
4.63816
4.60258
7.23717
1.64654
33.709
Ae
Severe
8
0.99397
2.00202
1.85098
1.97660
3.55816
0.84180
42.048
CLr
Normal
8 1708.45439 3023.35175 2928.05019 2983.69901 4443.82811 792.90521
26.226
CLr
Severe
8
564.08143 1063.94912
992.31982 1016.79021 1714.12729 413.70175
38.884
Lambda_z
Normal
8
0.11763
0.16999
0.16532
0.18252
0.22933
0.04151
24.417
Lambda_z
Severe
8
0.10375
0.16364
0.15649
0.17861
0.21916
0.04968
30.360
Cl_F
Normal
8
87.22046
137.28583
125.03299
111.17471
320.28197
76.75183
55.907
Cl_F
Severe
8
59.27081
110.52248
105.89071
110.76055
179.46073
34.59494
31.301
Vz_F
Normal
8
455.15651
812.52702
756.29525
786.87434 1623.58102 362.69776
44.638
Vz_F
Severe
8
497.02008
694.38660
676.63956
682.36672
910.20931 167.54105
24.128
fe
Normal
8
1.37392
2.44231
2.31908
2.30129
3.61858
0.82327
33.709
fe
Severe
8
0.49698
1.00101
0.92549
0.98830
1.77908
0.42090
42.048
lnCmax
Normal
8
4.83628
5.55782
5.64168
6.24222
0.42372
7.624
lnCmax
Severe
8
5.09375
5.67977
5.63915
6.15273
0.33688
5.931
lnAUCT
Normal
8
6.42705
7.36774
7.48722
7.72728
0.42187
5.726
lnAUCT
Severe
8
7.00642
7.53118
7.49197
8.10947
0.31504
4.183
lnAUCinf
Normal
8
6.43687
7.37750
7.49534
7.73763
0.42099
5.706
lnAUCinf
Severe
8
7.01612
7.54367
7.49884
8.12396
0.31634
4.193
lnAe
Normal
8
1.01081
1.53432
1.52618
1.97923
0.34855
22.717
lnAe
Severe
8
-0.00605
0.61571
0.68137
1.26924
0.42809
69.528
lnCLr
Normal
8
7.44334
7.98209
8.00041
8.39927
0.27709
3.471
lnCLr
Severe
8
6.33520
6.90005
6.91587
7.44666
0.40512
5.871
lnLambda_z Normal
8
-2.14023
-1.79985
-1.70282
-1.47258
0.25630
-14.240
lnLambda_z Severe
8
-2.26576
-1.85473
-1.72670
-1.51796
0.32714
-17.638
lnCl_F
Normal
8
4.46844
4.82858
4.71073
5.76920
0.42099
8.719
lnCl_F
Severe
8
4.08212
4.66241
4.70723
5.18996
0.31634
6.785
lnfe
Normal
8
0.31766
0.84117
0.83303
1.28608
0.34855
41.436
lnfe
Severe
8
-0.69920
-0.07743
-0.01178
0.57609
0.42809
-552.861
lnVz_F
Normal
8
6.12064
6.62843
6.66639
7.39239
0.38927
5.873
lnVz_F
Severe
8
6.20863
6.51714
6.51572
6.81367
0.24404
3.745
RkTmax
Normal
8
3.50000
9.43750
8.58239
10.00000
14.50000
3.95002
41.855
RkTmax
Severe
8
1.50000
7.56250
5.49765
6.50000
14.50000
5.46049
72.205


10:06 Monday, January 22, 2018
4
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - Lasmiditan - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
--------------------- SUMMARY REPORT ---------------------
The Mixed Procedure
10:06 Monday, January 22, 2018
4
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - Lasmiditan - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
--------------------- SUMMARY REPORT ---------------------
The Mixed Procedure
Order=1 Param=Cmax
Model Information
 Data Set 
WORK.KINDATA
 Dependent Variable 
Value
 Covariance Structure 
Variance Components
 Group Effect 
FunctionGroup
 Estimation Method 
REML
 Residual Variance Method 
None
 Fixed Effects SE Method 
Model-Based
 Degrees of Freedom Method Between-Within
Class Level Information
Class
Levels
Values
 FunctionGroup 
2 Severe Normal
Dimensions
 Covariance Parameters 
2
 Columns in X 
3
 Columns in Z 
0
 Subjects 
16
 Max Obs per Subject 
1
Number of Observations
 Number of Observations Read 
16
 Number of Observations Used 
16
 Number of Observations Not Used 
0
Iteration History
Iteration Evaluations -2 Res Log Like Criterion
      0 
1
175.20453373
      1 
1
175.05551335 0.00000000
Convergence criteria met.
Covariance Parameter Estimates
Cov Parm
Group
Estimate
 Residual FunctionGroup Severe
10126
 Residual FunctionGroup Normal
13564
Fit Statistics
 -2 Res Log Likelihood 
175.1
 AIC (Smaller is Better) 
179.1
 AICC (Smaller is Better) 180.1
 BIC (Smaller is Better) 
180.6
Null Model Likelihood
Ratio Test
DF
Chi-Square Pr > ChiSq
1
0.15
0.6995
Type 3 Tests of Fixed Effects
Effect
Num
DF
Den
DF
F Value Pr > F
 FunctionGroup 
1
14
0.26 0.6196
Least Squares Means
Effect
Renal
Function
Group
Estimate Standard
Error
DF t Value Pr > |t| Alpha
Lower
Upper
 FunctionGroup Severe
307.38
35.5773 14
8.64
<.0001
0.1 244.71 370.04
 FunctionGroup Normal
279.75
41.1768 14
6.79
<.0001
0.1 207.22 352.28
Differences of Least Squares Means
Effect
Renal
Function
Group
Renal
Function
Group
Estimate Standard
Error
DF t Value Pr > |t| Alpha
Lower
Upper
 FunctionGroup Severe
Normal
27.6250
54.4176 14
0.51
0.6196
0.1 -68.2213 123.47


10:06 Monday, January 22, 2018
5
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - Lasmiditan - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
--------------------- SUMMARY REPORT ---------------------
The Mixed Procedure
10:06 Monday, January 22, 2018
5
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - Lasmiditan - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
--------------------- SUMMARY REPORT ---------------------
The Mixed Procedure
Order=3 Param=AUCT
Model Information
 Data Set 
WORK.KINDATA
 Dependent Variable 
Value
 Covariance Structure 
Variance Components
 Group Effect 
FunctionGroup
 Estimation Method 
REML
 Residual Variance Method 
None
 Fixed Effects SE Method 
Model-Based
 Degrees of Freedom Method Between-Within
Class Level Information
Class
Levels
Values
 FunctionGroup 
2 Severe Normal
Dimensions
 Covariance Parameters 
2
 Columns in X 
3
 Columns in Z 
0
 Subjects 
16
 Max Obs per Subject 
1
Number of Observations
 Number of Observations Read 
16
 Number of Observations Used 
16
 Number of Observations Not Used 
0
Iteration History
Iteration Evaluations -2 Res Log Like Criterion
      0 
1
222.92709703
      1 
1
222.69812530 0.00000000
Convergence criteria met.
Covariance Parameter Estimates
Cov Parm
Group
Estimate
 Residual FunctionGroup Severe
422279
 Residual FunctionGroup Normal
293818
Fit Statistics
 -2 Res Log Likelihood 
222.7
 AIC (Smaller is Better) 
226.7
 AICC (Smaller is Better) 227.8
 BIC (Smaller is Better) 
228.2
Null Model Likelihood
Ratio Test
DF
Chi-Square Pr > ChiSq
1
0.23
0.6323
Type 3 Tests of Fixed Effects
Effect
Num
DF
Den
DF
F Value Pr > F
 FunctionGroup 
1
14
0.76 0.3973
Least Squares Means
Effect
Renal
Function
Group
Estimate Standard
Error
DF t Value Pr > |t| Alpha
Lower
Upper
 FunctionGroup Severe
1950.12
229.75 14
8.49
<.0001
0.1 1545.46 2354.78
 FunctionGroup Normal
1688.88
191.64 14
8.81
<.0001
0.1 1351.33 2026.42
Differences of Least Squares Means
Effect
Renal
Function
Group
Renal
Function
Group
Estimate Standard
Error
DF t Value Pr > |t| Alpha
Lower
Upper
 FunctionGroup Severe
Normal
261.24
299.19 14
0.87
0.3973
0.1 -265.72 788.20


10:06 Monday, January 22, 2018
6
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - Lasmiditan - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
--------------------- SUMMARY REPORT ---------------------
The Mixed Procedure
10:06 Monday, January 22, 2018
6
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - Lasmiditan - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
--------------------- SUMMARY REPORT ---------------------
The Mixed Procedure
Order=5 Param=AUCinf
Model Information
 Data Set 
WORK.KINDATA
 Dependent Variable 
Value
 Covariance Structure 
Variance Components
 Group Effect 
FunctionGroup
 Estimation Method 
REML
 Residual Variance Method 
None
 Fixed Effects SE Method 
Model-Based
 Degrees of Freedom Method Between-Within
Class Level Information
Class
Levels
Values
 FunctionGroup 
2 Severe Normal
Dimensions
 Covariance Parameters 
2
 Columns in X 
3
 Columns in Z 
0
 Subjects 
16
 Max Obs per Subject 
1
Number of Observations
 Number of Observations Read 
16
 Number of Observations Used 
16
 Number of Observations Not Used 
0
Iteration History
Iteration Evaluations -2 Res Log Like Criterion
      0 
1
223.28213516
      1 
1
223.02544785 0.00000000
Convergence criteria met.
Covariance Parameter Estimates
Cov Parm
Group
Estimate
 Residual FunctionGroup Severe
436930
 Residual FunctionGroup Normal
297560
Fit Statistics
 -2 Res Log Likelihood 
223.0
 AIC (Smaller is Better) 
227.0
 AICC (Smaller is Better) 228.1
 BIC (Smaller is Better) 
228.6
Null Model Likelihood
Ratio Test
DF
Chi-Square Pr > ChiSq
1
0.26
0.6124
Type 3 Tests of Fixed Effects
Effect
Num
DF
Den
DF
F Value Pr > F
 FunctionGroup 
1
14
0.80 0.3872
Least Squares Means
Effect
Renal
Function
Group
Estimate Standard
Error
DF t Value Pr > |t| Alpha
Lower
Upper
 FunctionGroup Severe
1975.34
233.70 14
8.45
<.0001
0.1 1563.72 2386.96
 FunctionGroup Normal
1704.90
192.86 14
8.84
<.0001
0.1 1365.22 2044.59
Differences of Least Squares Means
Effect
Renal
Function
Group
Renal
Function
Group
Estimate Standard
Error
DF t Value Pr > |t| Alpha
Lower
Upper
 FunctionGroup Severe
Normal
270.44
303.00 14
0.89
0.3872
0.1 -263.25 804.12


10:06 Monday, January 22, 2018
7
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - Lasmiditan - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
--------------------- SUMMARY REPORT ---------------------
The Mixed Procedure
10:06 Monday, January 22, 2018
7
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - Lasmiditan - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
--------------------- SUMMARY REPORT ---------------------
The Mixed Procedure
Order=12 Param=lnCmax
Model Information
 Data Set 
WORK.KINDATA
 Dependent Variable 
Value
 Covariance Structure 
Variance Components
 Group Effect 
FunctionGroup
 Estimation Method 
REML
 Residual Variance Method 
None
 Fixed Effects SE Method 
Model-Based
 Degrees of Freedom Method Between-Within
Class Level Information
Class
Levels
Values
 FunctionGroup 
2 Severe Normal
Dimensions
 Covariance Parameters 
2
 Columns in X 
3
 Columns in Z 
0
 Subjects 
16
 Max Obs per Subject 
1
Number of Observations
 Number of Observations Read 
16
 Number of Observations Used 
16
 Number of Observations Not Used 
0
Iteration History
Iteration Evaluations -2 Res Log Like Criterion
      0 
1
17.00030740
      1 
1
16.63533952 0.00000000
Convergence criteria met.
Covariance Parameter Estimates
Cov Parm
Group
Estimate
 Residual FunctionGroup Severe
0.1135
 Residual FunctionGroup Normal
0.1795
Fit Statistics
 -2 Res Log Likelihood 
16.6
 AIC (Smaller is Better) 
20.6
 AICC (Smaller is Better) 
21.7
 BIC (Smaller is Better) 
22.2
Null Model Likelihood
Ratio Test
DF
Chi-Square Pr > ChiSq
1
0.36
0.5458
Type 3 Tests of Fixed Effects
Effect
Num
DF
Den
DF
F Value Pr > F
 FunctionGroup 
1
14
0.41 0.5343
Least Squares Means
Effect
Renal
Function
Group
Estimate Standard
Error
DF t Value Pr > |t| Alpha
Lower
Upper
 FunctionGroup Severe
5.6798
0.1191 14
47.69
<.0001
0.1 5.4700 5.8895
 FunctionGroup Normal
5.5578
0.1498 14
37.10
<.0001
0.1 5.2940 5.8217
Differences of Least Squares Means
Effect
Renal
Function
Group
Renal
Function
Group
Estimate Standard
Error
DF t Value Pr > |t| Alpha
Lower
Upper
 FunctionGroup Severe
Normal
0.1220
0.1914 14
0.64
0.5343
0.1 -0.2151 0.4590


10:06 Monday, January 22, 2018
8
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - Lasmiditan - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
--------------------- SUMMARY REPORT ---------------------
The Mixed Procedure
10:06 Monday, January 22, 2018
8
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - Lasmiditan - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
--------------------- SUMMARY REPORT ---------------------
The Mixed Procedure
Order=13 Param=lnAUCT
Model Information
 Data Set 
WORK.KINDATA
 Dependent Variable 
Value
 Covariance Structure 
Variance Components
 Group Effect 
FunctionGroup
 Estimation Method 
REML
 Residual Variance Method 
None
 Fixed Effects SE Method 
Model-Based
 Degrees of Freedom Method Between-Within
Class Level Information
Class
Levels
Values
 FunctionGroup 
2 Severe Normal
Dimensions
 Covariance Parameters 
2
 Columns in X 
3
 Columns in Z 
0
 Subjects 
16
 Max Obs per Subject 
1
Number of Observations
 Number of Observations Read 
16
 Number of Observations Used 
16
 Number of Observations Not Used 
0
Iteration History
Iteration Evaluations -2 Res Log Like Criterion
      0 
1
16.22438554
      1 
1
15.63585311 0.00000000
Convergence criteria met.
Covariance Parameter Estimates
Cov Parm
Group
Estimate
 Residual FunctionGroup Severe
0.09925
 Residual FunctionGroup Normal
0.1780
Fit Statistics
 -2 Res Log Likelihood 
15.6
 AIC (Smaller is Better) 
19.6
 AICC (Smaller is Better) 
20.7
 BIC (Smaller is Better) 
21.2
Null Model Likelihood
Ratio Test
DF
Chi-Square Pr > ChiSq
1
0.59
0.4430
Type 3 Tests of Fixed Effects
Effect
Num
DF
Den
DF
F Value Pr > F
 FunctionGroup 
1
14
0.77 0.3948
Least Squares Means
Effect
Renal
Function
Group
Estimate Standard
Error
DF t Value Pr > |t| Alpha
Lower
Upper
 FunctionGroup Severe
7.5312
0.1114 14
67.61
<.0001
0.1 7.3350 7.7274
 FunctionGroup Normal
7.3677
0.1492 14
49.40
<.0001
0.1 7.1050 7.6304
Differences of Least Squares Means
Effect
Renal
Function
Group
Renal
Function
Group
Estimate Standard
Error
DF t Value Pr > |t| Alpha
Lower
Upper
 FunctionGroup Severe
Normal
0.1634
0.1862 14
0.88
0.3948
0.1 -0.1644 0.4913


10:06 Monday, January 22, 2018
9
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - Lasmiditan - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
--------------------- SUMMARY REPORT ---------------------
The Mixed Procedure
10:06 Monday, January 22, 2018
9
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - Lasmiditan - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
--------------------- SUMMARY REPORT ---------------------
The Mixed Procedure
Order=14 Param=lnAUCinf
Model Information
 Data Set 
WORK.KINDATA
 Dependent Variable 
Value
 Covariance Structure 
Variance Components
 Group Effect 
FunctionGroup
 Estimation Method 
REML
 Residual Variance Method 
None
 Fixed Effects SE Method 
Model-Based
 Degrees of Freedom Method Between-Within
Class Level Information
Class
Levels
Values
 FunctionGroup 
2 Severe Normal
Dimensions
 Covariance Parameters 
2
 Columns in X 
3
 Columns in Z 
0
 Subjects 
16
 Max Obs per Subject 
1
Number of Observations
 Number of Observations Read 
16
 Number of Observations Used 
16
 Number of Observations Not Used 
0
Iteration History
Iteration Evaluations -2 Res Log Like Criterion
      0 
1
16.22800060
      1 
1
15.66382424 0.00000000
Convergence criteria met.
Covariance Parameter Estimates
Cov Parm
Group
Estimate
 Residual FunctionGroup Severe
0.1001
 Residual FunctionGroup Normal
0.1772
Fit Statistics
 -2 Res Log Likelihood 
15.7
 AIC (Smaller is Better) 
19.7
 AICC (Smaller is Better) 
20.8
 BIC (Smaller is Better) 
21.2
Null Model Likelihood
Ratio Test
DF
Chi-Square Pr > ChiSq
1
0.56
0.4526
Type 3 Tests of Fixed Effects
Effect
Num
DF
Den
DF
F Value Pr > F
 FunctionGroup 
1
14
0.80 0.3872
Least Squares Means
Effect
Renal
Function
Group
Estimate Standard
Error
DF t Value Pr > |t| Alpha
Lower
Upper
 FunctionGroup Severe
7.5437
0.1118 14
67.45
<.0001
0.1 7.3467 7.7407
 FunctionGroup Normal
7.3775
0.1488 14
49.57
<.0001
0.1 7.1153 7.6397
Differences of Least Squares Means
Effect
Renal
Function
Group
Renal
Function
Group
Estimate Standard
Error
DF t Value Pr > |t| Alpha
Lower
Upper
 FunctionGroup Severe
Normal
0.1662
0.1862 14
0.89
0.3872
0.1 -0.1617 0.4941


10:06 Monday, January 22, 2018
10
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - Lasmiditan - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
--------------------- SUMMARY REPORT ---------------------
The Mixed Procedure
10:06 Monday, January 22, 2018
10
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - Lasmiditan - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
--------------------- SUMMARY REPORT ---------------------
The Mixed Procedure
Order=21 Param=RkTmax
Model Information
 Data Set 
WORK.KINDATA
 Dependent Variable 
Value
 Covariance Structure 
Variance Components
 Group Effect 
FunctionGroup
 Estimation Method 
REML
 Residual Variance Method 
None
 Fixed Effects SE Method 
Model-Based
 Degrees of Freedom Method Between-Within
Class Level Information
Class
Levels
Values
 FunctionGroup 
2 Severe Normal
Dimensions
 Covariance Parameters 
2
 Columns in X 
3
 Columns in Z 
0
 Subjects 
16
 Max Obs per Subject 
1
Number of Observations
 Number of Observations Read 
16
 Number of Observations Used 
16
 Number of Observations Not Used 
0
Iteration History
Iteration Evaluations -2 Res Log Like Criterion
      0 
1
87.60832691
      1 
1
86.88680275 0.00000000
Convergence criteria met.
Covariance Parameter Estimates
Cov Parm
Group
Estimate
 Residual FunctionGroup Severe
29.8170
 Residual FunctionGroup Normal
15.6027
Fit Statistics
 -2 Res Log Likelihood 
86.9
 AIC (Smaller is Better) 
90.9
 AICC (Smaller is Better) 
92.0
 BIC (Smaller is Better) 
92.4
Null Model Likelihood
Ratio Test
DF
Chi-Square Pr > ChiSq
1
0.72
0.3956
Type 3 Tests of Fixed Effects
Effect
Num
DF
Den
DF
F Value Pr > F
 FunctionGroup 
1
14
0.62 0.4445
Least Squares Means
Effect
Renal
Function
Group
Estimate Standard
Error
DF t Value Pr > |t| Alpha
Lower
Upper
 FunctionGroup Severe
7.5625
1.9306 14
3.92
0.0015
0.1 4.1622 10.9628
 FunctionGroup Normal
9.4375
1.3965 14
6.76
<.0001
0.1 6.9778 11.8972
Differences of Least Squares Means
Effect
Renal
Function
Group
Renal
Function
Group
Estimate Standard
Error
DF t Value Pr > |t| Alpha
Lower
Upper
 FunctionGroup Severe
Normal
-1.8750
2.3827 14
-0.79
0.4445
0.1 -6.0717 2.3217


10:06 Monday, January 22, 2018
11
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - Lasmiditan - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
Geometric LSmeans
--------------------- SUMMARY REPORT ---------------------
10:06 Monday, January 22, 2018
11
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - Lasmiditan - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
Geometric LSmeans
--------------------- SUMMARY REPORT ---------------------
Obs Parameters Group GeoLSmeans
 1 lnCmax
Severe
292.88
 2 lnCmax
Normal
259.26
 3 lnAUCT
Severe
1865.31
 4 lnAUCT
Normal
1584.04
 5 lnAUCinf
Severe
1888.74
 6 lnAUCinf
Normal
1599.58


10:06 Monday, January 22, 2018
12
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - Lasmiditan - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
RATIO ESTIMATE BASED ON ln-TRANSFORMED PARAMETERS
--------------------- SUMMARY REPORT ---------------------
10:06 Monday, January 22, 2018
12
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - Lasmiditan - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
RATIO ESTIMATE BASED ON ln-TRANSFORMED PARAMETERS
--------------------- SUMMARY REPORT ---------------------
Obs Parameters Group
vs
Group
Ratio
(%)
L90
U90
 1 lnCmax
Severe Normal 112.970 80.643 158.255
 2 lnAUCT
Severe Normal 117.756 84.837 163.447
 3 lnAUCinf
Severe Normal 118.077 85.065 163.901


Clinical Study Report  
Project No COL MIG-113/H8H-CD-LAHN 
 
16.1.9.3 Documentation of statistical analysis – SAS® output of (S)-M8 
 
Legend:  
AUCinf= AUC(0−∞) 
AUCT=AUC(0-tlast) 
Vz_F= VZ/F 
CL_F= CL/F 
LambdaZ = λZ 
lCmax= ln(Cmax) 
lAUCT= ln(AUC(0-tlast)) 
lAUCinf= ln(AUC(0−∞)) 
lCLF= ln(CL/F) 
lLambdaZ = ln(λZ) 
lVz_F= ln(VZ/F) 
RkTmax= Rank of Tmax 


11:31 Monday, February 12, 2018
1
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M8
(Healthy vs Severe)
ANOVA analysis
RAW DATA
--------------------- SUMMARY REPORT ---------------------
11:31 Monday, February 12, 2018
1
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M8
(Healthy vs Severe)
ANOVA analysis
RAW DATA
--------------------- SUMMARY REPORT ---------------------
Renal Function Group=Normal
Obs Subject
Cmax
Tmax
AUCT
Thalf
Ae
AUCinf
Res_Area Lambda_z lnCmax
lnAUCT
 1 101
418.00000 2.00000 5781.92500 16.77310
86.63720 7258.77076 20.34567
0.04132 6.03548 8.66249
 2 102
292.00000 2.50000 5449.00000 14.37083
83.95300 6685.55732 18.49595
0.04823 5.67675 8.60319
 3 103
527.00000 2.50000 7332.65000 11.05589 111.32950 8072.40389
9.16399
0.06269 6.26720 8.90009
 4 104
482.00000 2.00000 7017.30800 10.73134
75.04500 7829.60165 10.37465
0.06459 6.17794 8.85613
 5 105
276.00000 0.75000 2600.95000 22.26073
72.86400 3495.21568 25.58542
0.03114 5.62040 7.86363
 6 106
587.00000 2.50000 6180.57500
9.57655 114.41100 6588.78200
6.19549
0.07238 6.37502 8.72917
 7 107
368.00000 6.00000 6280.01000 12.05213
93.66040 7234.85257 13.19782
0.05751 5.90808 8.74513
 8 108
305.00000 2.50000 5063.21950 14.79742
93.54840 6192.57687 18.23728
0.04684 5.72031 8.52976
Obs lnAUCinf
lnAe
lnLambda_z RkTmax
eGFR
CrCL
 1 
8.8900 4.46173
-3.18629
6.5 115.00000 163.85000
 2 
8.8077 4.43026
-3.03171
9.5 102.00000 152.84000
 3 
8.9962 4.71249
-2.76948
9.5
94.00000 100.45000
 4 
8.9657 4.31809
-2.73968
6.5 109.00000 124.34000
 5 
8.1592 4.28859
-3.46934
1.5 102.00000 155.18000
 6 
8.7931 4.73980
-2.62583
9.5 116.00000 120.18000
 7 
8.8867 4.53968
-2.85575
14.5
98.00000 116.39000
 8 
8.7311 4.53848
-3.06097
9.5 118.00000 147.36000


11:31 Monday, February 12, 2018
2
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M8
(Healthy vs Severe)
ANOVA analysis
RAW DATA
--------------------- SUMMARY REPORT ---------------------
11:31 Monday, February 12, 2018
2
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M8
(Healthy vs Severe)
ANOVA analysis
RAW DATA
--------------------- SUMMARY REPORT ---------------------
Renal Function Group=Severe
Obs Subject
Cmax
Tmax
AUCT
Thalf
Ae
AUCinf
Res_Area Lambda_z lnCmax
 9 201
358.00000 1.00000
7425.10000 39.27202 28.24120 15368.01449 51.68471
0.01765 5.88053
 10 202
470.00000 1.75000
9428.50000 25.32404 41.78940 15253.32387 38.18724
0.02737 6.15273
 11 203
310.00000 4.00000
6700.17250 29.06330 40.12630 12055.64869 44.42296
0.02385 5.73657
 12 204
417.00000 6.00000 10078.39167 23.04963 48.17324 15380.50680 34.47295
0.03007 6.03309
 13 205
659.00000 6.00000 13860.92500 24.48850 55.44030 21130.95349 34.40464
0.02831 6.49072
 14 206
849.00000 0.75000 13271.27500 31.80603 33.06085 23844.88619 44.34331
0.02179 6.74406
 15 207
453.00000 1.00000
9315.07500 34.16493 45.28310 17732.59498 47.46919
0.02029 6.11589
 16 208
331.00000 6.00000
7604.02333 25.01790 48.79000 12356.74154 38.46255
0.02771 5.80212
Obs
lnAUCT lnAUCinf
lnAe
lnLambda_z RkTmax
eGFR
CrCL
 9 8.91262
9.6400 3.34078
-4.03703
3.5 26.00000 40.09000
 10 9.15149
9.6326 3.73264
-3.59827
5.0 23.00000 29.51000
 11 8.80989
9.3973 3.69203
-3.73599
12.0 26.00000 43.68000
 12 9.21815
9.6409 3.87480
-3.50416
14.5 19.00000 30.22000
 13 9.53683
9.9585 4.01531
-3.56472
14.5 27.00000 26.90000
 14 9.49336
10.0793 3.49835
-3.82617
1.5 16.00000 20.27000
 15 9.13939
9.7832 3.81293
-3.89771
3.5 21.00000 30.33000
 16 8.93643
9.4220 3.88753
-3.58610
14.5 28.00000 65.77000


11:31 Monday, February 12, 2018
3
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M8
(Healthy vs Severe)
ANOVA analysis
DESCRIPTIVE RESULTS (OVERALL)
--------------------- SUMMARY REPORT ---------------------
11:31 Monday, February 12, 2018
3
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M8
(Healthy vs Severe)
ANOVA analysis
DESCRIPTIVE RESULTS (OVERALL)
--------------------- SUMMARY REPORT ---------------------
Parameter
Renal
Function
Group
n
Min
Mean
Geometric
Mean
Median
Max
Standard
Deviation
Coefficient
of
Variation
Cmax
Normal
8
276.00000
406.87500
392.54455
393.00000
587.00000
116.40869
28.6104
Cmax
Severe
8
310.00000
480.87500
454.62126
435.00000
849.00000
184.76969
38.4236
Tmax
Normal
8
0.75000
2.59375
2.26923
2.50000
6.00000
1.49963
57.8170
Tmax
Severe
8
0.75000
3.31250
2.40894
2.87500
6.00000
2.44493
73.8092
AUCT
Normal
8 2600.95000 5713.20469
5492.82916 5981.25000 7332.65000 1466.09922
25.6616
AUCT
Severe
8 6700.17250 9710.43281
9412.27480 9371.78750 13860.9250 2645.71741
27.2461
Thalf
Normal
8
9.57655
13.95225
13.47543
13.21148
22.26073
4.12999
29.6009
Thalf
Severe
8
23.04963
29.02329
28.56709
27.19367
39.27202
5.67192
19.5427
Ae
Normal
8
72.86400
91.43106
90.34533
90.09280
114.41100
15.23914
16.6674
Ae
Severe
8
28.24120
42.61305
41.75407
43.53625
55.44030
8.82686
20.7140
AUCinf
Normal
8 3495.21568 6669.72009
6494.42091 6960.20495 8072.40389 1428.84310
21.4228
AUCinf
Severe
8 12055.6487 16640.3338 16223.39570 15374.2606 23844.8862 4101.61174
24.6486
Res_Area
Normal
8
6.19549
15.19953
13.86411
15.71755
25.58542
6.53814
43.0154
Res_Area
Severe
8
34.40464
41.68095
41.27221
41.40293
51.68471
6.27523
15.0554
Lambda_z
Normal
8
0.03114
0.05309
0.05144
0.05287
0.07238
0.01362
25.6606
Lambda_z
Severe
8
0.01765
0.02463
0.02426
0.02561
0.03007
0.00441
17.9180
lnCmax
Normal
8
5.62040
5.97265
5.97178
6.37502
0.28642
4.7954
lnCmax
Severe
8
5.73657
6.11946
6.07449
6.74406
0.34660
5.6639
lnAUCT
Normal
8
7.86363
8.61120
8.69583
8.90009
0.32590
3.7846
lnAUCT
Severe
8
8.80989
9.14977
9.14544
9.53683
0.26455
2.8914
lnAUCinf
Normal
8
8.15915
8.77870
8.84719
8.99621
0.26551
3.0244
lnAUCinf
Severe
8
9.39729
9.69421
9.64045
10.07933
0.23843
2.4595
lnAe
Normal
8
4.28859
4.50364
4.50010
4.73980
0.16463
3.6555
lnAe
Severe
8
3.34078
3.73180
3.77279
4.01531
0.22060
5.9112
lnLambda_z Normal
8
-3.46934
-2.96738
-2.94373
-2.62583
0.27592
-9.2983
lnLambda_z Severe
8
-4.03703
-3.71877
-3.66713
-3.50416
0.18786
-5.0518
RkTmax
Normal
8
1.50000
8.37500
7.23224
9.50000
14.50000
3.72012
44.4193
RkTmax
Severe
8
1.50000
8.62500
6.54350
8.50000
14.50000
5.74922
66.6577


11:31 Monday, February 12, 2018
4
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M8
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:31 Monday, February 12, 2018
4
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M8
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=9 Param=lnCmax
 Number of Observations Read 16
 Number of Observations Used 16
Analysis of Variance
Source
DF Sum of
Squares
Mean
Square
F Value Pr > F
 Model 
1 0.09927 0.09927
0.99 0.3363
 Error 
14 1.40212 0.10015
 Corrected Total 15 1.50139
 Root MSE 
0.31647  R-Square 
0.0661
 Dependent Mean 6.04606  Adj R-Sq -0.0006
 Coeff Var 
5.23427    
Parameter Estimates
Variable
Label
DF Parameter
Estimate
Standard
Error
t Value Pr > |t|
95%
Confidence
Limits
 Intercept Intercept
1
6.16719
0.14513
42.50
<.0001
5.85592 6.47845
 eGFR 
eGFR
1
-0.00186
0.00187
-1.00
0.3363 -0.00588 0.00215


11:31 Monday, February 12, 2018
5
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M8
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:31 Monday, February 12, 2018
5
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M8
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=9 Param=lnCmax
Output Statistics
Obs
Dependent
Variable
Predicted
Value
Std Error
Mean Predict
Residual Std Error
Residual
Student
Residual
-2-1 0 1 2
Cook's
D
        1 
6.0355
5.9529
0.1225
0.0826
0.292
0.283  |      |      | 
0.007
        2 
5.6768
5.9771
0.1051
-0.3004
0.298
-1.006  |    **|      | 
0.063
        3 
6.2672
5.9920
0.0959
0.2752
0.302
0.913  |      |*     | 
0.042
        4 
6.1779
5.9641
0.1142
0.2139
0.295
0.725  |      |*     | 
0.039
        5 
5.6204
5.9771
0.1051
-0.3567
0.298
-1.195  |    **|      | 
0.089
        6 
6.3750
5.9510
0.1240
0.4240
0.291
1.456  |      |**    | 
0.192
        7 
5.9081
5.9846
0.1004
-0.0765
0.300
-0.255  |      |      | 
0.004
        8 
5.7203
5.9473
0.1269
-0.2270
0.290
-0.783  |     *|      | 
0.059
        9 
5.8805
6.1187
0.1076
-0.2382
0.298
-0.800  |     *|      | 
0.042
       10 
6.1527
6.1243
0.1115
0.0284
0.296
0.0959  |      |      | 
0.001
       11 
5.7366
6.1187
0.1076
-0.3822
0.298
-1.284  |    **|      | 
0.108
       12 
6.0331
6.1318
0.1169
-0.0987
0.294
-0.336  |      |      | 
0.009
       13 
6.4907
6.1169
0.1064
0.3739
0.298
1.254  |      |**    | 
0.100
       14 
6.7441
6.1374
0.1211
0.6067
0.292
2.075  |      |****  | 
0.370
       15 
6.1159
6.1281
0.1142
-0.0122
0.295
-0.0412  |      |      | 
0.000
       16 
5.8021
6.1150
0.1051
-0.3129
0.298
-1.048  |    **|      | 
0.068
 Sum of Residuals 
0
 Sum of Squared Residuals 
1.40212
 Predicted Residual SS (PRESS) 1.84804


11:31 Monday, February 12, 2018
6
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M8
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:31 Monday, February 12, 2018
6
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M8
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=10 Param=lnAUCT
 Number of Observations Read 16
 Number of Observations Used 16
Analysis of Variance
Source
DF Sum of
Squares
Mean
Square
F Value Pr > F
 Model 
1 1.18316 1.18316
13.68 0.0024
 Error 
14 1.21049 0.08646
 Corrected Total 15 2.39365
 Root MSE 
0.29405  R-Square 0.4943
 Dependent Mean 8.88048  Adj R-Sq 0.4582
 Coeff Var 
3.31116    
Parameter Estimates
Variable
Label
DF Parameter
Estimate
Standard
Error
t Value Pr > |t|
95%
Confidence
Limits
 Intercept Intercept
1
9.29866
0.13485
68.96
<.0001
9.00945
9.58787
 eGFR 
eGFR
1
-0.00643
0.00174
-3.70
0.0024 -0.01016 -0.00270


11:31 Monday, February 12, 2018
7
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M8
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:31 Monday, February 12, 2018
7
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M8
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=10 Param=lnAUCT
Output Statistics
Obs
Dependent
Variable
Predicted
Value
Std Error
Mean Predict
Residual Std Error
Residual
Student
Residual
-2-1 0 1 2
Cook's
D
        1 
8.6625
8.5588
0.1139
0.1037
0.271
0.382  |      |      | 
0.013
        2 
8.6032
8.6424
0.0977
-0.0393
0.277
-0.142  |      |      | 
0.001
        3 
8.9001
8.6939
0.0892
0.2062
0.280
0.736  |      |*     | 
0.027
        4 
8.8561
8.5974
0.1061
0.2587
0.274
0.943  |      |*     | 
0.067
        5 
7.8636
8.6424
0.0977
-0.7788
0.277
-2.808  | *****|      | 
0.489
        6 
8.7292
8.5524
0.1152
0.1768
0.271
0.653  |      |*     | 
0.039
        7 
8.7451
8.6682
0.0933
0.0769
0.279
0.276  |      |      | 
0.004
        8 
8.5298
8.5395
0.1179 -0.009753
0.269
-0.0362  |      |      | 
0.000
        9 
8.9126
9.1314
0.1000
-0.2188
0.277
-0.791  |     *|      | 
0.041
       10 
9.1515
9.1507
0.1036
0.000802
0.275
0.00292  |      |      | 
0.000
       11 
8.8099
9.1314
0.1000
-0.3215
0.277
-1.163  |    **|      | 
0.088
       12 
9.2181
9.1764
0.1086
0.0417
0.273
0.153  |      |      | 
0.002
       13 
9.5368
9.1250
0.0989
0.4119
0.277
1.487  |      |**    | 
0.141
       14 
9.4934
9.1957
0.1125
0.2976
0.272
1.096  |      |**    | 
0.103
       15 
9.1394
9.1636
0.1061
-0.0242
0.274
-0.0881  |      |      | 
0.001
       16 
8.9364
9.1185
0.0977
-0.1821
0.277
-0.657  |     *|      | 
0.027
 Sum of Residuals 
0
 Sum of Squared Residuals 
1.21049
 Predicted Residual SS (PRESS) 1.54997


11:31 Monday, February 12, 2018
8
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M8
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:31 Monday, February 12, 2018
8
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M8
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=11 Param=lnAUCinf
 Number of Observations Read 16
 Number of Observations Used 16
Analysis of Variance
Source
DF Sum of
Squares
Mean
Square
F Value Pr > F
 Model 
1 3.35690 3.35690
52.98 <.0001
 Error 
14 0.88714 0.06337
 Corrected Total 15 4.24404
 Root MSE 
0.25173  R-Square 0.7910
 Dependent Mean 9.23645  Adj R-Sq 0.7760
 Coeff Var 
2.72538    
Parameter Estimates
Variable
Label
DF Parameter
Estimate
Standard
Error
t Value Pr > |t|
95%
Confidence
Limits
 Intercept Intercept
1
9.94083
0.11544
86.11
<.0001
9.69324 10.18842
 eGFR 
eGFR
1
-0.01084
0.00149
-7.28
<.0001 -0.01403 -0.00764


11:31 Monday, February 12, 2018
9
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M8
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:31 Monday, February 12, 2018
9
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M8
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=11 Param=lnAUCinf
Output Statistics
Obs
Dependent
Variable
Predicted
Value
Std Error
Mean Predict
Residual Std Error
Residual
Student
Residual
-2-1 0 1 2
Cook's
D
        1 
8.8900
8.6946
0.0975
0.1953
0.232
0.842  |      |*     | 
0.062
        2 
8.8077
8.8355
0.0836
-0.0278
0.237
-0.117  |      |      | 
0.001
        3 
8.9962
8.9222
0.0763
0.0740
0.240
0.309  |      |      | 
0.005
        4 
8.9657
8.7596
0.0908
0.2060
0.235
0.878  |      |*     | 
0.058
        5 
8.1592
8.8355
0.0836
-0.6764
0.237
-2.849  | *****|      | 
0.503
        6 
8.7931
8.6838
0.0986
0.1093
0.232
0.472  |      |      | 
0.020
        7 
8.8867
8.8788
0.0798 0.007818
0.239
0.0327  |      |      | 
0.000
        8 
8.7311
8.6621
0.1009
0.0690
0.231
0.299  |      |      | 
0.009
        9 
9.6400
9.6591
0.0856
-0.0190
0.237
-0.0804  |      |      | 
0.000
       10 
9.6326
9.6916
0.0887
-0.0590
0.236
-0.251  |      |      | 
0.004
       11 
9.3973
9.6591
0.0856
-0.2618
0.237
-1.106  |    **|      | 
0.080
       12 
9.6409
9.7349
0.0930
-0.0941
0.234
-0.402  |      |      | 
0.013
       13 
9.9585
9.6482
0.0846
0.3102
0.237
1.309  |      |**    | 
0.109
       14 
10.0793
9.7674
0.0963
0.3119
0.233
1.341  |      |**    | 
0.154
       15 
9.7832
9.7133
0.0908
0.0699
0.235
0.298  |      |      | 
0.007
       16 
9.4220
9.6374
0.0836
-0.2155
0.237
-0.907  |     *|      | 
0.051
 Sum of Residuals 
0
 Sum of Squared Residuals 
0.88714
 Predicted Residual SS (PRESS) 1.14358


11:31 Monday, February 12, 2018
10
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M8
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:31 Monday, February 12, 2018
10
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M8
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=12 Param=lnAe
 Number of Observations Read 16
 Number of Observations Used 16
Analysis of Variance
Source
DF Sum of
Squares
Mean
Square
F Value Pr > F
 Model 
1 2.35608 2.35608
59.19 <.0001
 Error 
14 0.55724 0.03980
 Corrected Total 15 2.91332
 Root MSE 
0.19951  R-Square 0.8087
 Dependent Mean 4.11772  Adj R-Sq 0.7951
 Coeff Var 
4.84506    
Parameter Estimates
Variable
Label
DF Parameter
Estimate
Standard
Error
t Value Pr > |t|
95%
Confidence
Limits
 Intercept Intercept
1
3.52761
0.09149
38.56
<.0001 3.33138 3.72384
 eGFR 
eGFR
1
0.00908
0.00118
7.69
<.0001 0.00655 0.01161


11:31 Monday, February 12, 2018
11
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M8
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:31 Monday, February 12, 2018
11
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M8
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=12 Param=lnAe
Output Statistics
Obs
Dependent
Variable
Predicted
Value
Std Error
Mean Predict
Residual Std Error
Residual
Student
Residual
-2-1 0 1 2
Cook's
D
        1 
4.4617
4.5716
0.0773
-0.1099
0.184
-0.598  |     *|      | 
0.031
        2 
4.4303
4.4536
0.0663
-0.0234
0.188
-0.124  |      |      | 
0.001
        3 
4.7125
4.3810
0.0605
0.3315
0.190
1.744  |      |***   | 
0.154
        4 
4.3181
4.5172
0.0720
-0.1991
0.186
-1.070  |    **|      | 
0.086
        5 
4.2886
4.4536
0.0663
-0.1650
0.188
-0.877  |     *|      | 
0.048
        6 
4.7398
4.5807
0.0782
0.1591
0.184
0.867  |      |*     | 
0.068
        7 
4.5397
4.4173
0.0633
0.1224
0.189
0.647  |      |*     | 
0.023
        8 
4.5385
4.5989
0.0800
-0.0604
0.183
-0.330  |      |      | 
0.010
        9 
3.3408
3.7637
0.0679
-0.4229
0.188
-2.254  |  ****|      | 
0.332
       10 
3.7326
3.7364
0.0703 -0.003775
0.187
-0.0202  |      |      | 
0.000
       11 
3.6920
3.7637
0.0679
-0.0716
0.188
-0.382  |      |      | 
0.010
       12 
3.8748
3.7001
0.0737
0.1747
0.185
0.942  |      |*     | 
0.070
       13 
4.0153
3.7727
0.0671
0.2426
0.188
1.291  |      |**    | 
0.106
       14 
3.4983
3.6729
0.0764
-0.1745
0.184
-0.947  |     *|      | 
0.077
       15 
3.8129
3.7183
0.0720
0.0947
0.186
0.509  |      |*     | 
0.019
       16 
3.8875
3.7818
0.0663
0.1057
0.188
0.562  |      |*     | 
0.020
 Sum of Residuals 
0
 Sum of Squared Residuals 
0.55724
 Predicted Residual SS (PRESS) 0.71524


11:31 Monday, February 12, 2018
12
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M8
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:31 Monday, February 12, 2018
12
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M8
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=13 Param=lnLambda_z
 Number of Observations Read 16
 Number of Observations Used 16
Analysis of Variance
Source
DF Sum of
Squares
Mean
Square
F Value Pr > F
 Model 
1 2.21253 2.21253
37.51 <.0001
 Error 
14 0.82576 0.05898
 Corrected Total 15 3.03829
 Root MSE 
0.24286  R-Square 0.7282
 Dependent Mean -3.34307  Adj R-Sq 0.7088
 Coeff Var 
-7.26467    
Parameter Estimates
Variable
Label
DF Parameter
Estimate
Standard
Error
t Value Pr > |t|
95%
Confidence
Limits
 Intercept Intercept
1
-3.91492
0.11137
-35.15
<.0001 -4.15380 -3.67605
 eGFR 
eGFR
1
0.00880
0.00144
6.12
<.0001
0.00572
0.01188


11:31 Monday, February 12, 2018
13
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M8
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:31 Monday, February 12, 2018
13
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M8
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=13 Param=lnLambda_z
Output Statistics
Obs
Dependent
Variable
Predicted
Value
Std Error
Mean Predict
Residual Std Error
Residual
Student
Residual
-2-1 0 1 2
Cook's
D
        1 
-3.1863
-2.9032
0.0940
-0.2831
0.224
-1.264  |    **|      | 
0.141
        2 
-3.0317
-3.0176
0.0807
-0.0142
0.229
-0.0618  |      |      | 
0.000
        3 
-2.7695
-3.0879
0.0736
0.3185
0.231
1.376  |      |**    | 
0.096
        4 
-2.7397
-2.9560
0.0876
0.2163
0.226
0.955  |      |*     | 
0.068
        5 
-3.4693
-3.0176
0.0807
-0.4518
0.229
-1.972  |   ***|      | 
0.241
        6 
-2.6258
-2.8944
0.0951
0.2686
0.223
1.202  |      |**    | 
0.131
        7 
-2.8558
-3.0528
0.0770
0.1970
0.230
0.855  |      |*     | 
0.041
        8 
-3.0610
-2.8768
0.0974
-0.1842
0.222
-0.828  |     *|      | 
0.066
        9 
-4.0370
-3.6862
0.0826
-0.3508
0.228
-1.536  |   ***|      | 
0.154
       10 
-3.5983
-3.7126
0.0856
0.1143
0.227
0.503  |      |*     | 
0.018
       11 
-3.7360
-3.6862
0.0826
-0.0498
0.228
-0.218  |      |      | 
0.003
       12 
-3.5042
-3.7478
0.0897
0.2436
0.226
1.079  |      |**    | 
0.092
       13 
-3.5647
-3.6774
0.0816
0.1127
0.229
0.493  |      |      | 
0.015
       14 
-3.8262
-3.7742
0.0930
-0.0520
0.224
-0.232  |      |      | 
0.005
       15 
-3.8977
-3.7302
0.0876
-0.1675
0.226
-0.740  |     *|      | 
0.041
       16 
-3.5861
-3.6686
0.0807
0.0825
0.229
0.360  |      |      | 
0.008
 Sum of Residuals 
0
 Sum of Squared Residuals 
0.82576
 Predicted Residual SS (PRESS) 1.07344


11:31 Monday, February 12, 2018
14
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M8
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:31 Monday, February 12, 2018
14
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M8
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=14 Param=RkTmax
 Number of Observations Read 16
 Number of Observations Used 16
Analysis of Variance
Source
DF
Sum of
Squares
Mean
Square
F Value Pr > F
 Model 
1
0.04660
0.04660
0.00 0.9651
 Error 
14 328.45340 23.46096
 Corrected Total 15 328.50000
 Root MSE 
4.84365  R-Square 
0.0001
 Dependent Mean 
8.50000  Adj R-Sq -0.0713
 Coeff Var 
56.98413    
Parameter Estimates
Variable
Label
DF Parameter
Estimate
Standard
Error
t Value Pr > |t|
95%
Confidence
Limits
 Intercept Intercept
1
8.58300
2.22122
3.86
0.0017
3.81895 13.34704
 eGFR 
eGFR
1
-0.00128
0.02865
-0.04
0.9651 -0.06272
0.06017


11:31 Monday, February 12, 2018
15
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M8
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:31 Monday, February 12, 2018
15
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M8
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=14 Param=RkTmax
Output Statistics
Obs
Dependent
Variable
Predicted
Value
Std Error
Mean Predict
Residual Std Error
Residual
Student
Residual
-2-1 0 1 2
Cook's
D
        1 
6.5000
8.4362
1.8757
-1.9362
4.466
-0.434  |      |      | 
0.017
        2 
9.5000
8.4528
1.6093
1.0472
4.568
0.229  |      |      | 
0.003
        3 
9.5000
8.4630
1.4685
1.0370
4.616
0.225  |      |      | 
0.003
        4 
6.5000
8.4438
1.7479
-1.9438
4.517
-0.430  |      |      | 
0.014
        5 
1.5000
8.4528
1.6093
-6.9528
4.568
-1.522  |   ***|      | 
0.144
        6 
9.5000
8.4349
1.8976
1.0651
4.456
0.239  |      |      | 
0.005
        7 
14.5000
8.4579
1.5363
6.0421
4.594
1.315  |      |**    | 
0.097
        8 
9.5000
8.4323
1.9421
1.0677
4.437
0.241  |      |      | 
0.006
        9 
3.5000
8.5498
1.6476
-5.0498
4.555
-1.109  |    **|      | 
0.080
       10 
5.0000
8.5536
1.7071
-3.5536
4.533
-0.784  |     *|      | 
0.044
       11 
12.0000
8.5498
1.6476
3.4502
4.555
0.757  |      |*     | 
0.038
       12 
14.5000
8.5587
1.7897
5.9413
4.501
1.320  |      |**    | 
0.138
       13 
14.5000
8.5485
1.6283
5.9515
4.562
1.305  |      |**    | 
0.108
       14 
1.5000
8.5626
1.8539
-7.0626
4.475
-1.578  |   ***|      | 
0.214
       15 
3.5000
8.5562
1.7479
-5.0562
4.517
-1.119  |    **|      | 
0.094
       16 
14.5000
8.5472
1.6093
5.9528
4.568
1.303  |      |**    | 
0.105
 Sum of Residuals 
0
 Sum of Squared Residuals 
328.45340
 Predicted Residual SS (PRESS) 425.98888


11:31 Monday, February 12, 2018
16
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M8
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:31 Monday, February 12, 2018
16
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M8
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=9 Param=lnCmax
 Number of Observations Read 16
 Number of Observations Used 16
Analysis of Variance
Source
DF Sum of
Squares
Mean
Square
F Value Pr > F
 Model 
1 0.29993 0.29993
3.49 0.0826
 Error 
14 1.20146 0.08582
 Corrected Total 15 1.50139
 Root MSE 
0.29295  R-Square 0.1998
 Dependent Mean 6.04606  Adj R-Sq 0.1426
 Coeff Var 
4.84527    
Parameter Estimates
Variable
Label
DF Parameter
Estimate
Standard
Error
t Value Pr > |t|
95%
Confidence Limits
 Intercept Intercept
1
6.26825
0.13961
44.90
<.0001
5.96883
6.56768
 CrCL 
CrCL
1
-0.00260
0.00139
-1.87
0.0826 -0.00558 0.00038289


11:31 Monday, February 12, 2018
17
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M8
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:31 Monday, February 12, 2018
17
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M8
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=9 Param=lnCmax
Output Statistics
Obs
Dependent
Variable
Predicted
Value
Std Error
Mean Predict
Residual Std Error
Residual
Student
Residual
-2-1 0 1 2
Cook's
D
        1 
6.0355
5.8422
0.1313
0.1932
0.262
0.738  |      |*     | 
0.068
        2 
5.6768
5.8709
0.1189
-0.1941
0.268
-0.725  |     *|      | 
0.052
        3 
6.2672
6.0071
0.0761
0.2601
0.283
0.920  |      |*     | 
0.031
        4 
6.1779
5.9450
0.0910
0.2330
0.278
0.837  |      |*     | 
0.037
        5 
5.6204
5.8648
0.1215
-0.2444
0.267
-0.917  |     *|      | 
0.087
        6 
6.3750
5.9558
0.0877
0.4192
0.280
1.500  |      |**    | 
0.111
        7 
5.9081
5.9656
0.0849
-0.0576
0.280
-0.205  |      |      | 
0.002
        8 
5.7203
5.8851
0.1130
-0.1648
0.270
-0.610  |     *|      | 
0.033
        9 
5.8805
6.1640
0.0967
-0.2835
0.277
-1.025  |    **|      | 
0.064
       10 
6.1527
6.1915
0.1069
-0.0388
0.273
-0.142  |      |      | 
0.002
       11 
5.7366
6.1547
0.0935
-0.4181
0.278
-1.506  |   ***|      | 
0.129
       12 
6.0331
6.1897
0.1061
-0.1566
0.273
-0.574  |     *|      | 
0.025
       13 
6.4907
6.1983
0.1095
0.2924
0.272
1.076  |      |**    | 
0.094
       14 
6.7441
6.2156
0.1165
0.5285
0.269
1.966  |      |***   | 
0.364
       15 
6.1159
6.1894
0.1060
-0.0735
0.273
-0.269  |      |      | 
0.005
       16 
5.8021
6.0973
0.0782
-0.2951
0.282
-1.045  |    **|      | 
0.042
 Sum of Residuals 
0
 Sum of Squared Residuals 
1.20146
 Predicted Residual SS (PRESS) 1.56784


11:31 Monday, February 12, 2018
18
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M8
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:31 Monday, February 12, 2018
18
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M8
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=10 Param=lnAUCT
 Number of Observations Read 16
 Number of Observations Used 16
Analysis of Variance
Source
DF Sum of
Squares
Mean
Square
F Value Pr > F
 Model 
1 1.57752 1.57752
27.06 0.0001
 Error 
14 0.81613 0.05830
 Corrected Total 15 2.39365
 Root MSE 
0.24144  R-Square 0.6590
 Dependent Mean 8.88048  Adj R-Sq 0.6347
 Coeff Var 
2.71881    
Parameter Estimates
Variable
Label
DF Parameter
Estimate
Standard
Error
t Value Pr > |t|
95%
Confidence
Limits
 Intercept Intercept
1
9.39007
0.11506
81.61
<.0001
9.14328
9.63685
 CrCL 
CrCL
1
-0.00596
0.00115
-5.20
0.0001 -0.00842 -0.00350


11:31 Monday, February 12, 2018
19
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M8
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:31 Monday, February 12, 2018
19
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M8
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=10 Param=lnAUCT
Output Statistics
Obs
Dependent
Variable
Predicted
Value
Std Error
Mean Predict
Residual Std Error
Residual
Student
Residual
-2-1 0 1 2
Cook's
D
        1 
8.6625
8.4131
0.1082
0.2494
0.216
1.156  |      |**    | 
0.168
        2 
8.6032
8.4787
0.0980
0.1245
0.221
0.564  |      |*     | 
0.031
        3 
8.9001
8.7911
0.0628
0.1090
0.233
0.467  |      |      | 
0.008
        4 
8.8561
8.6486
0.0750
0.2075
0.229
0.904  |      |*     | 
0.044
        5 
7.8636
8.4648
0.1002
-0.6011
0.220
-2.736  | *****|      | 
0.778
        6 
8.7292
8.6735
0.0723
0.0557
0.230
0.242  |      |      | 
0.003
        7 
8.7451
8.6961
0.0700
0.0491
0.231
0.212  |      |      | 
0.002
        8 
8.5298
8.5114
0.0932
0.0184
0.223
0.0825  |      |      | 
0.001
        9 
8.9126
9.1510
0.0797
-0.2384
0.228
-1.046  |    **|      | 
0.067
       10 
9.1515
9.2141
0.0881
-0.0626
0.225
-0.279  |      |      | 
0.006
       11 
8.8099
9.1296
0.0771
-0.3197
0.229
-1.397  |    **|      | 
0.111
       12 
9.2181
9.2099
0.0875 0.008278
0.225
0.0368  |      |      | 
0.000
       13 
9.5368
9.2297
0.0903
0.3072
0.224
1.372  |      |**    | 
0.153
       14 
9.4934
9.2692
0.0961
0.2242
0.222
1.012  |      |**    | 
0.096
       15 
9.1394
9.2092
0.0874
-0.0698
0.225
-0.310  |      |      | 
0.007
       16 
8.9364
8.9979
0.0644
-0.0615
0.233
-0.264  |      |      | 
0.003
 Sum of Residuals 
0
 Sum of Squared Residuals 
0.81613
 Predicted Residual SS (PRESS) 1.13316


11:31 Monday, February 12, 2018
20
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M8
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:31 Monday, February 12, 2018
20
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M8
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=11 Param=lnAUCinf
 Number of Observations Read 16
 Number of Observations Used 16
Analysis of Variance
Source
DF Sum of
Squares
Mean
Square
F Value Pr > F
 Model 
1 3.66660 3.66660
88.90 <.0001
 Error 
14 0.57744 0.04125
 Corrected Total 15 4.24404
 Root MSE 
0.20309  R-Square 0.8639
 Dependent Mean 9.23645  Adj R-Sq 0.8542
 Coeff Var 
2.19880    
Parameter Estimates
Variable
Label
DF Parameter
Estimate
Standard
Error
t Value Pr > |t|
95%
Confidence
Limits
 Intercept Intercept
1
10.01334
0.09679
103.46
<.0001
9.80576 10.22093
 CrCL 
CrCL
1
-0.00909 0.00096417
-9.43
<.0001 -0.01116 -0.00702


11:31 Monday, February 12, 2018
21
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M8
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:31 Monday, February 12, 2018
21
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M8
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=11 Param=lnAUCinf
Output Statistics
Obs
Dependent
Variable
Predicted
Value
Std Error
Mean Predict
Residual Std Error
Residual
Student
Residual
-2-1 0 1 2
Cook's
D
        1 
8.8900
8.5238
0.0911
0.3661
0.182
2.017  |      |****  | 
0.512
        2 
8.8077
8.6239
0.0825
0.1838
0.186
0.990  |      |*     | 
0.097
        3 
8.9962
9.1002
0.0528
-0.1040
0.196
-0.530  |     *|      | 
0.010
        4 
8.9657
8.8830
0.0631
0.0827
0.193
0.428  |      |      | 
0.010
        5 
8.1592
8.6027
0.0842
-0.4435
0.185
-2.400  |  ****|      | 
0.598
        6 
8.7931
8.9208
0.0608
-0.1277
0.194
-0.659  |     *|      | 
0.021
        7 
8.8867
8.9553
0.0589
-0.0686
0.194
-0.353  |      |      | 
0.006
        8 
8.7311
8.6737
0.0784
0.0574
0.187
0.306  |      |      | 
0.008
        9 
9.6400
9.6489
0.0670 -0.008855
0.192
-0.0462  |      |      | 
0.000
       10 
9.6326
9.7451
0.0741
-0.1125
0.189
-0.595  |     *|      | 
0.027
       11 
9.3973
9.6163
0.0648
-0.2190
0.192
-1.138  |    **|      | 
0.073
       12 
9.6409
9.7386
0.0736
-0.0978
0.189
-0.516  |     *|      | 
0.020
       13 
9.9585
9.7688
0.0759
0.1897
0.188
1.007  |      |**    | 
0.082
       14 
10.0793
9.8291
0.0808
0.2502
0.186
1.343  |      |**    | 
0.170
       15 
9.7832
9.7376
0.0735
0.0455
0.189
0.241  |      |      | 
0.004
       16 
9.4220
9.4154
0.0542
0.006507
0.196
0.0332  |      |      | 
0.000
 Sum of Residuals 
0
 Sum of Squared Residuals 
0.57744
 Predicted Residual SS (PRESS) 0.82485


11:31 Monday, February 12, 2018
22
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M8
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:31 Monday, February 12, 2018
22
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M8
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=12 Param=lnAe
 Number of Observations Read 16
 Number of Observations Used 16
Analysis of Variance
Source
DF Sum of
Squares
Mean
Square
F Value Pr > F
 Model 
1 1.93556 1.93556
27.71 0.0001
 Error 
14 0.97775 0.06984
 Corrected Total 15 2.91332
 Root MSE 
0.26427  R-Square 0.6644
 Dependent Mean 4.11772  Adj R-Sq 0.6404
 Coeff Var 
6.41791    
Parameter Estimates
Variable
Label
DF Parameter
Estimate
Standard
Error
t Value Pr > |t|
95%
Confidence
Limits
 Intercept Intercept
1
3.55326
0.12594
28.21
<.0001 3.28314 3.82338
 CrCL 
CrCL
1
0.00660
0.00125
5.26
0.0001 0.00391 0.00930


11:31 Monday, February 12, 2018
23
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M8
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:31 Monday, February 12, 2018
23
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M8
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=12 Param=lnAe
Output Statistics
Obs
Dependent
Variable
Predicted
Value
Std Error
Mean Predict
Residual Std Error
Residual
Student
Residual
-2-1 0 1 2
Cook's
D
        1 
4.4617
4.6355
0.1185
-0.1738
0.236
-0.736  |     *|      | 
0.068
        2 
4.4303
4.5628
0.1073
-0.1325
0.242
-0.549  |     *|      | 
0.030
        3 
4.7125
4.2167
0.0687
0.4958
0.255
1.943  |      |***   | 
0.137
        4 
4.3181
4.3745
0.0821
-0.0564
0.251
-0.225  |      |      | 
0.003
        5 
4.2886
4.5782
0.1096
-0.2896
0.240
-1.204  |    **|      | 
0.151
        6 
4.7398
4.3470
0.0791
0.3928
0.252
1.558  |      |***   | 
0.119
        7 
4.5397
4.3220
0.0766
0.2177
0.253
0.861  |      |*     | 
0.034
        8 
4.5385
4.5266
0.1020
0.0119
0.244
0.0489  |      |      | 
0.000
        9 
3.3408
3.8181
0.0872
-0.4773
0.249
-1.913  |   ***|      | 
0.224
       10 
3.7326
3.7482
0.0964
-0.0155
0.246
-0.0631  |      |      | 
0.000
       11 
3.6920
3.8418
0.0843
-0.1497
0.250
-0.598  |     *|      | 
0.020
       12 
3.8748
3.7529
0.0958
0.1219
0.246
0.495  |      |      | 
0.019
       13 
4.0153
3.7309
0.0988
0.2844
0.245
1.160  |      |**    | 
0.109
       14 
3.4983
3.6871
0.1051
-0.1888
0.242
-0.779  |     *|      | 
0.057
       15 
3.8129
3.7536
0.0957
0.0593
0.246
0.241  |      |      | 
0.004
       16 
3.8875
3.9877
0.0705
-0.1001
0.255
-0.393  |      |      | 
0.006
 Sum of Residuals 
0
 Sum of Squared Residuals 
0.97775
 Predicted Residual SS (PRESS) 1.23480


11:31 Monday, February 12, 2018
24
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M8
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:31 Monday, February 12, 2018
24
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M8
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=13 Param=lnLambda_z
 Number of Observations Read 16
 Number of Observations Used 16
Analysis of Variance
Source
DF Sum of
Squares
Mean
Square
F Value Pr > F
 Model 
1 1.58129 1.58129
15.19 0.0016
 Error 
14 1.45699 0.10407
 Corrected Total 15 3.03829
 Root MSE 
0.32260  R-Square 0.5205
 Dependent Mean -3.34307  Adj R-Sq 0.4862
 Coeff Var 
-9.64981    
Parameter Estimates
Variable
Label
DF Parameter
Estimate
Standard
Error
t Value Pr > |t|
95%
Confidence
Limits
 Intercept Intercept
1
-3.85327
0.15374
-25.06
<.0001 -4.18300 -3.52353
 CrCL 
CrCL
1
0.00597
0.00153
3.90
0.0016
0.00269
0.00925


11:31 Monday, February 12, 2018
25
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M8
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:31 Monday, February 12, 2018
25
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M8
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=13 Param=lnLambda_z
Output Statistics
Obs
Dependent
Variable
Predicted
Value
Std Error
Mean Predict
Residual Std Error
Residual
Student
Residual
-2-1 0 1 2
Cook's
D
        1 
-3.1863
-2.8751
0.1446
-0.3112
0.288
-1.079  |    **|      | 
0.146
        2 
-3.0317
-2.9408
0.1310
-0.0909
0.295
-0.308  |      |      | 
0.009
        3 
-2.7695
-3.2536
0.0839
0.4841
0.312
1.554  |      |***   | 
0.087
        4 
-2.7397
-3.1110
0.1003
0.3713
0.307
1.211  |      |**    | 
0.078
        5 
-3.4693
-2.9268
0.1338
-0.5425
0.294
-1.848  |   ***|      | 
0.355
        6 
-2.6258
-3.1358
0.0966
0.5100
0.308
1.657  |      |***   | 
0.135
        7 
-2.8558
-3.1584
0.0935
0.3027
0.309
0.980  |      |*     | 
0.044
        8 
-3.0610
-2.9735
0.1245
-0.0874
0.298
-0.294  |      |      | 
0.008
        9 
-4.0370
-3.6139
0.1065
-0.4231
0.305
-1.389  |    **|      | 
0.118
       10 
-3.5983
-3.6771
0.1177
0.0788
0.300
0.262  |      |      | 
0.005
       11 
-3.7360
-3.5925
0.1030
-0.1435
0.306
-0.469  |      |      | 
0.012
       12 
-3.5042
-3.6729
0.1169
0.1687
0.301
0.561  |      |*     | 
0.024
       13 
-3.5647
-3.6927
0.1206
0.1280
0.299
0.428  |      |      | 
0.015
       14 
-3.8262
-3.7323
0.1283
-0.0939
0.296
-0.317  |      |      | 
0.009
       15 
-3.8977
-3.6722
0.1168
-0.2255
0.301
-0.750  |     *|      | 
0.042
       16 
-3.5861
-3.4606
0.0861
-0.1255
0.311
-0.404  |      |      | 
0.006
 Sum of Residuals 
0
 Sum of Squared Residuals 
1.45699
 Predicted Residual SS (PRESS) 1.88199


11:31 Monday, February 12, 2018
26
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M8
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:31 Monday, February 12, 2018
26
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M8
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=14 Param=RkTmax
 Number of Observations Read 16
 Number of Observations Used 16
Analysis of Variance
Source
DF
Sum of
Squares
Mean
Square
F Value Pr > F
 Model 
1
0.51068
0.51068
0.02 0.8847
 Error 
14 327.98932 23.42781
 Corrected Total 15 328.50000
 Root MSE 
4.84023  R-Square 
0.0016
 Dependent Mean 
8.50000  Adj R-Sq -0.0698
 Coeff Var 
56.94386    
Parameter Estimates
Variable
Label
DF Parameter
Estimate
Standard
Error
t Value Pr > |t|
95%
Confidence
Limits
 Intercept Intercept
1
8.78994
2.30666
3.81
0.0019
3.84264 13.73724
 CrCL 
CrCL
1
-0.00339
0.02298
-0.15
0.8847 -0.05268
0.04589


11:31 Monday, February 12, 2018
27
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M8
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:31 Monday, February 12, 2018
27
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M8
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=14 Param=RkTmax
Output Statistics
Obs
Dependent
Variable
Predicted
Value
Std Error
Mean Predict
Residual Std Error
Residual
Student
Residual
-2-1 0 1 2
Cook's
D
        1 
6.5000
8.2340
2.1700
-1.7340
4.327
-0.401  |      |      | 
0.020
        2 
9.5000
8.2714
1.9651
1.2286
4.423
0.278  |      |      | 
0.008
        3 
9.5000
8.4491
1.2581
1.0509
4.674
0.225  |      |      | 
0.002
        4 
6.5000
8.3681
1.5041
-1.8681
4.601
-0.406  |      |      | 
0.009
        5 
1.5000
8.2635
2.0077
-6.7635
4.404
-1.536  |   ***|      | 
0.245
        6 
9.5000
8.3822
1.4494
1.1178
4.618
0.242  |      |      | 
0.003
        7 
14.5000
8.3951
1.4033
6.1049
4.632
1.318  |      |**    | 
0.080
        8 
9.5000
8.2900
1.8675
1.2100
4.465
0.271  |      |      | 
0.006
        9 
3.5000
8.6539
1.5972
-5.1539
4.569
-1.128  |    **|      | 
0.078
       10 
5.0000
8.6898
1.7656
-3.6898
4.507
-0.819  |     *|      | 
0.051
       11 
12.0000
8.6417
1.5447
3.3583
4.587
0.732  |      |*     | 
0.030
       12 
14.5000
8.6874
1.7537
5.8126
4.511
1.288  |      |**    | 
0.125
       13 
14.5000
8.6987
1.8097
5.8013
4.489
1.292  |      |**    | 
0.136
       14 
1.5000
8.7212
1.9257
-7.2212
4.441
-1.626  |   ***|      | 
0.249
       15 
3.5000
8.6870
1.7519
-5.1870
4.512
-1.150  |    **|      | 
0.100
       16 
14.5000
8.5668
1.2919
5.9332
4.665
1.272  |      |**    | 
0.062
 Sum of Residuals 
0
 Sum of Squared Residuals 
327.98932
 Predicted Residual SS (PRESS) 432.94522


11:31 Monday, February 12, 2018
28
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M8
(Healthy vs Severe)
ANOVA analysis
NON-PARAMETRIC TEST OF FIXED EFFECT for Tmax parameter
--------------------- SUMMARY REPORT ---------------------
The NPAR1WAY Procedure
11:31 Monday, February 12, 2018
28
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M8
(Healthy vs Severe)
ANOVA analysis
NON-PARAMETRIC TEST OF FIXED EFFECT for Tmax parameter
--------------------- SUMMARY REPORT ---------------------
The NPAR1WAY Procedure
Wilcoxon Scores (Rank Sums) for Variable Value
Classified by Variable Group
Group
N
Sum of
Scores
Expected
Under H0
Std Dev
Under H0
Mean
Score
 1 
8
67.0
68.0 9.359487
8.3750
 2 
8
69.0
68.0 9.359487
8.6250
Average scores were used for ties.
Wilcoxon Two-Sample Test
 Statistic 
67.0000
   
 Normal Approximation 
 Z 
-0.0534
 One-Sided Pr <  Z 
0.4787
 Two-Sided Pr > |Z| 
0.9574
   
 t Approximation 
 One-Sided Pr <  Z 
0.4791
 Two-Sided Pr > |Z| 
0.9581
Z includes a continuity correction of 0.5.
Kruskal-Wallis Test
 Chi-Square 
0.0114
 DF 
1
 Pr > Chi-Square 
0.9149
Hodges-Lehmann Estimation
Location Shift (1 - 2)    0.0000
Type
90%
Confidence
Limits
Interval
Midpoint
Asymptotic
Standard Error
 Asymptotic (Moses) -3.5000 1.5000
-1.0000
1.5199
 Exact 
-3.5000 1.5000
-1.0000


10:17 Monday, January 22, 2018
1
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M8 - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
RAW DATA
--------------------- SUMMARY REPORT ---------------------
10:17 Monday, January 22, 2018
1
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M8 - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
RAW DATA
--------------------- SUMMARY REPORT ---------------------
Renal Function Group=Normal
Obs Subject
Cmax
Tmax
AUCT
Thalf
Ae
AUCinf
Res_Area Lambda_z lnCmax
lnAUCT
 1 101
418.00000 2.00000 5781.92500 16.77310
86.63720 7258.77076 20.34567
0.04132 6.03548 8.66249
 2 102
292.00000 2.50000 5449.00000 14.37083
83.95300 6685.55732 18.49595
0.04823 5.67675 8.60319
 3 103
527.00000 2.50000 7332.65000 11.05589 111.32950 8072.40389
9.16399
0.06269 6.26720 8.90009
 4 104
482.00000 2.00000 7017.30800 10.73134
75.04500 7829.60165 10.37465
0.06459 6.17794 8.85613
 5 105
276.00000 0.75000 2600.95000 22.26073
72.86400 3495.21568 25.58542
0.03114 5.62040 7.86363
 6 106
587.00000 2.50000 6180.57500
9.57655 114.41100 6588.78200
6.19549
0.07238 6.37502 8.72917
 7 107
368.00000 6.00000 6280.01000 12.05213
93.66040 7234.85257 13.19782
0.05751 5.90808 8.74513
 8 108
305.00000 2.50000 5063.21950 14.79742
93.54840 6192.57687 18.23728
0.04684 5.72031 8.52976
Obs lnAUCinf
lnAe
lnLambda_z RkTmax
eGFR
CrCL
 1 
8.8900 4.46173
-3.18629
6.5 115.00000 163.85000
 2 
8.8077 4.43026
-3.03171
9.5 102.00000 152.84000
 3 
8.9962 4.71249
-2.76948
9.5
94.00000 100.45000
 4 
8.9657 4.31809
-2.73968
6.5 109.00000 124.34000
 5 
8.1592 4.28859
-3.46934
1.5 102.00000 155.18000
 6 
8.7931 4.73980
-2.62583
9.5 116.00000 120.18000
 7 
8.8867 4.53968
-2.85575
14.5
98.00000 116.39000
 8 
8.7311 4.53848
-3.06097
9.5 118.00000 147.36000


10:17 Monday, January 22, 2018
2
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M8 - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
RAW DATA
--------------------- SUMMARY REPORT ---------------------
10:17 Monday, January 22, 2018
2
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M8 - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
RAW DATA
--------------------- SUMMARY REPORT ---------------------
Renal Function Group=Severe
Obs Subject
Cmax
Tmax
AUCT
Thalf
Ae
AUCinf
Res_Area Lambda_z lnCmax
 9 013-01
470.00000 1.75000
9428.50000 25.32404 41.78940 15253.32387 38.18724
0.02737 6.15273
 10 013-02
659.00000 6.00000 13860.92500 24.48850 55.44030 21130.95349 34.40464
0.02831 6.49072
 11 013-03
310.00000 4.00000
6700.17250 29.06330 40.12630 12055.64869 44.42296
0.02385 5.73657
 12 013-04
331.00000 6.00000
7604.02333 25.01790 48.79000 12356.74154 38.46255
0.02771 5.80212
 13 013-05
849.00000 0.75000 13271.27500 31.80603 33.06085 23844.88619 44.34331
0.02179 6.74406
 14 013-06
358.00000 1.00000
7425.10000 39.27202 28.24120 15368.01449 51.68471
0.01765 5.88053
 15 013-07
417.00000 6.00000 10078.39167 23.04963 48.17324 15380.50680 34.47295
0.03007 6.03309
 16 013-08
453.00000 1.00000
9315.07500 34.16493 45.28310 17732.59498 47.46919
0.02029 6.11589
Obs
lnAUCT lnAUCinf
lnAe
lnLambda_z RkTmax
eGFR
CrCL
 9 9.15149
9.6326 3.73264
-3.59827
5.0 23.00000 29.51000
 10 9.53683
9.9585 4.01531
-3.56472
14.5 27.00000 26.90000
 11 8.80989
9.3973 3.69203
-3.73599
12.0 26.00000 43.68000
 12 8.93643
9.4220 3.88753
-3.58610
14.5 28.00000 65.77000
 13 9.49336
10.0793 3.49835
-3.82617
1.5 16.00000 20.27000
 14 8.91262
9.6400 3.34078
-4.03703
3.5 26.00000 40.09000
 15 9.21815
9.6409 3.87480
-3.50416
14.5 19.00000 30.22000
 16 9.13939
9.7832 3.81293
-3.89771
3.5 21.00000 30.33000


10:17 Monday, January 22, 2018
3
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M8 - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
DESCRIPTIVE RESULTS (OVERALL)
--------------------- SUMMARY REPORT ---------------------
10:17 Monday, January 22, 2018
3
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M8 - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
DESCRIPTIVE RESULTS (OVERALL)
--------------------- SUMMARY REPORT ---------------------
Parameter
Renal
Function
Group
n
Min
Mean
Geometric
Mean
Median
Max
Standard
Deviation
Coefficient
of
Variation
Cmax
Normal
8
276.00000
406.87500
392.54455
393.00000
587.00000
116.40869
28.6104
Cmax
Severe
8
310.00000
480.87500
454.62126
435.00000
849.00000
184.76969
38.4236
Tmax
Normal
8
0.75000
2.59375
2.26923
2.50000
6.00000
1.49963
57.8170
Tmax
Severe
8
0.75000
3.31250
2.40894
2.87500
6.00000
2.44493
73.8092
AUCT
Normal
8 2600.95000 5713.20469
5492.82916 5981.25000 7332.65000 1466.09922
25.6616
AUCT
Severe
8 6700.17250 9710.43281
9412.27480 9371.78750 13860.9250 2645.71741
27.2461
Thalf
Normal
8
9.57655
13.95225
13.47543
13.21148
22.26073
4.12999
29.6009
Thalf
Severe
8
23.04963
29.02329
28.56709
27.19367
39.27202
5.67192
19.5427
Ae
Normal
8
72.86400
91.43106
90.34533
90.09280
114.41100
15.23914
16.6674
Ae
Severe
8
28.24120
42.61305
41.75407
43.53625
55.44030
8.82686
20.7140
AUCinf
Normal
8 3495.21568 6669.72009
6494.42091 6960.20495 8072.40389 1428.84310
21.4228
AUCinf
Severe
8 12055.6487 16640.3338 16223.39570 15374.2606 23844.8862 4101.61174
24.6486
Res_Area
Normal
8
6.19549
15.19953
13.86411
15.71755
25.58542
6.53814
43.0154
Res_Area
Severe
8
34.40464
41.68095
41.27221
41.40293
51.68471
6.27523
15.0554
Lambda_z
Normal
8
0.03114
0.05309
0.05144
0.05287
0.07238
0.01362
25.6606
Lambda_z
Severe
8
0.01765
0.02463
0.02426
0.02561
0.03007
0.00441
17.9180
lnCmax
Normal
8
5.62040
5.97265
5.97178
6.37502
0.28642
4.7954
lnCmax
Severe
8
5.73657
6.11946
6.07449
6.74406
0.34660
5.6639
lnAUCT
Normal
8
7.86363
8.61120
8.69583
8.90009
0.32590
3.7846
lnAUCT
Severe
8
8.80989
9.14977
9.14544
9.53683
0.26455
2.8914
lnAUCinf
Normal
8
8.15915
8.77870
8.84719
8.99621
0.26551
3.0244
lnAUCinf
Severe
8
9.39729
9.69421
9.64045
10.07933
0.23843
2.4595
lnAe
Normal
8
4.28859
4.50364
4.50010
4.73980
0.16463
3.6555
lnAe
Severe
8
3.34078
3.73180
3.77279
4.01531
0.22060
5.9112
lnLambda_z Normal
8
-3.46934
-2.96738
-2.94373
-2.62583
0.27592
-9.2983
lnLambda_z Severe
8
-4.03703
-3.71877
-3.66713
-3.50416
0.18786
-5.0518
RkTmax
Normal
8
1.50000
8.37500
7.23224
9.50000
14.50000
3.72012
44.4193
RkTmax
Severe
8
1.50000
8.62500
6.54350
8.50000
14.50000
5.74922
66.6577


10:17 Monday, January 22, 2018
4
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M8 - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
--------------------- SUMMARY REPORT ---------------------
The Mixed Procedure
10:17 Monday, January 22, 2018
4
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M8 - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
--------------------- SUMMARY REPORT ---------------------
The Mixed Procedure
Order=1 Param=Cmax
Model Information
 Data Set 
WORK.KINDATA
 Dependent Variable 
Value
 Covariance Structure 
Variance Components
 Group Effect 
FunctionGroup
 Estimation Method 
REML
 Residual Variance Method 
None
 Fixed Effects SE Method 
Model-Based
 Degrees of Freedom Method Between-Within
Class Level Information
Class
Levels
Values
 FunctionGroup 
2 Severe Normal
Dimensions
 Covariance Parameters 
2
 Columns in X 
3
 Columns in Z 
0
 Subjects 
16
 Max Obs per Subject 
1
Number of Observations
 Number of Observations Read 
16
 Number of Observations Used 
16
 Number of Observations Not Used 
0
Iteration History
Iteration Evaluations -2 Res Log Like Criterion
      0 
1
185.00002078
      1 
1
183.55620418 0.00000000
Convergence criteria met.
Covariance Parameter Estimates
Cov Parm
Group
Estimate
 Residual FunctionGroup Severe
34140
 Residual FunctionGroup Normal
13551
Fit Statistics
 -2 Res Log Likelihood 
183.6
 AIC (Smaller is Better) 
187.6
 AICC (Smaller is Better) 188.6
 BIC (Smaller is Better) 
189.1
Null Model Likelihood
Ratio Test
DF
Chi-Square Pr > ChiSq
1
1.44
0.2295
Type 3 Tests of Fixed Effects
Effect
Num
DF
Den
DF
F Value Pr > F
 FunctionGroup 
1
14
0.92 0.3541
Least Squares Means
Effect
Renal
Function
Group
Estimate Standard
Error
DF t Value Pr > |t| Alpha
Lower
Upper
 FunctionGroup Severe
480.88
65.3260 14
7.36
<.0001
0.1 365.82 595.93
 FunctionGroup Normal
406.88
41.1567 14
9.89
<.0001
0.1 334.39 479.36
Differences of Least Squares Means
Effect
Renal
Function
Group
Renal
Function
Group
Estimate Standard
Error
DF t Value Pr > |t| Alpha
Lower
Upper
 FunctionGroup Severe
Normal
74.0000
77.2098 14
0.96
0.3541
0.1 -61.9904 209.99


10:17 Monday, January 22, 2018
5
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M8 - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
--------------------- SUMMARY REPORT ---------------------
The Mixed Procedure
10:17 Monday, January 22, 2018
5
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M8 - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
--------------------- SUMMARY REPORT ---------------------
The Mixed Procedure
Order=3 Param=AUCT
Model Information
 Data Set 
WORK.KINDATA
 Dependent Variable 
Value
 Covariance Structure 
Variance Components
 Group Effect 
FunctionGroup
 Estimation Method 
REML
 Residual Variance Method 
None
 Fixed Effects SE Method 
Model-Based
 Degrees of Freedom Method Between-Within
Class Level Information
Class
Levels
Values
 FunctionGroup 
2 Severe Normal
Dimensions
 Covariance Parameters 
2
 Columns in X 
3
 Columns in Z 
0
 Subjects 
16
 Max Obs per Subject 
1
Number of Observations
 Number of Observations Read 
16
 Number of Observations Used 
16
 Number of Observations Not Used 
0
Iteration History
Iteration Evaluations -2 Res Log Like Criterion
      0 
1
258.59368283
      1 
1
256.28397540 0.00000000
Convergence criteria met.
Covariance Parameter Estimates
Cov Parm
Group
Estimate
 Residual FunctionGroup Severe
6999821
 Residual FunctionGroup Normal
2149447
Fit Statistics
 -2 Res Log Likelihood 
256.3
 AIC (Smaller is Better) 
260.3
 AICC (Smaller is Better) 261.4
 BIC (Smaller is Better) 
261.8
Null Model Likelihood
Ratio Test
DF
Chi-Square Pr > ChiSq
1
2.31
0.1286
Type 3 Tests of Fixed Effects
Effect
Num
DF
Den
DF
F Value Pr > F
 FunctionGroup 
1
14
13.97 0.0022
Least Squares Means
Effect
Renal
Function
Group
Estimate Standard
Error
DF t Value Pr > |t| Alpha
Lower
Upper
 FunctionGroup Severe
9710.43
935.40 14
10.38
<.0001
0.1 8062.90
11358
 FunctionGroup Normal
5713.20
518.34 14
11.02
<.0001
0.1 4800.24 6626.17
Differences of Least Squares Means
Effect
Renal
Function
Group
Renal
Function
Group
Estimate Standard
Error
DF t Value Pr > |t| Alpha
Lower
Upper
 FunctionGroup Severe
Normal
3997.23
1069.42 14
3.74
0.0022
0.1 2113.65 5880.81


10:17 Monday, January 22, 2018
6
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M8 - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
--------------------- SUMMARY REPORT ---------------------
The Mixed Procedure
10:17 Monday, January 22, 2018
6
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M8 - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
--------------------- SUMMARY REPORT ---------------------
The Mixed Procedure
Order=6 Param=AUCinf
Model Information
 Data Set 
WORK.KINDATA
 Dependent Variable 
Value
 Covariance Structure 
Variance Components
 Group Effect 
FunctionGroup
 Estimation Method 
REML
 Residual Variance Method 
None
 Fixed Effects SE Method 
Model-Based
 Degrees of Freedom Method Between-Within
Class Level Information
Class
Levels
Values
 FunctionGroup 
2 Severe Normal
Dimensions
 Covariance Parameters 
2
 Columns in X 
3
 Columns in Z 
0
 Subjects 
16
 Max Obs per Subject 
1
Number of Observations
 Number of Observations Read 
16
 Number of Observations Used 
16
 Number of Observations Not Used 
0
Iteration History
Iteration Evaluations -2 Res Log Like Criterion
      0 
1
268.72442632
      1 
1
262.06174118 0.00000000
Convergence criteria met.
Covariance Parameter Estimates
Cov Parm
Group
Estimate
 Residual FunctionGroup Severe 16823219
 Residual FunctionGroup Normal
2041593
Fit Statistics
 -2 Res Log Likelihood 
262.1
 AIC (Smaller is Better) 
266.1
 AICC (Smaller is Better) 267.2
 BIC (Smaller is Better) 
267.6
Null Model Likelihood
Ratio Test
DF
Chi-Square Pr > ChiSq
1
6.66
0.0098
Type 3 Tests of Fixed Effects
Effect
Num
DF
Den
DF
F Value Pr > F
 FunctionGroup 
1
14
42.16 <.0001
Least Squares Means
Effect
Renal
Function
Group
Estimate Standard
Error
DF t Value Pr > |t| Alpha
Lower
Upper
 FunctionGroup Severe
16640
1450.14 14
11.47
<.0001
0.1
14086
19194
 FunctionGroup Normal
6669.72
505.17 14
13.20
<.0001
0.1 5779.95 7559.49
Differences of Least Squares Means
Effect
Renal
Function
Group
Renal
Function
Group
Estimate Standard
Error
DF t Value Pr > |t| Alpha
Lower Upper
 FunctionGroup Severe
Normal
9970.61
1535.61 14
6.49
<.0001
0.1 7265.93 12675


10:17 Monday, January 22, 2018
7
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M8 - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
--------------------- SUMMARY REPORT ---------------------
The Mixed Procedure
10:17 Monday, January 22, 2018
7
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M8 - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
--------------------- SUMMARY REPORT ---------------------
The Mixed Procedure
Order=9 Param=lnCmax
Model Information
 Data Set 
WORK.KINDATA
 Dependent Variable 
Value
 Covariance Structure 
Variance Components
 Group Effect 
FunctionGroup
 Estimation Method 
REML
 Residual Variance Method 
None
 Fixed Effects SE Method 
Model-Based
 Degrees of Freedom Method Between-Within
Class Level Information
Class
Levels
Values
 FunctionGroup 
2 Severe Normal
Dimensions
 Covariance Parameters 
2
 Columns in X 
3
 Columns in Z 
0
 Subjects 
16
 Max Obs per Subject 
1
Number of Observations
 Number of Observations Read 
16
 Number of Observations Used 
16
 Number of Observations Not Used 
0
Iteration History
Iteration Evaluations -2 Res Log Like Criterion
      0 
1
11.80387731
      1 
1
11.55074238 0.00000000
Convergence criteria met.
Covariance Parameter Estimates
Cov Parm
Group
Estimate
 Residual FunctionGroup Severe
0.1201
 Residual FunctionGroup Normal
0.08203
Fit Statistics
 -2 Res Log Likelihood 
11.6
 AIC (Smaller is Better) 
15.6
 AICC (Smaller is Better) 
16.6
 BIC (Smaller is Better) 
17.1
Null Model Likelihood
Ratio Test
DF
Chi-Square Pr > ChiSq
1
0.25
0.6149
Type 3 Tests of Fixed Effects
Effect
Num
DF
Den
DF
F Value Pr > F
 FunctionGroup 
1
14
0.85 0.3714
Least Squares Means
Effect
Renal
Function
Group
Estimate Standard
Error
DF t Value Pr > |t| Alpha
Lower
Upper
 FunctionGroup Severe
6.1195
0.1225 14
49.94
<.0001
0.1 5.9036 6.3353
 FunctionGroup Normal
5.9727
0.1013 14
58.98
<.0001
0.1 5.7943 6.1510
Differences of Least Squares Means
Effect
Renal
Function
Group
Renal
Function
Group
Estimate Standard
Error
DF t Value Pr > |t| Alpha
Lower
Upper
 FunctionGroup Severe
Normal
0.1468
0.1590 14
0.92
0.3714
0.1 -0.1332 0.4268


10:17 Monday, January 22, 2018
8
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M8 - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
--------------------- SUMMARY REPORT ---------------------
The Mixed Procedure
10:17 Monday, January 22, 2018
8
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M8 - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
--------------------- SUMMARY REPORT ---------------------
The Mixed Procedure
Order=10 Param=lnAUCT
Model Information
 Data Set 
WORK.KINDATA
 Dependent Variable 
Value
 Covariance Structure 
Variance Components
 Group Effect 
FunctionGroup
 Estimation Method 
REML
 Residual Variance Method 
None
 Fixed Effects SE Method 
Model-Based
 Degrees of Freedom Method Between-Within
Class Level Information
Class
Levels
Values
 FunctionGroup 
2 Severe Normal
Dimensions
 Covariance Parameters 
2
 Columns in X 
3
 Columns in Z 
0
 Subjects 
16
 Max Obs per Subject 
1
Number of Observations
 Number of Observations Read 
16
 Number of Observations Used 
16
 Number of Observations Not Used 
0
Iteration History
Iteration Evaluations -2 Res Log Like Criterion
      0 
1
9.87937378
      1 
1
9.57709878 0.00000000
Convergence criteria met.
Covariance Parameter Estimates
Cov Parm
Group
Estimate
 Residual FunctionGroup Severe
0.06999
 Residual FunctionGroup Normal
0.1062
Fit Statistics
 -2 Res Log Likelihood 
9.6
 AIC (Smaller is Better) 
13.6
 AICC (Smaller is Better) 
14.7
 BIC (Smaller is Better) 
15.1
Null Model Likelihood
Ratio Test
DF
Chi-Square Pr > ChiSq
1
0.30
0.5825
Type 3 Tests of Fixed Effects
Effect
Num
DF
Den
DF
F Value Pr > F
 FunctionGroup 
1
14
13.17 0.0027
Least Squares Means
Effect
Renal
Function
Group
Estimate Standard
Error
DF t Value Pr > |t| Alpha
Lower
Upper
 FunctionGroup Severe
9.1498
0.09353 14
97.82
<.0001
0.1 8.9850 9.3145
 FunctionGroup Normal
8.6112
0.1152 14
74.73
<.0001
0.1 8.4083 8.8141
Differences of Least Squares Means
Effect
Renal
Function
Group
Renal
Function
Group
Estimate Standard
Error
DF t Value Pr > |t| Alpha
Lower
Upper
 FunctionGroup Severe
Normal
0.5386
0.1484 14
3.63
0.0027
0.1 0.2772 0.8000


10:17 Monday, January 22, 2018
9
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M8 - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
--------------------- SUMMARY REPORT ---------------------
The Mixed Procedure
10:17 Monday, January 22, 2018
9
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M8 - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
--------------------- SUMMARY REPORT ---------------------
The Mixed Procedure
Order=11 Param=lnAUCinf
Model Information
 Data Set 
WORK.KINDATA
 Dependent Variable 
Value
 Covariance Structure 
Variance Components
 Group Effect 
FunctionGroup
 Estimation Method 
REML
 Residual Variance Method 
None
 Fixed Effects SE Method 
Model-Based
 Degrees of Freedom Method Between-Within
Class Level Information
Class
Levels
Values
 FunctionGroup 
2 Severe Normal
Dimensions
 Covariance Parameters 
2
 Columns in X 
3
 Columns in Z 
0
 Subjects 
16
 Max Obs per Subject 
1
Number of Observations
 Number of Observations Read 
16
 Number of Observations Used 
16
 Number of Observations Not Used 
0
Iteration History
Iteration Evaluations -2 Res Log Like Criterion
      0 
1
5.33283729
      1 
1
5.25199201 0.00000000
Convergence criteria met.
Covariance Parameter Estimates
Cov Parm
Group
Estimate
 Residual FunctionGroup Severe
0.05685
 Residual FunctionGroup Normal
0.07049
Fit Statistics
 -2 Res Log Likelihood 
5.3
 AIC (Smaller is Better) 
9.3
 AICC (Smaller is Better) 
10.3
 BIC (Smaller is Better) 
10.8
Null Model Likelihood
Ratio Test
DF
Chi-Square Pr > ChiSq
1
0.08
0.7762
Type 3 Tests of Fixed Effects
Effect
Num
DF
Den
DF
F Value Pr > F
 FunctionGroup 
1
14
52.66 <.0001
Least Squares Means
Effect
Renal
Function
Group
Estimate Standard
Error
DF t Value Pr > |t| Alpha
Lower
Upper
 FunctionGroup Severe
9.6942
0.08430 14
115.00
<.0001
0.1 9.5457 9.8427
 FunctionGroup Normal
8.7787
0.09387 14
93.52
<.0001
0.1 8.6134 8.9440
Differences of Least Squares Means
Effect
Renal
Function
Group
Renal
Function
Group
Estimate Standard
Error
DF t Value Pr > |t| Alpha
Lower
Upper
 FunctionGroup Severe
Normal
0.9155
0.1262 14
7.26
<.0001
0.1 0.6933 1.1377


10:17 Monday, January 22, 2018
10
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M8 - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
--------------------- SUMMARY REPORT ---------------------
The Mixed Procedure
10:17 Monday, January 22, 2018
10
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M8 - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
--------------------- SUMMARY REPORT ---------------------
The Mixed Procedure
Order=14 Param=RkTmax
Model Information
 Data Set 
WORK.KINDATA
 Dependent Variable 
Value
 Covariance Structure 
Variance Components
 Group Effect 
FunctionGroup
 Estimation Method 
REML
 Residual Variance Method 
None
 Fixed Effects SE Method 
Model-Based
 Degrees of Freedom Method Between-Within
Class Level Information
Class
Levels
Values
 FunctionGroup 
2 Severe Normal
Dimensions
 Covariance Parameters 
2
 Columns in X 
3
 Columns in Z 
0
 Subjects 
16
 Max Obs per Subject 
1
Number of Observations
 Number of Observations Read 
16
 Number of Observations Used 
16
 Number of Observations Not Used 
0
Iteration History
Iteration Evaluations -2 Res Log Like Criterion
      0 
1
88.05521658
      1 
1
86.76864874 0.00000000
Convergence criteria met.
Covariance Parameter Estimates
Cov Parm
Group
Estimate
 Residual FunctionGroup Severe
33.0536
 Residual FunctionGroup Normal
13.8393
Fit Statistics
 -2 Res Log Likelihood 
86.8
 AIC (Smaller is Better) 
90.8
 AICC (Smaller is Better) 
91.9
 BIC (Smaller is Better) 
92.3
Null Model Likelihood
Ratio Test
DF
Chi-Square Pr > ChiSq
1
1.29
0.2567
Type 3 Tests of Fixed Effects
Effect
Num
DF
Den
DF
F Value Pr > F
 FunctionGroup 
1
14
0.01 0.9192
Least Squares Means
Effect
Renal
Function
Group
Estimate Standard
Error
DF t Value Pr > |t| Alpha
Lower
Upper
 FunctionGroup Severe
8.6250
2.0327 14
4.24
0.0008
0.1 5.0449 12.2051
 FunctionGroup Normal
8.3750
1.3153 14
6.37
<.0001
0.1 6.0584 10.6916
Differences of Least Squares Means
Effect
Renal
Function
Group
Renal
Function
Group
Estimate Standard
Error
DF t Value Pr > |t| Alpha
Lower
Upper
 FunctionGroup Severe
Normal
0.2500
2.4211 14
0.10
0.9192
0.1 -4.0143 4.5143


10:17 Monday, January 22, 2018
11
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M8 - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
Geometric LSmeans
--------------------- SUMMARY REPORT ---------------------
10:17 Monday, January 22, 2018
11
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M8 - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
Geometric LSmeans
--------------------- SUMMARY REPORT ---------------------
Obs Parameters Group GeoLSmeans
 1 lnCmax
Severe
454.62
 2 lnCmax
Normal
392.54
 3 lnAUCT
Severe
9412.27
 4 lnAUCT
Normal
5492.83
 5 lnAUCinf
Severe
16223
 6 lnAUCinf
Normal
6494.42


10:17 Monday, January 22, 2018
12
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M8 - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
RATIO ESTIMATE BASED ON ln-TRANSFORMED PARAMETERS
--------------------- SUMMARY REPORT ---------------------
10:17 Monday, January 22, 2018
12
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M8 - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
RATIO ESTIMATE BASED ON ln-TRANSFORMED PARAMETERS
--------------------- SUMMARY REPORT ---------------------
Obs Parameters Group
vs
Group
Ratio
(%)
L90
U90
 1 lnCmax
Severe Normal 115.814
87.531 153.236
 2 lnAUCT
Severe Normal 171.356 131.940 222.546
 3 lnAUCinf
Severe Normal 249.805 200.029 311.967


Clinical Study Report  
Project No COL MIG-113/H8H-CD-LAHN 
 
16.1.9.4 Documentation of statistical analysis – SAS® output of (S,R)-M18 
 
Legend:  
AUCinf= AUC(0−∞) 
AUCT=AUC(0-tlast) 
Vz_F= VZ/F 
CL_F= CL/F 
LambdaZ = λZ 
lCmax= ln(Cmax) 
lAUCT= ln(AUC(0-tlast)) 
lAUCinf= ln(AUC(0−∞)) 
lCLF= ln(CL/F) 
lLambdaZ = ln(λZ) 
lVz_F= ln(VZ/F) 
RkTmax= Rank of Tmax 


11:11 Monday, February 12, 2018
1
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,R)-M18
(Healthy vs Severe)
ANOVA analysis
RAW DATA
--------------------- SUMMARY REPORT ---------------------
11:11 Monday, February 12, 2018
1
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,R)-M18
(Healthy vs Severe)
ANOVA analysis
RAW DATA
--------------------- SUMMARY REPORT ---------------------
Renal Function Group=Normal
Obs Subject
Cmax
Tmax
AUCT
Thalf
Ae
AUCinf
Res_Area Lambda_z lnCmax
lnAUCT
 1 101
65.40000 8.00000 1622.48750 14.31625 1.81632 2046.25114 20.70927
0.04842 4.18052 7.39172
 2 102
60.80000 8.00000 1421.13750 12.64878 1.79845 1712.48846 17.01331
0.05480 4.10759 7.25921
 3 103
89.90000 8.00000 1765.70500
8.55370 2.26527 1905.63475
7.34295
0.08103 4.49870 7.47631
 4 104
77.00000 8.00000 1578.40617
8.71141 1.59174 1717.79161
8.11422
0.07957 4.34381 7.36417
 5 105
34.50000 4.00000
629.62000 12.80730 0.70113
737.98538 14.68395
0.05412 3.54096 6.44512
 6 106
70.90000 4.00000 1267.15500
8.04806 1.79999 1351.60507
6.24813
0.08613 4.26127 7.14453
 7 107
69.10000 8.03333 1439.94250 10.72780 1.79353 1649.92717 12.72691
0.06461 4.23555 7.27236
 8 108
55.50000 8.00000 1336.16300 12.46407 1.43729 1629.00185 17.97658
0.05561 4.01638 7.19756
Obs lnAUCinf
lnAe
lnLambda_z RkTmax
eGFR
CrCL
 1 
7.62376
0.59681
-3.02791
8.0 115.00000 163.85000
 2 
7.44570
0.58692
-2.90407
8.0 102.00000 152.84000
 3 
7.55257
0.81769
-2.51288
8.0
94.00000 100.45000
 4 
7.44879
0.46483
-2.53115
8.0 109.00000 124.34000
 5 
6.60392 -0.35506
-2.91653
1.5 102.00000 155.18000
 6 
7.20905
0.58778
-2.45194
1.5 116.00000 120.18000
 7 
7.40849
0.58418
-2.73935
12.0
98.00000 116.39000
 8 
7.39572
0.36276
-2.88936
8.0 118.00000 147.36000


11:11 Monday, February 12, 2018
2
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,R)-M18
(Healthy vs Severe)
ANOVA analysis
RAW DATA
--------------------- SUMMARY REPORT ---------------------
11:11 Monday, February 12, 2018
2
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,R)-M18
(Healthy vs Severe)
ANOVA analysis
RAW DATA
--------------------- SUMMARY REPORT ---------------------
Renal Function Group=Severe
Obs Subject
Cmax
Tmax
AUCT
Thalf
Ae
AUCinf
Res_Area Lambda_z lnCmax
lnAUCT
 9 201
93.10000 12.00000 2726.85000 42.77174 0.58419 6704.18507 59.32615
0.01621 4.53367 7.91090
 10 202
68.30000
8.00000 1748.49750 24.77645 0.51524 2863.39423 38.93619
0.02798 4.22391 7.46651
 11 203
71.60000 12.00000 2002.04000 26.20845 1.48157 3518.28125 43.09608
0.02645 4.27110 7.60192
 12 204
132.00000 12.00000 3378.34583 18.65050 1.24216 4878.47360 30.74994
0.03717 4.88280 8.12514
 13 205
90.70000
6.00000 2073.23500 19.35086 0.42887 2955.06339 29.84127
0.03582 4.50756 7.63687
 14 206
77.40000
6.00000 1736.29833 23.54602 0.31198 2671.16709 34.99851
0.02944 4.34899 7.45951
 15 207
81.70000
8.00000 2231.73750 25.49687 0.99874 3825.46501 41.66101
0.02719 4.40305 7.71054
 16 208
86.90000 12.08333 2299.13583 45.55366 0.65712 5991.68955 61.62792
0.01522 4.46476 7.74029
Obs lnAUCinf
lnAe
lnLambda_z RkTmax
eGFR
CrCL
 9 
8.81049 -0.53754
-4.12239
14.0 26.00000 40.09000
 10 
7.95976 -0.66312
-3.57641
8.0 23.00000 29.51000
 11 
8.16573
0.39310
-3.63259
14.0 26.00000 43.68000
 12 
8.49259
0.21685
-3.29239
14.0 19.00000 30.22000
 13 
7.99128 -0.84661
-3.32925
3.5 27.00000 26.90000
 14 
7.89027 -1.16481
-3.52547
3.5 16.00000 20.27000
 15 
8.24944 -0.00126
-3.60507
8.0 21.00000 30.33000
 16 
8.69813 -0.41989
-4.18540
16.0 28.00000 65.77000


11:11 Monday, February 12, 2018
3
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,R)-M18
(Healthy vs Severe)
ANOVA analysis
DESCRIPTIVE RESULTS (OVERALL)
--------------------- SUMMARY REPORT ---------------------
11:11 Monday, February 12, 2018
3
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,R)-M18
(Healthy vs Severe)
ANOVA analysis
DESCRIPTIVE RESULTS (OVERALL)
--------------------- SUMMARY REPORT ---------------------
Parameter
Renal
Function
Group
n
Min
Mean
Geometric
Mean
Median
Max
Standard
Deviation
Coefficient
of
Variation
Cmax
Normal
8
34.50000
65.38750
63.31345
67.25000
89.90000
16.26885
24.881
Cmax
Severe
8
68.30000
87.71250
86.01138
84.30000
132.00000
19.92468
22.716
Tmax
Normal
8
4.00000
7.00417
6.73067
8.00000
8.03333
1.85425
26.473
Tmax
Severe
8
6.00000
9.51042
9.12592
10.00000
12.08333
2.78831
29.318
AUCT
Normal
8
629.62000 1382.57708 1331.24627 1430.54000 1765.70500
344.31954
24.904
AUCT
Severe
8 1736.29833 2274.51750 2222.65966 2152.48625 3378.34583
548.58434
24.119
Thalf
Normal
8
8.04806
11.03467
10.80637
11.59593
14.31625
2.36420
21.425
Thalf
Severe
8
18.65050
28.29432
26.89951
25.13666
45.55366
10.19501
36.032
Ae
Normal
8
0.70113
1.65046
1.57734
1.79599
2.26527
0.45045
27.292
Ae
Severe
8
0.31198
0.77748
0.68529
0.62065
1.48157
0.41738
53.684
AUCinf
Normal
8
737.98538 1593.83568 1534.56427 1681.20781 2046.25114
401.22674
25.174
AUCinf
Severe
8 2671.16709 4175.96490 3952.91869 3671.87313 6704.18507 1522.00659
36.447
Res_Area
Normal
8
6.24813
13.10191
12.03682
13.70543
20.70927
5.40626
41.263
Res_Area
Severe
8
29.84127
42.52964
41.14168
40.29860
61.62792
12.05540
28.346
Lambda_z
Normal
8
0.04842
0.06554
0.06414
0.06011
0.08613
0.01463
22.329
Lambda_z
Severe
8
0.01522
0.02693
0.02577
0.02758
0.03717
0.00796
29.562
lnCmax
Normal
8
3.54096
4.14810
4.20804
4.49870
0.28544
6.881
lnCmax
Severe
8
4.22391
4.45448
4.43391
4.88280
0.20467
4.595
lnAUCT
Normal
8
6.44512
7.19387
7.26579
7.47631
0.32103
4.463
lnAUCT
Severe
8
7.45951
7.70646
7.67370
8.12514
0.22443
2.912
lnAUCinf
Normal
8
6.60392
7.33600
7.42709
7.62376
0.31967
4.358
lnAUCinf
Severe
8
7.89027
8.28221
8.20758
8.81049
0.34912
4.215
lnAe
Normal
8
-0.35506
0.45574
0.58555
0.81769
0.35217
77.275
lnAe
Severe
8
-1.16481
-0.37791
-0.47871
0.39310
0.53952
-142.764
lnLambda_z Normal
8
-3.02791
-2.74665
-2.81436
-2.45194
0.22075
-8.037
lnLambda_z Severe
8
-4.18540
-3.65862
-3.59074
-3.29239
0.33020
-9.025
RkTmax
Normal
8
1.50000
6.87500
5.53798
8.00000
12.00000
3.59315
52.264
RkTmax
Severe
8
3.50000
10.12500
8.75190
11.00000
16.00000
5.01960
49.576


11:11 Monday, February 12, 2018
4
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,R)-M18
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:11 Monday, February 12, 2018
4
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,R)-M18
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=9 Param=lnCmax
 Number of Observations Read 16
 Number of Observations Used 16
Analysis of Variance
Source
DF Sum of
Squares
Mean
Square
F Value Pr > F
 Model 
1 0.38670 0.38670
6.35 0.0245
 Error 
14 0.85234 0.06088
 Corrected Total 15 1.23904
 Root MSE 
0.24674  R-Square 0.3121
 Dependent Mean 4.30129  Adj R-Sq 0.2630
 Coeff Var 
5.73646    
Parameter Estimates
Variable
Label
DF Parameter
Estimate
Standard
Error
t Value Pr > |t|
95%
Confidence Limits
 Intercept Intercept
1
4.54036
0.11315
40.13
<.0001
4.29767
4.78304
 eGFR 
eGFR
1
-0.00368
0.00146
-2.52
0.0245 -0.00681 -0.00054793


11:11 Monday, February 12, 2018
5
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,R)-M18
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:11 Monday, February 12, 2018
5
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,R)-M18
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=9 Param=lnCmax
Output Statistics
Obs
Dependent
Variable
Predicted
Value
Std Error
Mean Predict
Residual Std Error
Residual
Student
Residual
-2-1 0 1 2
Cook's
D
        1 
4.1805
4.1174
0.0955
0.0631
0.227
0.278  |      |      | 
0.007
        2 
4.1076
4.1652
0.0820
-0.0576
0.233
-0.248  |      |      | 
0.004
        3 
4.4987
4.1946
0.0748
0.3041
0.235
1.293  |      |**    | 
0.085
        4 
4.3438
4.1395
0.0890
0.2043
0.230
0.888  |      |*     | 
0.059
        5 
3.5410
4.1652
0.0820
-0.6242
0.233
-2.682  | *****|      | 
0.446
        6 
4.2613
4.1137
0.0967
0.1476
0.227
0.650  |      |*     | 
0.038
        7 
4.2356
4.1799
0.0783
0.0556
0.234
0.238  |      |      | 
0.003
        8 
4.0164
4.1064
0.0989
-0.0900
0.226
-0.398  |      |      | 
0.015
        9 
4.5337
4.4447
0.0839
0.0889
0.232
0.383  |      |      | 
0.010
       10 
4.2239
4.4558
0.0870
-0.2319
0.231
-1.004  |    **|      | 
0.071
       11 
4.2711
4.4447
0.0839
-0.1736
0.232
-0.748  |     *|      | 
0.037
       12 
4.8828
4.4705
0.0912
0.4123
0.229
1.798  |      |***   | 
0.256
       13 
4.5076
4.4411
0.0829
0.0665
0.232
0.286  |      |      | 
0.005
       14 
4.3490
4.4815
0.0944
-0.1325
0.228
-0.581  |     *|      | 
0.029
       15 
4.4031
4.4631
0.0890
-0.0601
0.230
-0.261  |      |      | 
0.005
       16 
4.4648
4.4374
0.0820
0.0274
0.233
0.118  |      |      | 
0.001
 Sum of Residuals 
0
 Sum of Squared Residuals 
0.85234
 Predicted Residual SS (PRESS) 1.09736


11:11 Monday, February 12, 2018
6
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,R)-M18
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:11 Monday, February 12, 2018
6
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,R)-M18
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=10 Param=lnAUCT
 Number of Observations Read 16
 Number of Observations Used 16
Analysis of Variance
Source
DF Sum of
Squares
Mean
Square
F Value Pr > F
 Model 
1 1.01586 1.01586
12.82 0.0030
 Error 
14 1.10914 0.07922
 Corrected Total 15 2.12500
 Root MSE 
0.28147  R-Square 0.4781
 Dependent Mean 7.45017  Adj R-Sq 0.4408
 Coeff Var 
3.77800    
Parameter Estimates
Variable
Label
DF Parameter
Estimate
Standard
Error
t Value Pr > |t|
95%
Confidence
Limits
 Intercept Intercept
1
7.83765
0.12908
60.72
<.0001
7.56081
8.11449
 eGFR 
eGFR
1
-0.00596
0.00166
-3.58
0.0030 -0.00953 -0.00239


11:11 Monday, February 12, 2018
7
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,R)-M18
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:11 Monday, February 12, 2018
7
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,R)-M18
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=10 Param=lnAUCT
Output Statistics
Obs
Dependent
Variable
Predicted
Value
Std Error
Mean Predict
Residual Std Error
Residual
Student
Residual
-2-1 0 1 2
Cook's
D
        1 
7.3917
7.1521
0.1090
0.2396
0.260
0.923  |      |*     | 
0.075
        2 
7.2592
7.2296
0.0935
0.0296
0.265
0.112  |      |      | 
0.001
        3 
7.4763
7.2773
0.0853
0.1990
0.268
0.742  |      |*     | 
0.028
        4 
7.3642
7.1879
0.1016
0.1763
0.263
0.672  |      |*     | 
0.034
        5 
6.4451
7.2296
0.0935
-0.7845
0.265
-2.955  | *****|      | 
0.542
        6 
7.1445
7.1461
0.1103 -0.001610
0.259
-0.0062  |      |      | 
0.000
        7 
7.2724
7.2534
0.0893
0.0189
0.267
0.0709  |      |      | 
0.000
        8 
7.1976
7.1342
0.1129
0.0633
0.258
0.246  |      |      | 
0.006
        9 
7.9109
7.6827
0.0957
0.2282
0.265
0.862  |      |*     | 
0.049
       10 
7.4665
7.7005
0.0992
-0.2340
0.263
-0.888  |     *|      | 
0.056
       11 
7.6019
7.6827
0.0957
-0.0807
0.265
-0.305  |      |      | 
0.006
       12 
8.1251
7.7244
0.1040
0.4008
0.262
1.532  |      |***   | 
0.186
       13 
7.6369
7.6767
0.0946
-0.0398
0.265
-0.150  |      |      | 
0.001
       14 
7.4595
7.7423
0.1077
-0.2828
0.260
-1.087  |    **|      | 
0.101
       15 
7.7105
7.7125
0.1016 -0.001927
0.263
-0.0073  |      |      | 
0.000
       16 
7.7403
7.6707
0.0935
0.0696
0.265
0.262  |      |      | 
0.004
 Sum of Residuals 
0
 Sum of Squared Residuals 
1.10914
 Predicted Residual SS (PRESS) 1.43310


11:11 Monday, February 12, 2018
8
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,R)-M18
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:11 Monday, February 12, 2018
8
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,R)-M18
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=11 Param=lnAUCinf
 Number of Observations Read 16
 Number of Observations Used 16
Analysis of Variance
Source
DF Sum of
Squares
Mean
Square
F Value Pr > F
 Model 
1 3.36674 3.36674
26.43 0.0001
 Error 
14 1.78304 0.12736
 Corrected Total 15 5.14978
 Root MSE 
0.35687  R-Square 0.6538
 Dependent Mean 7.80911  Adj R-Sq 0.6290
 Coeff Var 
4.56998    
Parameter Estimates
Variable
Label
DF Parameter
Estimate
Standard
Error
t Value Pr > |t|
95%
Confidence
Limits
 Intercept Intercept
1
8.51452
0.16366
52.03
<.0001
8.16351
8.86553
 eGFR 
eGFR
1
-0.01085
0.00211
-5.14
0.0001 -0.01538 -0.00633


11:11 Monday, February 12, 2018
9
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,R)-M18
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:11 Monday, February 12, 2018
9
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,R)-M18
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=11 Param=lnAUCinf
Output Statistics
Obs
Dependent
Variable
Predicted
Value
Std Error
Mean Predict
Residual Std Error
Residual
Student
Residual
-2-1 0 1 2
Cook's
D
        1 
7.6238
7.2665
0.1382
0.3573
0.329
1.086  |      |**    | 
0.104
        2 
7.4457
7.4076
0.1186
0.0381
0.337
0.113  |      |      | 
0.001
        3 
7.5526
7.4944
0.1082
0.0582
0.340
0.171  |      |      | 
0.001
        4 
7.4488
7.3316
0.1288
0.1172
0.333
0.352  |      |      | 
0.009
        5 
6.6039
7.4076
0.1186
-0.8036
0.337
-2.388  |  ****|      | 
0.354
        6 
7.2090
7.2556
0.1398
-0.0466
0.328
-0.142  |      |      | 
0.002
        7 
7.4085
7.4510
0.1132
-0.0425
0.338
-0.126  |      |      | 
0.001
        8 
7.3957
7.2339
0.1431
0.1618
0.327
0.495  |      |      | 
0.023
        9 
8.8105
8.2324
0.1214
0.5781
0.336
1.723  |      |***   | 
0.194
       10 
7.9598
8.2649
0.1258
-0.3051
0.334
-0.914  |     *|      | 
0.059
       11 
8.1657
8.2324
0.1214
-0.0666
0.336
-0.199  |      |      | 
0.003
       12 
8.4926
8.3083
0.1319
0.1843
0.332
0.556  |      |*     | 
0.024
       13 
7.9913
8.2215
0.1200
-0.2302
0.336
-0.685  |     *|      | 
0.030
       14 
7.8903
8.3409
0.1366
-0.4506
0.330
-1.367  |    **|      | 
0.160
       15 
8.2494
8.2866
0.1288
-0.0372
0.333
-0.112  |      |      | 
0.001
       16 
8.6981
8.2106
0.1186
0.4875
0.337
1.448  |      |**    | 
0.130
 Sum of Residuals 
0
 Sum of Squared Residuals 
1.78304
 Predicted Residual SS (PRESS) 2.30750


11:11 Monday, February 12, 2018
10
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,R)-M18
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:11 Monday, February 12, 2018
10
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,R)-M18
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=12 Param=lnAe
 Number of Observations Read 16
 Number of Observations Used 16
Analysis of Variance
Source
DF Sum of
Squares
Mean
Square
F Value Pr > F
 Model 
1 2.73112 2.73112
12.94 0.0029
 Error 
14 2.95449 0.21103
 Corrected Total 15 5.68561
 Root MSE 
0.45939  R-Square 0.4804
 Dependent Mean 
0.03892  Adj R-Sq 0.4432
 Coeff Var 
1180.46320    
Parameter Estimates
Variable
Label
DF Parameter
Estimate
Standard
Error
t Value Pr > |t|
95%
Confidence
Limits
 Intercept Intercept
1
-0.59643
0.21067
-2.83
0.0133 -1.04826 -0.14459
 eGFR 
eGFR
1
0.00977
0.00272
3.60
0.0029
0.00395
0.01560


11:11 Monday, February 12, 2018
11
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,R)-M18
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:11 Monday, February 12, 2018
11
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,R)-M18
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=12 Param=lnAe
Output Statistics
Obs
Dependent
Variable
Predicted
Value
Std Error
Mean Predict
Residual Std Error
Residual
Student
Residual
-2-1 0 1 2
Cook's
D
        1 
0.5968
0.5276
0.1779
0.0692
0.424
0.163  |      |      | 
0.002
        2 
0.5869
0.4006
0.1526
0.1864
0.433
0.430  |      |      | 
0.011
        3 
0.8177
0.3224
0.1393
0.4953
0.438
1.131  |      |**    | 
0.065
        4 
0.4648
0.4690
0.1658 -0.004164
0.428
-0.0097  |      |      | 
0.000
        5 
-0.3551
0.4006
0.1526
-0.7556
0.433
-1.744  |   ***|      | 
0.189
        6 
0.5878
0.5374
0.1800
0.0504
0.423
0.119  |      |      | 
0.001
        7 
0.5842
0.3615
0.1457
0.2227
0.436
0.511  |      |*     | 
0.015
        8 
0.3628
0.5570
0.1842
-0.1942
0.421
-0.461  |      |      | 
0.020
        9 
-0.5375
-0.3423
0.1563
-0.1952
0.432
-0.452  |      |      | 
0.013
       10 
-0.6631
-0.3716
0.1619
-0.2915
0.430
-0.678  |     *|      | 
0.033
       11 
0.3931
-0.3423
0.1563
0.7354
0.432
1.702  |      |***   | 
0.190
       12 
0.2169
-0.4107
0.1697
0.6276
0.427
1.470  |      |**    | 
0.171
       13 
-0.8466
-0.3325
0.1544
-0.5141
0.433
-1.188  |    **|      | 
0.090
       14 
-1.1648
-0.4400
0.1758
-0.7248
0.424
-1.708  |   ***|      | 
0.250
       15 -0.001261
-0.3912
0.1658
0.3899
0.428
0.910  |      |*     | 
0.062
       16 
-0.4199
-0.3227
0.1526
-0.0971
0.433
-0.224  |      |      | 
0.003
 Sum of Residuals 
0
 Sum of Squared Residuals 
2.95449
 Predicted Residual SS (PRESS) 3.83717


11:11 Monday, February 12, 2018
12
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,R)-M18
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:11 Monday, February 12, 2018
12
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,R)-M18
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=13 Param=lnLambda_z
 Number of Observations Read 16
 Number of Observations Used 16
Analysis of Variance
Source
DF Sum of
Squares
Mean
Square
F Value Pr > F
 Model 
1 3.09115 3.09115
32.30 <.0001
 Error 
14 1.33996 0.09571
 Corrected Total 15 4.43111
 Root MSE 
0.30937  R-Square 0.6976
 Dependent Mean -3.20264  Adj R-Sq 0.6760
 Coeff Var 
-9.65995    
Parameter Estimates
Variable
Label
DF Parameter
Estimate
Standard
Error
t Value Pr > |t|
95%
Confidence
Limits
 Intercept Intercept
1
-3.87856
0.14187
-27.34
<.0001 -4.18285 -3.57427
 eGFR 
eGFR
1
0.01040
0.00183
5.68
<.0001
0.00647
0.01432


11:11 Monday, February 12, 2018
13
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,R)-M18
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:11 Monday, February 12, 2018
13
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,R)-M18
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=13 Param=lnLambda_z
Output Statistics
Obs
Dependent
Variable
Predicted
Value
Std Error
Mean Predict
Residual Std Error
Residual
Student
Residual
-2-1 0 1 2
Cook's
D
        1 
-3.0279
-2.6827
0.1198
-0.3452
0.285
-1.210  |    **|      | 
0.129
        2 
-2.9041
-2.8179
0.1028
-0.0862
0.292
-0.295  |      |      | 
0.005
        3 
-2.5129
-2.9011
0.0938
0.3882
0.295
1.317  |      |**    | 
0.088
        4 
-2.5311
-2.7451
0.1116
0.2139
0.289
0.741  |      |*     | 
0.041
        5 
-2.9165
-2.8179
0.1028
-0.0986
0.292
-0.338  |      |      | 
0.007
        6 
-2.4519
-2.6723
0.1212
0.2204
0.285
0.774  |      |*     | 
0.054
        7 
-2.7394
-2.8595
0.0981
0.1201
0.293
0.409  |      |      | 
0.009
        8 
-2.8894
-2.6515
0.1240
-0.2379
0.283
-0.839  |     *|      | 
0.067
        9 
-4.1224
-3.6082
0.1052
-0.5142
0.291
-1.767  |   ***|      | 
0.204
       10 
-3.5764
-3.6394
0.1090
0.0630
0.290
0.218  |      |      | 
0.003
       11 
-3.6326
-3.6082
0.1052
-0.0244
0.291
-0.0839  |      |      | 
0.000
       12 
-3.2924
-3.6810
0.1143
0.3886
0.287
1.352  |      |**    | 
0.144
       13 
-3.3292
-3.5978
0.1040
0.2685
0.291
0.922  |      |*     | 
0.054
       14 
-3.5255
-3.7122
0.1184
0.1867
0.286
0.653  |      |*     | 
0.037
       15 
-3.6051
-3.6602
0.1116
0.0551
0.289
0.191  |      |      | 
0.003
       16 
-4.1854
-3.5874
0.1028
-0.5980
0.292
-2.049  |  ****|      | 
0.261
 Sum of Residuals 
0
 Sum of Squared Residuals 
1.33996
 Predicted Residual SS (PRESS) 1.73778


11:11 Monday, February 12, 2018
14
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,R)-M18
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:11 Monday, February 12, 2018
14
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,R)-M18
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=14 Param=RkTmax
 Number of Observations Read 16
 Number of Observations Used 16
Analysis of Variance
Source
DF
Sum of
Squares
Mean
Square
F Value Pr > F
 Model 
1
41.44799 41.44799
2.17 0.1630
 Error 
14 267.55201 19.11086
 Corrected Total 15 309.00000
 Root MSE 
4.37160  R-Square 0.1341
 Dependent Mean 
8.50000  Adj R-Sq 0.0723
 Coeff Var 
51.43055    
Parameter Estimates
Variable
Label
DF Parameter
Estimate
Standard
Error
t Value Pr > |t|
95%
Confidence
Limits
 Intercept Intercept
1
10.97508
2.00475
5.47
<.0001
6.67532 15.27483
 eGFR 
eGFR
1
-0.03808
0.02586
-1.47
0.1630 -0.09353
0.01738


11:11 Monday, February 12, 2018
15
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,R)-M18
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:11 Monday, February 12, 2018
15
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,R)-M18
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=14 Param=RkTmax
Output Statistics
Obs
Dependent
Variable
Predicted
Value
Std Error
Mean Predict
Residual Std Error
Residual
Student
Residual
-2-1 0 1 2
Cook's
D
        1 
8.0000
6.5961
1.6929
1.4039
4.031
0.348  |      |      | 
0.011
        2 
8.0000
7.0911
1.4525
0.9089
4.123
0.220  |      |      | 
0.003
        3 
8.0000
7.3957
1.3254
0.6043
4.166
0.145  |      |      | 
0.001
        4 
8.0000
6.8246
1.5776
1.1754
4.077
0.288  |      |      | 
0.006
        5 
1.5000
7.0911
1.4525
-5.5911
4.123
-1.356  |    **|      | 
0.114
        6 
1.5000
6.5580
1.7127
-5.0580
4.022
-1.258  |    **|      | 
0.143
        7 
12.0000
7.2434
1.3865
4.7566
4.146
1.147  |      |**    | 
0.074
        8 
8.0000
6.4819
1.7528
1.5181
4.005
0.379  |      |      | 
0.014
        9 
14.0000
9.9850
1.4870
4.0150
4.111
0.977  |      |*     | 
0.062
       10 
8.0000
10.0993
1.5407
-2.0993
4.091
-0.513  |     *|      | 
0.019
       11 
14.0000
9.9850
1.4870
4.0150
4.111
0.977  |      |*     | 
0.062
       12 
14.0000
10.2516
1.6153
3.7484
4.062
0.923  |      |*     | 
0.067
       13 
3.5000
9.9470
1.4696
-6.4470
4.117
-1.566  |   ***|      | 
0.156
       14 
3.5000
10.3658
1.6732
-6.8658
4.039
-1.700  |   ***|      | 
0.248
       15 
8.0000
10.1754
1.5776
-2.1754
4.077
-0.534  |     *|      | 
0.021
       16 
16.0000
9.9089
1.4525
6.0911
4.123
1.477  |      |**    | 
0.135
 Sum of Residuals 
0
 Sum of Squared Residuals 
267.55201
 Predicted Residual SS (PRESS) 348.97946


11:11 Monday, February 12, 2018
16
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,R)-M18
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:11 Monday, February 12, 2018
16
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,R)-M18
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=9 Param=lnCmax
 Number of Observations Read 16
 Number of Observations Used 16
Analysis of Variance
Source
DF Sum of
Squares
Mean
Square
F Value Pr > F
 Model 
1 0.52808 0.52808
10.40 0.0061
 Error 
14 0.71096 0.05078
 Corrected Total 15 1.23904
 Root MSE 
0.22535  R-Square 0.4262
 Dependent Mean 4.30129  Adj R-Sq 0.3852
 Coeff Var 
5.23914    
Parameter Estimates
Variable
Label
DF Parameter
Estimate
Standard
Error
t Value Pr > |t|
95%
Confidence
Limits
 Intercept Intercept
1
4.59612
0.10739
42.80
<.0001
4.36579
4.82646
 CrCL 
CrCL
1
-0.00345
0.00107
-3.22
0.0061 -0.00574 -0.00116


11:11 Monday, February 12, 2018
17
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,R)-M18
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:11 Monday, February 12, 2018
17
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,R)-M18
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=9 Param=lnCmax
Output Statistics
Obs
Dependent
Variable
Predicted
Value
Std Error
Mean Predict
Residual Std Error
Residual
Student
Residual
-2-1 0 1 2
Cook's
D
        1 
4.1805
4.0308
0.1010
0.1497
0.201
0.743  |      |*     | 
0.069
        2 
4.1076
4.0688
0.0915
0.0388
0.206
0.188  |      |      | 
0.003
        3 
4.4987
4.2496
0.0586
0.2491
0.218
1.145  |      |**    | 
0.047
        4 
4.3438
4.1672
0.0700
0.1767
0.214
0.825  |      |*     | 
0.036
        5 
3.5410
4.0608
0.0935
-0.5198
0.205
-2.535  | *****|      | 
0.668
        6 
4.2613
4.1815
0.0675
0.0798
0.215
0.371  |      |      | 
0.007
        7 
4.2356
4.1946
0.0653
0.0410
0.216
0.190  |      |      | 
0.002
        8 
4.0164
4.0877
0.0869
-0.0714
0.208
-0.343  |      |      | 
0.010
        9 
4.5337
4.4578
0.0744
0.0759
0.213
0.357  |      |      | 
0.008
       10 
4.2239
4.4943
0.0822
-0.2704
0.210
-1.289  |    **|      | 
0.127
       11 
4.2711
4.4454
0.0719
-0.1743
0.214
-0.816  |     *|      | 
0.038
       12 
4.8828
4.4919
0.0816
0.3909
0.210
1.861  |      |***   | 
0.262
       13 
4.5076
4.5033
0.0843 0.004239
0.209
0.0203  |      |      | 
0.000
       14 
4.3490
4.5262
0.0897
-0.1772
0.207
-0.857  |     *|      | 
0.069
       15 
4.4031
4.4915
0.0816
-0.0884
0.210
-0.421  |      |      | 
0.013
       16 
4.4648
4.3692
0.0601
0.0955
0.217
0.440  |      |      | 
0.007
 Sum of Residuals 
0
 Sum of Squared Residuals 
0.71096
 Predicted Residual SS (PRESS) 0.96773


11:11 Monday, February 12, 2018
18
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,R)-M18
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:11 Monday, February 12, 2018
18
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,R)-M18
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=10 Param=lnAUCT
 Number of Observations Read 16
 Number of Observations Used 16
Analysis of Variance
Source
DF Sum of
Squares
Mean
Square
F Value Pr > F
 Model 
1 1.08368 1.08368
14.57 0.0019
 Error 
14 1.04132 0.07438
 Corrected Total 15 2.12500
 Root MSE 
0.27273  R-Square 0.5100
 Dependent Mean 7.45017  Adj R-Sq 0.4750
 Coeff Var 
3.66068    
Parameter Estimates
Variable
Label
DF Parameter
Estimate
Standard
Error
t Value Pr > |t|
95%
Confidence
Limits
 Intercept Intercept
1
7.87252
0.12997
60.57
<.0001
7.59376
8.15128
 CrCL 
CrCL
1
-0.00494
0.00129
-3.82
0.0019 -0.00772 -0.00217


11:11 Monday, February 12, 2018
19
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,R)-M18
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:11 Monday, February 12, 2018
19
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,R)-M18
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=10 Param=lnAUCT
Output Statistics
Obs
Dependent
Variable
Predicted
Value
Std Error
Mean Predict
Residual Std Error
Residual
Student
Residual
-2-1 0 1 2
Cook's
D
        1 
7.3917
7.0628
0.1223
0.3290
0.244
1.349  |      |**    | 
0.229
        2 
7.2592
7.1172
0.1107
0.1420
0.249
0.570  |      |*     | 
0.032
        3 
7.4763
7.3761
0.0709
0.1002
0.263
0.381  |      |      | 
0.005
        4 
7.3642
7.2580
0.0848
0.1062
0.259
0.410  |      |      | 
0.009
        5 
6.4451
7.1056
0.1131
-0.6605
0.248
-2.662  | *****|      | 
0.736
        6 
7.1445
7.2786
0.0817
-0.1340
0.260
-0.515  |     *|      | 
0.013
        7 
7.2724
7.2973
0.0791
-0.0249
0.261
-0.0956  |      |      | 
0.000
        8 
7.1976
7.1442
0.1052
0.0533
0.252
0.212  |      |      | 
0.004
        9 
7.9109
7.6744
0.0900
0.2365
0.257
0.919  |      |*     | 
0.052
       10 
7.4665
7.7267
0.0995
-0.2602
0.254
-1.025  |    **|      | 
0.081
       11 
7.6019
7.6566
0.0870
-0.0547
0.258
-0.212  |      |      | 
0.003
       12 
8.1251
7.7232
0.0988
0.4020
0.254
1.581  |      |***   | 
0.189
       13 
7.6369
7.7396
0.1020
-0.1027
0.253
-0.406  |      |      | 
0.013
       14 
7.4595
7.7723
0.1085
-0.3128
0.250
-1.250  |    **|      | 
0.147
       15 
7.7105
7.7226
0.0987
-0.0121
0.254
-0.0476  |      |      | 
0.000
       16 
7.7403
7.5475
0.0728
0.1928
0.263
0.734  |      |*     | 
0.021
 Sum of Residuals 
0
 Sum of Squared Residuals 
1.04132
 Predicted Residual SS (PRESS) 1.46054


11:11 Monday, February 12, 2018
20
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,R)-M18
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:11 Monday, February 12, 2018
20
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,R)-M18
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=11 Param=lnAUCinf
 Number of Observations Read 16
 Number of Observations Used 16
Analysis of Variance
Source
DF Sum of
Squares
Mean
Square
F Value Pr > F
 Model 
1 2.98572 2.98572
19.32 0.0006
 Error 
14 2.16406 0.15458
 Corrected Total 15 5.14978
 Root MSE 
0.39316  R-Square 0.5798
 Dependent Mean 7.80911  Adj R-Sq 0.5498
 Coeff Var 
5.03465    
Parameter Estimates
Variable
Label
DF Parameter
Estimate
Standard
Error
t Value Pr > |t|
95%
Confidence
Limits
 Intercept Intercept
1
8.51016
0.18737
45.42
<.0001
8.10830
8.91202
 CrCL 
CrCL
1
-0.00820
0.00187
-4.39
0.0006 -0.01221 -0.00420


11:11 Monday, February 12, 2018
21
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,R)-M18
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:11 Monday, February 12, 2018
21
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,R)-M18
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=11 Param=lnAUCinf
Output Statistics
Obs
Dependent
Variable
Predicted
Value
Std Error
Mean Predict
Residual Std Error
Residual
Student
Residual
-2-1 0 1 2
Cook's
D
        1 
7.6238
7.1660
0.1763
0.4577
0.351
1.302  |      |**    | 
0.213
        2 
7.4457
7.2564
0.1596
0.1893
0.359
0.527  |      |*     | 
0.027
        3 
7.5526
7.6861
0.1022
-0.1336
0.380
-0.352  |      |      | 
0.004
        4 
7.4488
7.4902
0.1222
-0.0414
0.374
-0.111  |      |      | 
0.001
        5 
6.6039
7.2372
0.1631
-0.6332
0.358
-1.770  |   ***|      | 
0.326
        6 
7.2090
7.5243
0.1177
-0.3152
0.375
-0.840  |     *|      | 
0.035
        7 
7.4085
7.5554
0.1140
-0.1469
0.376
-0.390  |      |      | 
0.007
        8 
7.3957
7.3013
0.1517
0.0944
0.363
0.260  |      |      | 
0.006
        9 
8.8105
8.1813
0.1297
0.6292
0.371
1.695  |      |***   | 
0.176
       10 
7.9598
8.2681
0.1434
-0.3083
0.366
-0.842  |     *|      | 
0.054
       11 
8.1657
8.1518
0.1255
0.0139
0.373
0.0373  |      |      | 
0.000
       12 
8.4926
8.2623
0.1425
0.2303
0.366
0.629  |      |*     | 
0.030
       13 
7.9913
8.2895
0.1470
-0.2982
0.365
-0.818  |     *|      | 
0.054
       14 
7.8903
8.3439
0.1564
-0.4536
0.361
-1.258  |    **|      | 
0.149
       15 
8.2494
8.2614
0.1423
-0.0119
0.367
-0.0325  |      |      | 
0.000
       16 
8.6981
7.9706
0.1049
0.7275
0.379
1.920  |      |***   | 
0.141
 Sum of Residuals 
0
 Sum of Squared Residuals 
2.16406
 Predicted Residual SS (PRESS) 2.86504


11:11 Monday, February 12, 2018
22
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,R)-M18
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:11 Monday, February 12, 2018
22
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,R)-M18
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=12 Param=lnAe
 Number of Observations Read 16
 Number of Observations Used 16
Analysis of Variance
Source
DF Sum of
Squares
Mean
Square
F Value Pr > F
 Model 
1 2.30470 2.30470
9.54 0.0080
 Error 
14 3.38091 0.24149
 Corrected Total 15 5.68561
 Root MSE 
0.49142  R-Square 0.4054
 Dependent Mean 
0.03892  Adj R-Sq 0.3629
 Coeff Var 
1262.78135    
Parameter Estimates
Variable
Label
DF Parameter
Estimate
Standard
Error
t Value Pr > |t|
95%
Confidence
Limits
 Intercept Intercept
1
-0.57702
0.23419
-2.46
0.0273 -1.07931 -0.07473
 CrCL 
CrCL
1
0.00721
0.00233
3.09
0.0080
0.00220
0.01221


11:11 Monday, February 12, 2018
23
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,R)-M18
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:11 Monday, February 12, 2018
23
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,R)-M18
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=12 Param=lnAe
Output Statistics
Obs
Dependent
Variable
Predicted
Value
Std Error
Mean Predict
Residual Std Error
Residual
Student
Residual
-2-1 0 1 2
Cook's
D
        1 
0.5968
0.6039
0.2203 -0.007082
0.439
-0.0161  |      |      | 
0.000
        2 
0.5869
0.5245
0.1995
0.0624
0.449
0.139  |      |      | 
0.002
        3 
0.8177
0.1470
0.1277
0.6707
0.475
1.413  |      |**    | 
0.072
        4 
0.4648
0.3191
0.1527
0.1457
0.467
0.312  |      |      | 
0.005
        5 
-0.3551
0.5414
0.2038
-0.8965
0.447
-2.005  |  ****|      | 
0.418
        6 
0.5878
0.2892
0.1472
0.2986
0.469
0.637  |      |*     | 
0.020
        7 
0.5842
0.2618
0.1425
0.3223
0.470
0.685  |      |*     | 
0.022
        8 
0.3628
0.4850
0.1896
-0.1223
0.453
-0.270  |      |      | 
0.006
        9 
-0.5375
-0.2881
0.1622
-0.2495
0.464
-0.538  |     *|      | 
0.018
       10 
-0.6631
-0.3643
0.1793
-0.2988
0.458
-0.653  |     *|      | 
0.033
       11 
0.3931
-0.2622
0.1568
0.6553
0.466
1.407  |      |**    | 
0.112
       12 
0.2169
-0.3592
0.1781
0.5761
0.458
1.258  |      |**    | 
0.120
       13 
-0.8466
-0.3831
0.1837
-0.4635
0.456
-1.017  |    **|      | 
0.084
       14 
-1.1648
-0.4309
0.1955
-0.7339
0.451
-1.628  |   ***|      | 
0.249
       15 -0.001261
-0.3584
0.1779
0.3572
0.458
0.780  |      |*     | 
0.046
       16 
-0.4199
-0.1030
0.1312
-0.3169
0.474
-0.669  |     *|      | 
0.017
 Sum of Residuals 
0
 Sum of Squared Residuals 
3.38091
 Predicted Residual SS (PRESS) 4.47864


11:11 Monday, February 12, 2018
24
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,R)-M18
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:11 Monday, February 12, 2018
24
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,R)-M18
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=13 Param=lnLambda_z
 Number of Observations Read 16
 Number of Observations Used 16
Analysis of Variance
Source
DF Sum of
Squares
Mean
Square
F Value Pr > F
 Model 
1 2.10429 2.10429
12.66 0.0031
 Error 
14 2.32682 0.16620
 Corrected Total 15 4.43111
 Root MSE 
0.40768  R-Square 0.4749
 Dependent Mean 
-3.20264  Adj R-Sq 0.4374
 Coeff Var 
-12.72947    
Parameter Estimates
Variable
Label
DF Parameter
Estimate
Standard
Error
t Value Pr > |t|
95%
Confidence
Limits
 Intercept Intercept
1
-3.79118
0.19428
-19.51
<.0001 -4.20788 -3.37449
 CrCL 
CrCL
1
0.00689
0.00194
3.56
0.0031
0.00274
0.01104


11:11 Monday, February 12, 2018
25
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,R)-M18
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:11 Monday, February 12, 2018
25
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,R)-M18
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=13 Param=lnLambda_z
Output Statistics
Obs
Dependent
Variable
Predicted
Value
Std Error
Mean Predict
Residual Std Error
Residual
Student
Residual
-2-1 0 1 2
Cook's
D
        1 
-3.0279
-2.6628
0.1828
-0.3651
0.364
-1.002  |    **|      | 
0.126
        2 
-2.9041
-2.7386
0.1655
-0.1655
0.373
-0.444  |      |      | 
0.019
        3 
-2.5129
-3.0994
0.1060
0.5865
0.394
1.490  |      |**    | 
0.080
        4 
-2.5311
-2.9349
0.1267
0.4037
0.387
1.042  |      |**    | 
0.058
        5 
-2.9165
-2.7225
0.1691
-0.1940
0.371
-0.523  |     *|      | 
0.028
        6 
-2.4519
-2.9635
0.1221
0.5116
0.389
1.315  |      |**    | 
0.085
        7 
-2.7394
-2.9896
0.1182
0.2503
0.390
0.641  |      |*     | 
0.019
        8 
-2.8894
-2.7763
0.1573
-0.1130
0.376
-0.300  |      |      | 
0.008
        9 
-4.1224
-3.5151
0.1345
-0.6073
0.385
-1.578  |   ***|      | 
0.152
       10 
-3.5764
-3.5880
0.1487
0.0115
0.380
0.0304  |      |      | 
0.000
       11 
-3.6326
-3.4904
0.1301
-0.1422
0.386
-0.368  |      |      | 
0.008
       12 
-3.2924
-3.5831
0.1477
0.2907
0.380
0.765  |      |*     | 
0.044
       13 
-3.3292
-3.6059
0.1524
0.2767
0.378
0.732  |      |*     | 
0.044
       14 
-3.5255
-3.6516
0.1622
0.1261
0.374
0.337  |      |      | 
0.011
       15 
-3.6051
-3.5823
0.1476
-0.0228
0.380
-0.0599  |      |      | 
0.000
       16 
-4.1854
-3.3382
0.1088
-0.8472
0.393
-2.156  |  ****|      | 
0.178
 Sum of Residuals 
0
 Sum of Squared Residuals 
2.32682
 Predicted Residual SS (PRESS) 2.86678


11:11 Monday, February 12, 2018
26
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,R)-M18
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:11 Monday, February 12, 2018
26
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,R)-M18
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=14 Param=RkTmax
 Number of Observations Read 16
 Number of Observations Used 16
Analysis of Variance
Source
DF
Sum of
Squares
Mean
Square
F Value Pr > F
 Model 
1
22.99752 22.99752
1.13 0.3066
 Error 
14 286.00248 20.42875
 Corrected Total 15 309.00000
 Root MSE 
4.51982  R-Square 0.0744
 Dependent Mean 
8.50000  Adj R-Sq 0.0083
 Coeff Var 
53.17432    
Parameter Estimates
Variable
Label
DF Parameter
Estimate
Standard
Error
t Value Pr > |t|
95%
Confidence
Limits
 Intercept Intercept
1
10.44567
2.15397
4.85
0.0003
5.82587 15.06547
 CrCL 
CrCL
1
-0.02277
0.02146
-1.06
0.3066 -0.06879
0.02326


11:11 Monday, February 12, 2018
27
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,R)-M18
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:11 Monday, February 12, 2018
27
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,R)-M18
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=14 Param=RkTmax
Output Statistics
Obs
Dependent
Variable
Predicted
Value
Std Error
Mean Predict
Residual Std Error
Residual
Student
Residual
-2-1 0 1 2
Cook's
D
        1 
8.0000
6.7153
2.0264
1.2847
4.040
0.318  |      |      | 
0.013
        2 
8.0000
6.9660
1.8350
1.0340
4.131
0.250  |      |      | 
0.006
        3 
8.0000
8.1587
1.1748
-0.1587
4.364
-0.0364  |      |      | 
0.000
        4 
8.0000
7.6148
1.4046
0.3852
4.296
0.0897  |      |      | 
0.000
        5 
1.5000
6.9127
1.8748
-5.4127
4.113
-1.316  |    **|      | 
0.180
        6 
1.5000
7.7095
1.3535
-6.2095
4.312
-1.440  |    **|      | 
0.102
        7 
12.0000
7.7958
1.3105
4.2042
4.326
0.972  |      |*     | 
0.043
        8 
8.0000
7.0907
1.7439
0.9093
4.170
0.218  |      |      | 
0.004
        9 
14.0000
9.5329
1.4915
4.4671
4.267
1.047  |      |**    | 
0.067
       10 
8.0000
9.7738
1.6487
-1.7738
4.208
-0.421  |      |      | 
0.014
       11 
14.0000
9.4512
1.4424
4.5488
4.283
1.062  |      |**    | 
0.064
       12 
14.0000
9.7576
1.6376
4.2424
4.213
1.007  |      |**    | 
0.077
       13 
3.5000
9.8332
1.6899
-6.3332
4.192
-1.511  |   ***|      | 
0.185
       14 
3.5000
9.9842
1.7982
-6.4842
4.147
-1.564  |   ***|      | 
0.230
       15 
8.0000
9.7551
1.6359
-1.7551
4.213
-0.417  |      |      | 
0.013
       16 
16.0000
8.9483
1.2064
7.0517
4.356
1.619  |      |***   | 
0.101
 Sum of Residuals 
0
 Sum of Squared Residuals 
286.00248
 Predicted Residual SS (PRESS) 369.89708


11:11 Monday, February 12, 2018
28
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,R)-M18
(Healthy vs Severe)
ANOVA analysis
NON-PARAMETRIC TEST OF FIXED EFFECT for Tmax parameter
--------------------- SUMMARY REPORT ---------------------
The NPAR1WAY Procedure
11:11 Monday, February 12, 2018
28
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,R)-M18
(Healthy vs Severe)
ANOVA analysis
NON-PARAMETRIC TEST OF FIXED EFFECT for Tmax parameter
--------------------- SUMMARY REPORT ---------------------
The NPAR1WAY Procedure
Wilcoxon Scores (Rank Sums) for Variable Value
Classified by Variable Group
Group
N
Sum of
Scores
Expected
Under H0
Std Dev
Under H0
Mean
Score
 1 
8
55.0
68.0 9.077445
6.8750
 2 
8
81.0
68.0 9.077445 10.1250
Average scores were used for ties.
Wilcoxon Two-Sample Test
 Statistic 
55.0000
   
 Normal Approximation 
 Z 
-1.3770
 One-Sided Pr <  Z 
0.0843
 Two-Sided Pr > |Z| 
0.1685
   
 t Approximation 
 One-Sided Pr <  Z 
0.0944
 Two-Sided Pr > |Z| 
0.1887
Z includes a continuity correction of 0.5.
Kruskal-Wallis Test
 Chi-Square 
2.0510
 DF 
1
 Pr > Chi-Square 
0.1521
Hodges-Lehmann Estimation
Location Shift (1 - 2)    -4.0000
Type
90%
Confidence
Limits
Interval
Midpoint
Asymptotic
Standard Error
 Asymptotic (Moses) -4.0000 0.0000
-2.0000
1.2159
 Exact 
-4.0000 0.0000
-2.0000


09:52 Monday, January 22, 2018
1
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,R)-M18 - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
RAW DATA
--------------------- SUMMARY REPORT ---------------------
09:52 Monday, January 22, 2018
1
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,R)-M18 - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
RAW DATA
--------------------- SUMMARY REPORT ---------------------
Renal Function Group=Normal
Obs Subject
Cmax
Tmax
AUCT
Thalf
Ae
AUCinf
Res_Area Lambda_z lnCmax
lnAUCT
 1 101
65.40000 8.00000 1622.48750 14.31625 1.81632 2046.25114 20.70927
0.04842 4.18052 7.39172
 2 102
60.80000 8.00000 1421.13750 12.64878 1.79845 1712.48846 17.01331
0.05480 4.10759 7.25921
 3 103
89.90000 8.00000 1765.70500
8.55370 2.26527 1905.63475
7.34295
0.08103 4.49870 7.47631
 4 104
77.00000 8.00000 1578.40617
8.71141 1.59174 1717.79161
8.11422
0.07957 4.34381 7.36417
 5 105
34.50000 4.00000
629.62000 12.80730 0.70113
737.98538 14.68395
0.05412 3.54096 6.44512
 6 106
70.90000 4.00000 1267.15500
8.04806 1.79999 1351.60507
6.24813
0.08613 4.26127 7.14453
 7 107
69.10000 8.03333 1439.94250 10.72780 1.79353 1649.92717 12.72691
0.06461 4.23555 7.27236
 8 108
55.50000 8.00000 1336.16300 12.46407 1.43729 1629.00185 17.97658
0.05561 4.01638 7.19756
Obs lnAUCinf
lnAe
lnLambda_z RkTmax
eGFR
CrCL
 1 
7.62376
0.59681
-3.02791
8.0 115.00000 163.85000
 2 
7.44570
0.58692
-2.90407
8.0 102.00000 152.84000
 3 
7.55257
0.81769
-2.51288
8.0
94.00000 100.45000
 4 
7.44879
0.46483
-2.53115
8.0 109.00000 124.34000
 5 
6.60392 -0.35506
-2.91653
1.5 102.00000 155.18000
 6 
7.20905
0.58778
-2.45194
1.5 116.00000 120.18000
 7 
7.40849
0.58418
-2.73935
12.0
98.00000 116.39000
 8 
7.39572
0.36276
-2.88936
8.0 118.00000 147.36000


09:52 Monday, January 22, 2018
2
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,R)-M18 - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
RAW DATA
--------------------- SUMMARY REPORT ---------------------
09:52 Monday, January 22, 2018
2
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,R)-M18 - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
RAW DATA
--------------------- SUMMARY REPORT ---------------------
Renal Function Group=Severe
Obs Subject
Cmax
Tmax
AUCT
Thalf
Ae
AUCinf
Res_Area Lambda_z lnCmax
lnAUCT
 9 013-01
68.30000
8.00000 1748.49750 24.77645 0.51524 2863.39423 38.93619
0.02798 4.22391 7.46651
 10 013-02
90.70000
6.00000 2073.23500 19.35086 0.42887 2955.06339 29.84127
0.03582 4.50756 7.63687
 11 013-03
71.60000 12.00000 2002.04000 26.20845 1.48157 3518.28125 43.09608
0.02645 4.27110 7.60192
 12 013-04
86.90000 12.08333 2299.13583 45.55366 0.65712 5991.68955 61.62792
0.01522 4.46476 7.74029
 13 013-05
77.40000
6.00000 1736.29833 23.54602 0.31198 2671.16709 34.99851
0.02944 4.34899 7.45951
 14 013-06
93.10000 12.00000 2726.85000 42.77174 0.58419 6704.18507 59.32615
0.01621 4.53367 7.91090
 15 013-07
132.00000 12.00000 3378.34583 18.65050 1.24216 4878.47360 30.74994
0.03717 4.88280 8.12514
 16 013-08
81.70000
8.00000 2231.73750 25.49687 0.99874 3825.46501 41.66101
0.02719 4.40305 7.71054
Obs lnAUCinf
lnAe
lnLambda_z RkTmax
eGFR
CrCL
 9 
7.95976 -0.66312
-3.57641
8.0 23.00000 29.51000
 10 
7.99128 -0.84661
-3.32925
3.5 27.00000 26.90000
 11 
8.16573
0.39310
-3.63259
14.0 26.00000 43.68000
 12 
8.69813 -0.41989
-4.18540
16.0 28.00000 65.77000
 13 
7.89027 -1.16481
-3.52547
3.5 16.00000 20.27000
 14 
8.81049 -0.53754
-4.12239
14.0 26.00000 40.09000
 15 
8.49259
0.21685
-3.29239
14.0 19.00000 30.22000
 16 
8.24944 -0.00126
-3.60507
8.0 21.00000 30.33000


09:52 Monday, January 22, 2018
3
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,R)-M18 - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
DESCRIPTIVE RESULTS (OVERALL)
--------------------- SUMMARY REPORT ---------------------
09:52 Monday, January 22, 2018
3
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,R)-M18 - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
DESCRIPTIVE RESULTS (OVERALL)
--------------------- SUMMARY REPORT ---------------------
Parameter
Renal
Function
Group
n
Min
Mean
Geometric
Mean
Median
Max
Standard
Deviation
Coefficient
of
Variation
Cmax
Normal
8
34.50000
65.38750
63.31345
67.25000
89.90000
16.26885
24.881
Cmax
Severe
8
68.30000
87.71250
86.01138
84.30000
132.00000
19.92468
22.716
Tmax
Normal
8
4.00000
7.00417
6.73067
8.00000
8.03333
1.85425
26.473
Tmax
Severe
8
6.00000
9.51042
9.12592
10.00000
12.08333
2.78831
29.318
AUCT
Normal
8
629.62000 1382.57708 1331.24627 1430.54000 1765.70500
344.31954
24.904
AUCT
Severe
8 1736.29833 2274.51750 2222.65966 2152.48625 3378.34583
548.58434
24.119
Thalf
Normal
8
8.04806
11.03467
10.80637
11.59593
14.31625
2.36420
21.425
Thalf
Severe
8
18.65050
28.29432
26.89951
25.13666
45.55366
10.19501
36.032
Ae
Normal
8
0.70113
1.65046
1.57734
1.79599
2.26527
0.45045
27.292
Ae
Severe
8
0.31198
0.77748
0.68529
0.62065
1.48157
0.41738
53.684
AUCinf
Normal
8
737.98538 1593.83568 1534.56427 1681.20781 2046.25114
401.22674
25.174
AUCinf
Severe
8 2671.16709 4175.96490 3952.91869 3671.87313 6704.18507 1522.00659
36.447
Res_Area
Normal
8
6.24813
13.10191
12.03682
13.70543
20.70927
5.40626
41.263
Res_Area
Severe
8
29.84127
42.52964
41.14168
40.29860
61.62792
12.05540
28.346
Lambda_z
Normal
8
0.04842
0.06554
0.06414
0.06011
0.08613
0.01463
22.329
Lambda_z
Severe
8
0.01522
0.02693
0.02577
0.02758
0.03717
0.00796
29.562
lnCmax
Normal
8
3.54096
4.14810
4.20804
4.49870
0.28544
6.881
lnCmax
Severe
8
4.22391
4.45448
4.43391
4.88280
0.20467
4.595
lnAUCT
Normal
8
6.44512
7.19387
7.26579
7.47631
0.32103
4.463
lnAUCT
Severe
8
7.45951
7.70646
7.67370
8.12514
0.22443
2.912
lnAUCinf
Normal
8
6.60392
7.33600
7.42709
7.62376
0.31967
4.358
lnAUCinf
Severe
8
7.89027
8.28221
8.20758
8.81049
0.34912
4.215
lnAe
Normal
8
-0.35506
0.45574
0.58555
0.81769
0.35217
77.275
lnAe
Severe
8
-1.16481
-0.37791
-0.47871
0.39310
0.53952
-142.764
lnLambda_z Normal
8
-3.02791
-2.74665
-2.81436
-2.45194
0.22075
-8.037
lnLambda_z Severe
8
-4.18540
-3.65862
-3.59074
-3.29239
0.33020
-9.025
RkTmax
Normal
8
1.50000
6.87500
5.53798
8.00000
12.00000
3.59315
52.264
RkTmax
Severe
8
3.50000
10.12500
8.75190
11.00000
16.00000
5.01960
49.576


09:52 Monday, January 22, 2018
4
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,R)-M18 - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
--------------------- SUMMARY REPORT ---------------------
The Mixed Procedure
09:52 Monday, January 22, 2018
4
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,R)-M18 - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
--------------------- SUMMARY REPORT ---------------------
The Mixed Procedure
Order=1 Param=Cmax
Model Information
 Data Set 
WORK.KINDATA
 Dependent Variable 
Value
 Covariance Structure 
Variance Components
 Group Effect 
FunctionGroup
 Estimation Method 
REML
 Residual Variance Method 
None
 Fixed Effects SE Method 
Model-Based
 Degrees of Freedom Method Between-Within
Class Level Information
Class
Levels
Values
 FunctionGroup 
2 Severe Normal
Dimensions
 Covariance Parameters 
2
 Columns in X 
3
 Columns in Z 
0
 Subjects 
16
 Max Obs per Subject 
1
Number of Observations
 Number of Observations Read 
16
 Number of Observations Used 
16
 Number of Observations Not Used 
0
Iteration History
Iteration Evaluations -2 Res Log Like Criterion
      0 
1
125.11180089
      1 
1
124.82611966 0.00000000
Convergence criteria met.
Covariance Parameter Estimates
Cov Parm
Group
Estimate
 Residual FunctionGroup Severe
396.99
 Residual FunctionGroup Normal
264.68
Fit Statistics
 -2 Res Log Likelihood 
124.8
 AIC (Smaller is Better) 
128.8
 AICC (Smaller is Better) 129.9
 BIC (Smaller is Better) 
130.4
Null Model Likelihood
Ratio Test
DF
Chi-Square Pr > ChiSq
1
0.29
0.5930
Type 3 Tests of Fixed Effects
Effect
Num
DF
Den
DF
F Value Pr > F
 FunctionGroup 
1
14
6.03 0.0278
Least Squares Means
Effect
Renal
Function
Group
Estimate Standard
Error
DF t Value Pr > |t| Alpha
Lower
Upper
 FunctionGroup Severe
87.7125
7.0444 14
12.45
<.0001
0.1 75.3051
100.12
 FunctionGroup Normal
65.3875
5.7519 14
11.37
<.0001
0.1 55.2566 75.5184
Differences of Least Squares Means
Effect
Renal
Function
Group
Renal
Function
Group
Estimate Standard
Error
DF t Value Pr > |t| Alpha
Lower
Upper
 FunctionGroup Severe
Normal
22.3250
9.0944 14
2.45
0.0278
0.1 6.3069 38.3431


09:52 Monday, January 22, 2018
5
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,R)-M18 - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
--------------------- SUMMARY REPORT ---------------------
The Mixed Procedure
09:52 Monday, January 22, 2018
5
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,R)-M18 - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
--------------------- SUMMARY REPORT ---------------------
The Mixed Procedure
Order=3 Param=AUCT
Model Information
 Data Set 
WORK.KINDATA
 Dependent Variable 
Value
 Covariance Structure 
Variance Components
 Group Effect 
FunctionGroup
 Estimation Method 
REML
 Residual Variance Method 
None
 Fixed Effects SE Method 
Model-Based
 Degrees of Freedom Method Between-Within
Class Level Information
Class
Levels
Values
 FunctionGroup 
2 Severe Normal
Dimensions
 Covariance Parameters 
2
 Columns in X 
3
 Columns in Z 
0
 Subjects 
16
 Max Obs per Subject 
1
Number of Observations
 Number of Observations Read 
16
 Number of Observations Used 
16
 Number of Observations Not Used 
0
Iteration History
Iteration Evaluations -2 Res Log Like Criterion
      0 
1
215.44058880
      1 
1
213.97391815 0.00000000
Convergence criteria met.
Covariance Parameter Estimates
Cov Parm
Group
Estimate
 Residual FunctionGroup Severe
300945
 Residual FunctionGroup Normal
118556
Fit Statistics
 -2 Res Log Likelihood 
214.0
 AIC (Smaller is Better) 
218.0
 AICC (Smaller is Better) 219.1
 BIC (Smaller is Better) 
219.5
Null Model Likelihood
Ratio Test
DF
Chi-Square Pr > ChiSq
1
1.47
0.2259
Type 3 Tests of Fixed Effects
Effect
Num
DF
Den
DF
F Value Pr > F
 FunctionGroup 
1
14
15.17 0.0016
Least Squares Means
Effect
Renal
Function
Group
Estimate Standard
Error
DF t Value Pr > |t| Alpha
Lower
Upper
 FunctionGroup Severe
2274.52
193.95 14
11.73
<.0001
0.1 1932.90 2616.13
 FunctionGroup Normal
1382.58
121.74 14
11.36
<.0001
0.1 1168.16 1596.99
Differences of Least Squares Means
Effect
Renal
Function
Group
Renal
Function
Group
Estimate Standard
Error
DF t Value Pr > |t| Alpha
Lower
Upper
 FunctionGroup Severe
Normal
891.94
228.99 14
3.90
0.0016
0.1 488.61 1295.27


09:52 Monday, January 22, 2018
6
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,R)-M18 - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
--------------------- SUMMARY REPORT ---------------------
The Mixed Procedure
09:52 Monday, January 22, 2018
6
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,R)-M18 - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
--------------------- SUMMARY REPORT ---------------------
The Mixed Procedure
Order=6 Param=AUCinf
Model Information
 Data Set 
WORK.KINDATA
 Dependent Variable 
Value
 Covariance Structure 
Variance Components
 Group Effect 
FunctionGroup
 Estimation Method 
REML
 Residual Variance Method 
None
 Fixed Effects SE Method 
Model-Based
 Degrees of Freedom Method Between-Within
Class Level Information
Class
Levels
Values
 FunctionGroup 
2 Severe Normal
Dimensions
 Covariance Parameters 
2
 Columns in X 
3
 Columns in Z 
0
 Subjects 
16
 Max Obs per Subject 
1
Number of Observations
 Number of Observations Read 
16
 Number of Observations Used 
16
 Number of Observations Not Used 
0
Iteration History
Iteration Evaluations -2 Res Log Like Criterion
      0 
1
240.30367540
      1 
1
230.40152400 0.00000000
Convergence criteria met.
Covariance Parameter Estimates
Cov Parm
Group
Estimate
 Residual FunctionGroup Severe
2316504
 Residual FunctionGroup Normal
160983
Fit Statistics
 -2 Res Log Likelihood 
230.4
 AIC (Smaller is Better) 
234.4
 AICC (Smaller is Better) 235.5
 BIC (Smaller is Better) 
235.9
Null Model Likelihood
Ratio Test
DF
Chi-Square Pr > ChiSq
1
9.90
0.0017
Type 3 Tests of Fixed Effects
Effect
Num
DF
Den
DF
F Value Pr > F
 FunctionGroup 
1
14
21.53 0.0004
Least Squares Means
Effect
Renal
Function
Group
Estimate Standard
Error
DF t Value Pr > |t| Alpha
Lower
Upper
 FunctionGroup Severe
4175.96
538.11 14
7.76
<.0001
0.1 3228.19 5123.74
 FunctionGroup Normal
1593.84
141.86 14
11.24
<.0001
0.1 1343.98 1843.69
Differences of Least Squares Means
Effect
Renal
Function
Group
Renal
Function
Group
Estimate Standard
Error
DF t Value Pr > |t| Alpha
Lower
Upper
 FunctionGroup Severe
Normal
2582.13
556.49 14
4.64
0.0004
0.1 1601.97 3562.29


09:52 Monday, January 22, 2018
7
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,R)-M18 - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
--------------------- SUMMARY REPORT ---------------------
The Mixed Procedure
09:52 Monday, January 22, 2018
7
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,R)-M18 - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
--------------------- SUMMARY REPORT ---------------------
The Mixed Procedure
Order=9 Param=lnCmax
Model Information
 Data Set 
WORK.KINDATA
 Dependent Variable 
Value
 Covariance Structure 
Variance Components
 Group Effect 
FunctionGroup
 Estimation Method 
REML
 Residual Variance Method 
None
 Fixed Effects SE Method 
Model-Based
 Degrees of Freedom Method Between-Within
Class Level Information
Class
Levels
Values
 FunctionGroup 
2 Severe Normal
Dimensions
 Covariance Parameters 
2
 Columns in X 
3
 Columns in Z 
0
 Subjects 
16
 Max Obs per Subject 
1
Number of Observations
 Number of Observations Read 
16
 Number of Observations Used 
16
 Number of Observations Not Used 
0
Iteration History
Iteration Evaluations -2 Res Log Like Criterion
      0 
1
4.88862737
      1 
1
4.12790664 0.00000000
Convergence criteria met.
Covariance Parameter Estimates
Cov Parm
Group
Estimate
 Residual FunctionGroup Severe
0.04189
 Residual FunctionGroup Normal
0.08148
Fit Statistics
 -2 Res Log Likelihood 
4.1
 AIC (Smaller is Better) 
8.1
 AICC (Smaller is Better) 
9.2
 BIC (Smaller is Better) 
9.7
Null Model Likelihood
Ratio Test
DF
Chi-Square Pr > ChiSq
1
0.76
0.3831
Type 3 Tests of Fixed Effects
Effect
Num
DF
Den
DF
F Value Pr > F
 FunctionGroup 
1
14
6.09 0.0271
Least Squares Means
Effect
Renal
Function
Group
Estimate Standard
Error
DF t Value Pr > |t| Alpha
Lower
Upper
 FunctionGroup Severe
4.4545
0.07236 14
61.56
<.0001
0.1 4.3270 4.5819
 FunctionGroup Normal
4.1481
0.1009 14
41.10
<.0001
0.1 3.9703 4.3258
Differences of Least Squares Means
Effect
Renal
Function
Group
Renal
Function
Group
Estimate Standard
Error
DF t Value Pr > |t| Alpha
Lower
Upper
 FunctionGroup Severe
Normal
0.3064
0.1242 14
2.47
0.0271
0.1 0.08766 0.5251


09:52 Monday, January 22, 2018
8
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,R)-M18 - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
--------------------- SUMMARY REPORT ---------------------
The Mixed Procedure
09:52 Monday, January 22, 2018
8
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,R)-M18 - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
--------------------- SUMMARY REPORT ---------------------
The Mixed Procedure
Order=10 Param=lnAUCT
Model Information
 Data Set 
WORK.KINDATA
 Dependent Variable 
Value
 Covariance Structure 
Variance Components
 Group Effect 
FunctionGroup
 Estimation Method 
REML
 Residual Variance Method 
None
 Fixed Effects SE Method 
Model-Based
 Degrees of Freedom Method Between-Within
Class Level Information
Class
Levels
Values
 FunctionGroup 
2 Severe Normal
Dimensions
 Covariance Parameters 
2
 Columns in X 
3
 Columns in Z 
0
 Subjects 
16
 Max Obs per Subject 
1
Number of Observations
 Number of Observations Read 
16
 Number of Observations Used 
16
 Number of Observations Not Used 
0
Iteration History
Iteration Evaluations -2 Res Log Like Criterion
      0 
1
7.94191682
      1 
1
7.06343593 0.00000000
Convergence criteria met.
Covariance Parameter Estimates
Cov Parm
Group
Estimate
 Residual FunctionGroup Severe
0.05037
 Residual FunctionGroup Normal
0.1031
Fit Statistics
 -2 Res Log Likelihood 
7.1
 AIC (Smaller is Better) 
11.1
 AICC (Smaller is Better) 
12.2
 BIC (Smaller is Better) 
12.6
Null Model Likelihood
Ratio Test
DF
Chi-Square Pr > ChiSq
1
0.88
0.3486
Type 3 Tests of Fixed Effects
Effect
Num
DF
Den
DF
F Value Pr > F
 FunctionGroup 
1
14
13.70 0.0024
Least Squares Means
Effect
Renal
Function
Group
Estimate Standard
Error
DF t Value Pr > |t| Alpha
Lower
Upper
 FunctionGroup Severe
7.7065
0.07935 14
97.12
<.0001
0.1 7.5667 7.8462
 FunctionGroup Normal
7.1939
0.1135 14
63.38
<.0001
0.1 6.9940 7.3938
Differences of Least Squares Means
Effect
Renal
Function
Group
Renal
Function
Group
Estimate Standard
Error
DF t Value Pr > |t| Alpha
Lower
Upper
 FunctionGroup Severe
Normal
0.5126
0.1385 14
3.70
0.0024
0.1 0.2687 0.7565


09:52 Monday, January 22, 2018
9
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,R)-M18 - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
--------------------- SUMMARY REPORT ---------------------
The Mixed Procedure
09:52 Monday, January 22, 2018
9
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,R)-M18 - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
--------------------- SUMMARY REPORT ---------------------
The Mixed Procedure
Order=11 Param=lnAUCinf
Model Information
 Data Set 
WORK.KINDATA
 Dependent Variable 
Value
 Covariance Structure 
Variance Components
 Group Effect 
FunctionGroup
 Estimation Method 
REML
 Residual Variance Method 
None
 Fixed Effects SE Method 
Model-Based
 Degrees of Freedom Method Between-Within
Class Level Information
Class
Levels
Values
 FunctionGroup 
2 Severe Normal
Dimensions
 Covariance Parameters 
2
 Columns in X 
3
 Columns in Z 
0
 Subjects 
16
 Max Obs per Subject 
1
Number of Observations
 Number of Observations Read 
16
 Number of Observations Used 
16
 Number of Observations Not Used 
0
Iteration History
Iteration Evaluations -2 Res Log Like Criterion
      0 
1
13.24438753
      1 
1
13.19010744 0.00000000
Convergence criteria met.
Covariance Parameter Estimates
Cov Parm
Group
Estimate
 Residual FunctionGroup Severe
0.1219
 Residual FunctionGroup Normal
0.1022
Fit Statistics
 -2 Res Log Likelihood 
13.2
 AIC (Smaller is Better) 
17.2
 AICC (Smaller is Better) 
18.3
 BIC (Smaller is Better) 
18.7
Null Model Likelihood
Ratio Test
DF
Chi-Square Pr > ChiSq
1
0.05
0.8158
Type 3 Tests of Fixed Effects
Effect
Num
DF
Den
DF
F Value Pr > F
 FunctionGroup 
1
14
31.96 <.0001
Least Squares Means
Effect
Renal
Function
Group
Estimate Standard
Error
DF t Value Pr > |t| Alpha
Lower
Upper
 FunctionGroup Severe
8.2822
0.1234 14
67.10
<.0001
0.1 8.0648 8.4996
 FunctionGroup Normal
7.3360
0.1130 14
64.91
<.0001
0.1 7.1369 7.5351
Differences of Least Squares Means
Effect
Renal
Function
Group
Renal
Function
Group
Estimate Standard
Error
DF t Value Pr > |t| Alpha
Lower
Upper
 FunctionGroup Severe
Normal
0.9462
0.1674 14
5.65
<.0001
0.1 0.6514 1.2410


09:52 Monday, January 22, 2018
10
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,R)-M18 - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
--------------------- SUMMARY REPORT ---------------------
The Mixed Procedure
09:52 Monday, January 22, 2018
10
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,R)-M18 - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
--------------------- SUMMARY REPORT ---------------------
The Mixed Procedure
Order=14 Param=RkTmax
Model Information
 Data Set 
WORK.KINDATA
 Dependent Variable 
Value
 Covariance Structure 
Variance Components
 Group Effect 
FunctionGroup
 Estimation Method 
REML
 Residual Variance Method 
None
 Fixed Effects SE Method 
Model-Based
 Degrees of Freedom Method Between-Within
Class Level Information
Class
Levels
Values
 FunctionGroup 
2 Severe Normal
Dimensions
 Covariance Parameters 
2
 Columns in X 
3
 Columns in Z 
0
 Subjects 
16
 Max Obs per Subject 
1
Number of Observations
 Number of Observations Read 
16
 Number of Observations Used 
16
 Number of Observations Not Used 
0
Iteration History
Iteration Evaluations -2 Res Log Like Criterion
      0 
1
85.15072586
      1 
1
84.38248056 0.00000000
Convergence criteria met.
Covariance Parameter Estimates
Cov Parm
Group
Estimate
 Residual FunctionGroup Severe
25.1964
 Residual FunctionGroup Normal
12.9107
Fit Statistics
 -2 Res Log Likelihood 
84.4
 AIC (Smaller is Better) 
88.4
 AICC (Smaller is Better) 
89.5
 BIC (Smaller is Better) 
89.9
Null Model Likelihood
Ratio Test
DF
Chi-Square Pr > ChiSq
1
0.77
0.3808
Type 3 Tests of Fixed Effects
Effect
Num
DF
Den
DF
F Value Pr > F
 FunctionGroup 
1
14
2.22 0.1586
Least Squares Means
Effect
Renal
Function
Group
Estimate Standard
Error
DF t Value Pr > |t| Alpha
Lower
Upper
 FunctionGroup Severe
10.1250
1.7747 14
5.71
<.0001
0.1 6.9992 13.2508
 FunctionGroup Normal
6.8750
1.2704 14
5.41
<.0001
0.1 4.6375
9.1125
Differences of Least Squares Means
Effect
Renal
Function
Group
Renal
Function
Group
Estimate Standard
Error
DF t Value Pr > |t| Alpha
Lower
Upper
 FunctionGroup Severe
Normal
3.2500
2.1825 14
1.49
0.1586
0.1 -0.5941 7.0941


09:52 Monday, January 22, 2018
11
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,R)-M18 - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
Geometric LSmeans
--------------------- SUMMARY REPORT ---------------------
09:52 Monday, January 22, 2018
11
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,R)-M18 - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
Geometric LSmeans
--------------------- SUMMARY REPORT ---------------------
Obs Parameters Group GeoLSmeans
 1 lnCmax
Severe
86.0114
 2 lnCmax
Normal
63.3135
 3 lnAUCT
Severe
2222.66
 4 lnAUCT
Normal
1331.25
 5 lnAUCinf
Severe
3952.92
 6 lnAUCinf
Normal
1534.56


09:52 Monday, January 22, 2018
12
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,R)-M18 - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
RATIO ESTIMATE BASED ON ln-TRANSFORMED PARAMETERS
--------------------- SUMMARY REPORT ---------------------
09:52 Monday, January 22, 2018
12
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,R)-M18 - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
RATIO ESTIMATE BASED ON ln-TRANSFORMED PARAMETERS
--------------------- SUMMARY REPORT ---------------------
Obs Parameters Group
vs
Group
Ratio
(%)
L90
U90
 1 lnCmax
Severe Normal 135.850 109.162 169.063
 2 lnAUCT
Severe Normal 166.961 130.822 213.082
 3 lnAUCinf
Severe Normal 257.592 191.829 345.901


Clinical Study Report  
Project No COL MIG-113/H8H-CD-LAHN 
 
16.1.9.5 Documentation of statistical analysis – SAS® output of (S,S)-M18 
 
Legend:  
AUCinf= AUC(0−∞) 
AUCT=AUC(0-tlast) 
Vz_F= VZ/F 
CL_F= CL/F 
LambdaZ = λZ 
lCmax= ln(Cmax) 
lAUCT= ln(AUC(0-tlast)) 
lAUCinf= ln(AUC(0−∞)) 
lCLF= ln(CL/F) 
lLambdaZ = ln(λZ) 
lVz_F= ln(VZ/F) 
RkTmax= Rank of Tmax 


11:14 Monday, February 12, 2018
1
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,S)-M18
(Healthy vs Severe)
ANOVA analysis
RAW DATA
--------------------- SUMMARY REPORT ---------------------
11:14 Monday, February 12, 2018
1
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,S)-M18
(Healthy vs Severe)
ANOVA analysis
RAW DATA
--------------------- SUMMARY REPORT ---------------------
Renal Function Group=Normal
Obs Subject
Cmax
Tmax
AUCT
Thalf
Ae
AUCinf
Res_Area Lambda_z lnCmax
lnAUCT
 1 101
11.60000 4.00000 251.07875 11.49043 0.29028 291.46523 13.85636
0.06032 2.45101 5.52577
 2 102
11.60000 6.00000 237.11000
9.64792 0.36323 262.55454
9.69115
0.07184 2.45101 5.46852
 3 103
30.50000 4.00000 410.77500
6.13046 0.68963 420.79761
2.38181
0.11307 3.41773 6.01805
 4 104
17.70000 4.05000 250.40233
6.75169 0.35708 284.88339 12.10357
0.10266 2.87356 5.52307
 5 105
10.20000 6.00000 140.57375
8.09317 0.17223 165.52203 15.07248
0.08565 2.32239 4.94573
 6 106
26.20000 4.00000 294.73500
6.55312 0.49921 327.35368
9.96435
0.10577 3.26576 5.68608
 7 107
16.30000 8.03333 262.55675 10.35958 0.35874 290.19352
9.52357
0.06691 2.79117 5.57047
 8 108
15.70000 8.00000 298.52700
7.04445 0.35671 315.40243
5.35045
0.09840 2.75366 5.69886
Obs lnAUCinf
lnAe
lnLambda_z RkTmax
eGFR
CrCL
 1 
5.67492 -1.23692
-2.80803
5.0 115.00000 163.85000
 2 
5.57046 -1.01271
-2.63325
9.5 102.00000 152.84000
 3 
6.04215 -0.37160
-2.17978
5.0
94.00000 100.45000
 4 
5.65208 -1.02980
-2.27631
8.0 109.00000 124.34000
 5 
5.10910 -1.75895
-2.45753
9.5 102.00000 155.18000
 6 
5.79104 -0.69474
-2.24645
5.0 116.00000 120.18000
 7 
5.67055 -1.02517
-2.70442
13.0
98.00000 116.39000
 8 
5.75385 -1.03082
-2.31875
11.5 118.00000 147.36000


11:14 Monday, February 12, 2018
2
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,S)-M18
(Healthy vs Severe)
ANOVA analysis
RAW DATA
--------------------- SUMMARY REPORT ---------------------
11:14 Monday, February 12, 2018
2
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,S)-M18
(Healthy vs Severe)
ANOVA analysis
RAW DATA
--------------------- SUMMARY REPORT ---------------------
Renal Function Group=Severe
Obs Subject
Cmax
Tmax
AUCT
Thalf
Ae
AUCinf
Res_Area Lambda_z lnCmax
lnAUCT
 9 201
8.63000
8.00000 226.50375 23.37308 0.05148 360.22751 37.12203
0.02966 2.15524 5.42276
 10 202
20.30000
4.00000 321.06250 14.67003 0.10180 393.73800 18.45783
0.04725 3.01062 5.77164
 11 203
17.90000 12.00000 355.50900 15.98556 0.28436 464.47530 23.46008
0.04336 2.88480 5.87355
 12 204
17.00000 12.00000 394.10558 13.57770 0.14649 489.91608 19.55651
0.05105 2.83321 5.97662
 13 205
21.40000
3.00000 392.19250 12.93609 0.08889 464.78850 15.61915
0.05358 3.06339 5.97175
 14 206
25.80000
3.00000 430.38083 17.84727 0.08234 559.95407 23.13998
0.03884 3.25037 6.06467
 15 207
21.10000
4.00000 312.17500 11.80038 0.10227 359.52637 13.17049
0.05874 3.04927 5.74356
 16 208
8.61000 12.08333 211.49083 24.81341 0.05965 356.02825 40.59718
0.02793 2.15292 5.35418
Obs lnAUCinf
lnAe
lnLambda_z RkTmax
eGFR
CrCL
 9 
5.88674 -2.96660
-3.51810
11.5 26.00000 40.09000
 10 
5.97569 -2.28477
-3.05232
5.0 23.00000 29.51000
 11 
6.14091 -1.25750
-3.13820
14.5 26.00000 43.68000
 12 
6.19423 -1.92077
-2.97494
14.5 19.00000 30.22000
 13 
6.14158 -2.42039
-2.92653
1.5 27.00000 26.90000
 14 
6.32785 -2.49689
-3.24836
1.5 16.00000 20.27000
 15 
5.88479 -2.28014
-2.83464
5.0 21.00000 30.33000
 16 
5.87501 -2.81924
-3.57790
16.0 28.00000 65.77000


11:14 Monday, February 12, 2018
3
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,S)-M18
(Healthy vs Severe)
ANOVA analysis
DESCRIPTIVE RESULTS (OVERALL)
--------------------- SUMMARY REPORT ---------------------
11:14 Monday, February 12, 2018
3
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,S)-M18
(Healthy vs Severe)
ANOVA analysis
DESCRIPTIVE RESULTS (OVERALL)
--------------------- SUMMARY REPORT ---------------------
Parameter
Renal
Function
Group
n
Min
Mean
Geometric
Mean
Median
Max
Standard
Deviation
Coefficient
of
Variation
Cmax
Normal
8
10.20000
17.47500
16.29379
16.00000
30.50000
7.29300
41.7339
Cmax
Severe
8
8.61000
17.59250
16.44432
19.10000
25.80000
6.12898
34.8386
Tmax
Normal
8
4.00000
5.51042
5.27522
5.02500
8.03333
1.77359
32.1862
Tmax
Severe
8
3.00000
7.26042
6.13409
6.00000
12.08333
4.24765
58.5042
AUCT
Normal
8 140.57375 268.21982 258.41524 256.81775 410.77500
75.44937
28.1297
AUCT
Severe
8 211.49083 330.42750 321.28929 338.28575 430.38083
79.15310
23.9548
Thalf
Normal
8
6.13046
8.25885
8.05710
7.56881
11.49043
1.99997
24.2160
Thalf
Severe
8
11.80038
16.87544
16.31952
15.32780
24.81341
4.84002
28.6809
Ae
Normal
8
0.17223
0.38589
0.36056
0.35791
0.68963
0.15252
39.5232
Ae
Severe
8
0.05148
0.11466
0.09968
0.09534
0.28436
0.07451
64.9800
AUCinf
Normal
8 165.52203 294.77155 286.58045 290.82938 420.79761
70.95555
24.0714
AUCinf
Severe
8 356.02825 431.08176 425.53613 429.10665 559.95407
75.10840
17.4232
Res_Area
Normal
8
2.38181
9.74297
8.58932
9.82775
15.07248
4.21692
43.2817
Res_Area
Severe
8
13.17049
23.89041
22.28147
21.34824
40.59718
9.90358
41.4542
Lambda_z
Normal
8
0.06032
0.08808
0.08603
0.09202
0.11307
0.01980
22.4815
Lambda_z
Severe
8
0.02793
0.04380
0.04247
0.04531
0.05874
0.01108
25.3046
lnCmax
Normal
8
2.32239
2.79078
2.77241
3.41773
0.39228
14.0563
lnCmax
Severe
8
2.15292
2.79998
2.94771
3.25037
0.41772
14.9186
lnAUCT
Normal
8
4.94573
5.55457
5.54812
6.01805
0.30073
5.4142
lnAUCT
Severe
8
5.35418
5.77234
5.82259
6.06467
0.26052
4.5132
lnAUCinf
Normal
8
5.10910
5.65802
5.67273
6.04215
0.26292
4.6469
lnAUCinf
Severe
8
5.87501
6.05335
6.05830
6.32785
0.17099
2.8247
lnAe
Normal
8
-1.75895
-1.02009
-1.02748
-0.37160
0.39993
-39.2056
lnAe
Severe
8
-2.96660
-2.30579
-2.35258
-1.25750
0.53428
-23.1713
lnLambda_z Normal
8
-2.80803
-2.45307
-2.38814
-2.17978
0.23553
-9.6015
lnLambda_z Severe
8
-3.57790
-3.15887
-3.09526
-2.83464
0.27186
-8.6062
RkTmax
Normal
8
5.00000
8.31250
7.78504
8.75000
13.00000
3.11606
37.4864
RkTmax
Severe
8
1.50000
8.68750
6.19740
8.25000
16.00000
6.08826
70.0807


11:14 Monday, February 12, 2018
4
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,S)-M18
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:14 Monday, February 12, 2018
4
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,S)-M18
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=9 Param=lnCmax
 Number of Observations Read 16
 Number of Observations Used 16
Analysis of Variance
Source
DF Sum of
Squares
Mean
Square
F Value Pr > F
 Model 
1 0.00639 0.00639
0.04 0.8462
 Error 
14 2.29255 0.16375
 Corrected Total 15 2.29894
 Root MSE 
0.40467  R-Square 
0.0028
 Dependent Mean 
2.79538  Adj R-Sq -0.0685
 Coeff Var 
14.47620    
Parameter Estimates
Variable
Label
DF
Parameter
Estimate
Standard
Error
t Value Pr > |t|
95%
Confidence
Limits
 Intercept Intercept
1
2.82612
0.18557
15.23
<.0001
2.42810 3.22413
 eGFR 
eGFR
1 -0.00047282
0.00239
-0.20
0.8462 -0.00561 0.00466


11:14 Monday, February 12, 2018
5
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,S)-M18
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:14 Monday, February 12, 2018
5
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,S)-M18
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=9 Param=lnCmax
Output Statistics
Obs
Dependent
Variable
Predicted
Value
Std Error
Mean Predict
Residual Std Error
Residual
Student
Residual
-2-1 0 1 2
Cook's
D
        1 
2.4510
2.7717
0.1567
-0.3207
0.373
-0.860  |     *|      | 
0.065
        2 
2.4510
2.7779
0.1345
-0.3269
0.382
-0.856  |     *|      | 
0.046
        3 
3.4177
2.7817
0.1227
0.6361
0.386
1.649  |      |***   | 
0.138
        4 
2.8736
2.7746
0.1460
0.0990
0.377
0.262  |      |      | 
0.005
        5 
2.3224
2.7779
0.1345
-0.4555
0.382
-1.193  |    **|      | 
0.088
        6 
3.2658
2.7713
0.1585
0.4945
0.372
1.328  |      |**    | 
0.160
        7 
2.7912
2.7798
0.1283
0.0114
0.384
0.0297  |      |      | 
0.000
        8 
2.7537
2.7703
0.1623
-0.0167
0.371
-0.0449  |      |      | 
0.000
        9 
2.1552
2.8138
0.1377
-0.6586
0.381
-1.731  |   ***|      | 
0.196
       10 
3.0106
2.8152
0.1426
0.1954
0.379
0.516  |      |*     | 
0.019
       11 
2.8848
2.8138
0.1377
0.0710
0.381
0.187  |      |      | 
0.002
       12 
2.8332
2.8171
0.1495
0.0161
0.376
0.0428  |      |      | 
0.000
       13 
3.0634
2.8133
0.1360
0.2500
0.381
0.656  |      |*     | 
0.027
       14 
3.2504
2.8186
0.1549
0.4318
0.374
1.155  |      |**    | 
0.114
       15 
3.0493
2.8162
0.1460
0.2331
0.377
0.618  |      |*     | 
0.029
       16 
2.1529
2.8129
0.1345
-0.6600
0.382
-1.729  |   ***|      | 
0.185
 Sum of Residuals 
0
 Sum of Squared Residuals 
2.29255
 Predicted Residual SS (PRESS) 2.95371


11:14 Monday, February 12, 2018
6
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,S)-M18
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:14 Monday, February 12, 2018
6
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,S)-M18
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=10 Param=lnAUCT
 Number of Observations Read 16
 Number of Observations Used 16
Analysis of Variance
Source
DF Sum of
Squares
Mean
Square
F Value Pr > F
 Model 
1 0.21173 0.21173
2.73 0.1208
 Error 
14 1.08615 0.07758
 Corrected Total 15 1.29787
 Root MSE 
0.27854  R-Square 0.1631
 Dependent Mean 5.66345  Adj R-Sq 0.1034
 Coeff Var 
4.91812    
Parameter Estimates
Variable
Label
DF Parameter
Estimate
Standard
Error
t Value Pr > |t|
95%
Confidence Limits
 Intercept Intercept
1
5.84035
0.12773
45.72
<.0001
5.56640
6.11431
 eGFR 
eGFR
1
-0.00272
0.00165
-1.65
0.1208 -0.00625 0.00081184


11:14 Monday, February 12, 2018
7
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,S)-M18
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:14 Monday, February 12, 2018
7
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,S)-M18
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=10 Param=lnAUCT
Output Statistics
Obs
Dependent
Variable
Predicted
Value
Std Error
Mean Predict
Residual Std Error
Residual
Student
Residual
-2-1 0 1 2
Cook's
D
        1 
5.5258
5.5274
0.1079 -0.001612
0.257
-0.0063  |      |      | 
0.000
        2 
5.4685
5.5628
0.0925
-0.0942
0.263
-0.359  |      |      | 
0.008
        3 
6.0180
5.5845
0.0844
0.4335
0.265
1.633  |      |***   | 
0.135
        4 
5.5231
5.5437
0.1005
-0.0206
0.260
-0.0795  |      |      | 
0.000
        5 
4.9457
5.5628
0.0925
-0.6170
0.263
-2.349  |  ****|      | 
0.342
        6 
5.6861
5.5247
0.1091
0.1614
0.256
0.630  |      |*     | 
0.036
        7 
5.5705
5.5736
0.0883 -0.003178
0.264
-0.0120  |      |      | 
0.000
        8 
5.6989
5.5192
0.1117
0.1796
0.255
0.704  |      |*     | 
0.047
        9 
5.4228
5.7696
0.0947
-0.3468
0.262
-1.324  |    **|      | 
0.115
       10 
5.7716
5.7778
0.0982 -0.006123
0.261
-0.0235  |      |      | 
0.000
       11 
5.8736
5.7696
0.0947
0.1040
0.262
0.397  |      |      | 
0.010
       12 
5.9766
5.7886
0.1029
0.1880
0.259
0.726  |      |*     | 
0.042
       13 
5.9718
5.7669
0.0936
0.2049
0.262
0.781  |      |*     | 
0.039
       14 
6.0647
5.7968
0.1066
0.2679
0.257
1.041  |      |**    | 
0.093
       15 
5.7436
5.7832
0.1005
-0.0396
0.260
-0.153  |      |      | 
0.002
       16 
5.3542
5.7642
0.0925
-0.4100
0.263
-1.561  |   ***|      | 
0.151
 Sum of Residuals 
0
 Sum of Squared Residuals 
1.08615
 Predicted Residual SS (PRESS) 1.38435


11:14 Monday, February 12, 2018
8
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,S)-M18
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:14 Monday, February 12, 2018
8
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,S)-M18
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=11 Param=lnAUCinf
 Number of Observations Read 16
 Number of Observations Used 16
Analysis of Variance
Source
DF Sum of
Squares
Mean
Square
F Value Pr > F
 Model 
1 0.63297 0.63297
13.02 0.0029
 Error 
14 0.68073 0.04862
 Corrected Total 15 1.31370
 Root MSE 
0.22051  R-Square 0.4818
 Dependent Mean 5.85568  Adj R-Sq 0.4448
 Coeff Var 
3.76570    
Parameter Estimates
Variable
Label
DF Parameter
Estimate
Standard
Error
t Value Pr > |t|
95%
Confidence
Limits
 Intercept Intercept
1
6.16155
0.10112
60.93
<.0001
5.94466
6.37843
 eGFR 
eGFR
1
-0.00471
0.00130
-3.61
0.0029 -0.00750 -0.00191


11:14 Monday, February 12, 2018
9
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,S)-M18
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:14 Monday, February 12, 2018
9
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,S)-M18
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=11 Param=lnAUCinf
Output Statistics
Obs
Dependent
Variable
Predicted
Value
Std Error
Mean Predict
Residual Std Error
Residual
Student
Residual
-2-1 0 1 2
Cook's
D
        1 
5.6749
5.6204
0.0854
0.0545
0.203
0.268  |      |      | 
0.006
        2 
5.5705
5.6816
0.0733
-0.1111
0.208
-0.534  |     *|      | 
0.018
        3 
6.0422
5.7192
0.0669
0.3229
0.210
1.537  |      |***   | 
0.120
        4 
5.6521
5.6486
0.0796 0.003441
0.206
0.0167  |      |      | 
0.000
        5 
5.1091
5.6816
0.0733
-0.5725
0.208
-2.753  | *****|      | 
0.470
        6 
5.7910
5.6157
0.0864
0.1753
0.203
0.864  |      |*     | 
0.068
        7 
5.6705
5.7004
0.0699
-0.0299
0.209
-0.143  |      |      | 
0.001
        8 
5.7538
5.6063
0.0884
0.1476
0.202
0.730  |      |*     | 
0.051
        9 
5.8867
6.0392
0.0750
-0.1525
0.207
-0.735  |     *|      | 
0.035
       10 
5.9757
6.0533
0.0777
-0.0776
0.206
-0.376  |      |      | 
0.010
       11 
6.1409
6.0392
0.0750
0.1017
0.207
0.490  |      |      | 
0.016
       12 
6.1942
6.0721
0.0815
0.1221
0.205
0.596  |      |*     | 
0.028
       13 
6.1416
6.0345
0.0741
0.1071
0.208
0.516  |      |*     | 
0.017
       14 
6.3279
6.0863
0.0844
0.2416
0.204
1.186  |      |**    | 
0.121
       15 
5.8848
6.0627
0.0796
-0.1779
0.206
-0.865  |     *|      | 
0.056
       16 
5.8750
6.0298
0.0733
-0.1548
0.208
-0.744  |     *|      | 
0.034
 Sum of Residuals 
0
 Sum of Squared Residuals 
0.68073
 Predicted Residual SS (PRESS) 0.87286


11:14 Monday, February 12, 2018
10
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,S)-M18
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:14 Monday, February 12, 2018
10
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,S)-M18
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=12 Param=lnAe
 Number of Observations Read 16
 Number of Observations Used 16
Analysis of Variance
Source
DF Sum of
Squares
Mean
Square
F Value Pr > F
 Model 
1 6.27816 6.27816
25.46 0.0002
 Error 
14 3.45176 0.24655
 Corrected Total 15 9.72992
 Root MSE 
0.49654  R-Square 0.6452
 Dependent Mean 
-1.66294  Adj R-Sq 0.6199
 Coeff Var 
-29.85933    
Parameter Estimates
Variable
Label
DF Parameter
Estimate
Standard
Error
t Value Pr > |t|
95%
Confidence
Limits
 Intercept Intercept
1
-2.62622
0.22771
-11.53
<.0001 -3.11460 -2.13784
 eGFR 
eGFR
1
0.01482
0.00294
5.05
0.0002
0.00852
0.02112


11:14 Monday, February 12, 2018
11
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,S)-M18
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:14 Monday, February 12, 2018
11
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,S)-M18
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=12 Param=lnAe
Output Statistics
Obs
Dependent
Variable
Predicted
Value
Std Error
Mean Predict
Residual Std Error
Residual
Student
Residual
-2-1 0 1 2
Cook's
D
        1 
-1.2369
-0.9220
0.1923
-0.3150
0.458
-0.688  |     *|      | 
0.042
        2 
-1.0127
-1.1146
0.1650
0.1019
0.468
0.218  |      |      | 
0.003
        3 
-0.3716
-1.2332
0.1505
0.8616
0.473
1.821  |      |***   | 
0.168
        4 
-1.0298
-1.0109
0.1792
-0.0189
0.463
-0.0409  |      |      | 
0.000
        5 
-1.7590
-1.1146
0.1650
-0.6443
0.468
-1.376  |    **|      | 
0.117
        6 
-0.6947
-0.9071
0.1945
0.2124
0.457
0.465  |      |      | 
0.020
        7 
-1.0252
-1.1739
0.1575
0.1487
0.471
0.316  |      |      | 
0.006
        8 
-1.0308
-0.8775
0.1991
-0.1533
0.455
-0.337  |      |      | 
0.011
        9 
-2.9666
-2.2409
0.1689
-0.7257
0.467
-1.554  |   ***|      | 
0.158
       10 
-2.2848
-2.2854
0.1750 0.000591
0.465
0.00127  |      |      | 
0.000
       11 
-1.2575
-2.2409
0.1689
0.9834
0.467
2.106  |      |****  | 
0.290
       12 
-1.9208
-2.3446
0.1835
0.4239
0.461
0.919  |      |*     | 
0.067
       13 
-2.4204
-2.2261
0.1669
-0.1943
0.468
-0.415  |      |      | 
0.011
       14 
-2.4969
-2.3891
0.1900
-0.1078
0.459
-0.235  |      |      | 
0.005
       15 
-2.2801
-2.3150
0.1792
0.0349
0.463
0.0753  |      |      | 
0.000
       16 
-2.8192
-2.2113
0.1650
-0.6080
0.468
-1.298  |    **|      | 
0.105
 Sum of Residuals 
0
 Sum of Squared Residuals 
3.45176
 Predicted Residual SS (PRESS) 4.38311


11:14 Monday, February 12, 2018
12
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,S)-M18
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:14 Monday, February 12, 2018
12
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,S)-M18
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=13 Param=lnLambda_z
 Number of Observations Read 16
 Number of Observations Used 16
Analysis of Variance
Source
DF Sum of
Squares
Mean
Square
F Value Pr > F
 Model 
1 1.90378 1.90378
26.80 0.0001
 Error 
14 0.99455 0.07104
 Corrected Total 15 2.89833
 Root MSE 
0.26653  R-Square 0.6569
 Dependent Mean -2.80597  Adj R-Sq 0.6323
 Coeff Var 
-9.49874    
Parameter Estimates
Variable
Label
DF Parameter
Estimate
Standard
Error
t Value Pr > |t|
95%
Confidence
Limits
 Intercept Intercept
1
-3.33642
0.12223
-27.30
<.0001 -3.59857 -3.07427
 eGFR 
eGFR
1
0.00816
0.00158
5.18
0.0001
0.00478
0.01154


11:14 Monday, February 12, 2018
13
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,S)-M18
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:14 Monday, February 12, 2018
13
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,S)-M18
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=13 Param=lnLambda_z
Output Statistics
Obs
Dependent
Variable
Predicted
Value
Std Error
Mean Predict
Residual Std Error
Residual
Student
Residual
-2-1 0 1 2
Cook's
D
        1 
-2.8080
-2.3979
0.1032
-0.4101
0.246
-1.669  |   ***|      | 
0.246
        2 
-2.6333
-2.5040
0.0886
-0.1292
0.251
-0.514  |     *|      | 
0.016
        3 
-2.1798
-2.5693
0.0808
0.3895
0.254
1.534  |      |***   | 
0.119
        4 
-2.2763
-2.4469
0.0962
0.1706
0.249
0.686  |      |*     | 
0.035
        5 
-2.4575
-2.5040
0.0886
0.0465
0.251
0.185  |      |      | 
0.002
        6 
-2.2465
-2.3898
0.1044
0.1433
0.245
0.584  |      |*     | 
0.031
        7 
-2.7044
-2.5367
0.0845
-0.1678
0.253
-0.664  |     *|      | 
0.025
        8 
-2.3188
-2.3734
0.1069
0.0547
0.244
0.224  |      |      | 
0.005
        9 
-3.5181
-3.1242
0.0907
-0.3939
0.251
-1.571  |   ***|      | 
0.162
       10 
-3.0523
-3.1487
0.0939
0.0964
0.249
0.386  |      |      | 
0.011
       11 
-3.1382
-3.1242
0.0907
-0.0140
0.251
-0.0557  |      |      | 
0.000
       12 
-2.9749
-3.1814
0.0985
0.2064
0.248
0.833  |      |*     | 
0.055
       13 
-2.9265
-3.1161
0.0896
0.1895
0.251
0.755  |      |*     | 
0.036
       14 
-3.2484
-3.2058
0.1020
-0.0425
0.246
-0.173  |      |      | 
0.003
       15 
-2.8346
-3.1650
0.0962
0.3304
0.249
1.329  |      |**    | 
0.132
       16 
-3.5779
-3.1079
0.0886
-0.4700
0.251
-1.870  |   ***|      | 
0.217
 Sum of Residuals 
0
 Sum of Squared Residuals 
0.99455
 Predicted Residual SS (PRESS) 1.28619


11:14 Monday, February 12, 2018
14
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,S)-M18
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:14 Monday, February 12, 2018
14
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,S)-M18
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=14 Param=RkTmax
 Number of Observations Read 16
 Number of Observations Used 16
Analysis of Variance
Source
DF
Sum of
Squares
Mean
Square
F Value Pr > F
 Model 
1
0.28336
0.28336
0.01 0.9140
 Error 
14 327.71664 23.40833
 Corrected Total 15 328.00000
 Root MSE 
4.83822  R-Square 
0.0009
 Dependent Mean 
8.50000  Adj R-Sq -0.0705
 Coeff Var 
56.92019    
Parameter Estimates
Variable
Label
DF Parameter
Estimate
Standard
Error
t Value Pr > |t|
95%
Confidence
Limits
 Intercept Intercept
1
8.70465
2.21873
3.92
0.0015
3.94594 13.46335
 eGFR 
eGFR
1
-0.00315
0.02862
-0.11
0.9140 -0.06452
0.05823


11:14 Monday, February 12, 2018
15
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,S)-M18
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:14 Monday, February 12, 2018
15
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,S)-M18
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=14 Param=RkTmax
Output Statistics
Obs
Dependent
Variable
Predicted
Value
Std Error
Mean Predict
Residual Std Error
Residual
Student
Residual
-2-1 0 1 2
Cook's
D
        1 
5.0000
8.3426
1.8736
-3.3426
4.461
-0.749  |     *|      | 
0.050
        2 
9.5000
8.3835
1.6075
1.1165
4.563
0.245  |      |      | 
0.004
        3 
5.0000
8.4087
1.4669
-3.4087
4.610
-0.739  |     *|      | 
0.028
        4 
8.0000
8.3615
1.7460
-0.3615
4.512
-0.0801  |      |      | 
0.000
        5 
9.5000
8.3835
1.6075
1.1165
4.563
0.245  |      |      | 
0.004
        6 
5.0000
8.3394
1.8955
-3.3394
4.451
-0.750  |     *|      | 
0.051
        7 
13.0000
8.3961
1.5345
4.6039
4.588
1.003  |      |**    | 
0.056
        8 
11.5000
8.3331
1.9399
3.1669
4.432
0.715  |      |*     | 
0.049
        9 
11.5000
8.6228
1.6458
2.8772
4.550
0.632  |      |*     | 
0.026
       10 
5.0000
8.6322
1.7051
-3.6322
4.528
-0.802  |     *|      | 
0.046
       11 
14.5000
8.6228
1.6458
5.8772
4.550
1.292  |      |**    | 
0.109
       12 
14.5000
8.6448
1.7877
5.8552
4.496
1.302  |      |**    | 
0.134
       13 
1.5000
8.6196
1.6265
-7.1196
4.557
-1.562  |   ***|      | 
0.156
       14 
1.5000
8.6543
1.8518
-7.1543
4.470
-1.601  |   ***|      | 
0.220
       15 
5.0000
8.6385
1.7460
-3.6385
4.512
-0.806  |     *|      | 
0.049
       16 
16.0000
8.6165
1.6075
7.3835
4.563
1.618  |      |***   | 
0.162
 Sum of Residuals 
0
 Sum of Squared Residuals 
327.71664
 Predicted Residual SS (PRESS) 427.89663


11:14 Monday, February 12, 2018
16
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,S)-M18
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:14 Monday, February 12, 2018
16
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,S)-M18
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=9 Param=lnCmax
 Number of Observations Read 16
 Number of Observations Used 16
Analysis of Variance
Source
DF Sum of
Squares
Mean
Square
F Value Pr > F
 Model 
1 0.19376 0.19376
1.29 0.2754
 Error 
14 2.10519 0.15037
 Corrected Total 15 2.29894
 Root MSE 
0.38778  R-Square 0.0843
 Dependent Mean 
2.79538  Adj R-Sq 0.0189
 Coeff Var 
13.87203    
Parameter Estimates
Variable
Label
DF Parameter
Estimate
Standard
Error
t Value Pr > |t|
95%
Confidence
Limits
 Intercept Intercept
1
2.97397
0.18480
16.09
<.0001
2.57762 3.37033
 CrCL 
CrCL
1
-0.00209
0.00184
-1.14
0.2754 -0.00604 0.00186


11:14 Monday, February 12, 2018
17
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,S)-M18
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:14 Monday, February 12, 2018
17
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,S)-M18
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=9 Param=lnCmax
Output Statistics
Obs
Dependent
Variable
Predicted
Value
Std Error
Mean Predict
Residual Std Error
Residual
Student
Residual
-2-1 0 1 2
Cook's
D
        1 
2.4510
2.6316
0.1739
-0.1806
0.347
-0.521  |     *|      | 
0.034
        2 
2.4510
2.6546
0.1574
-0.2036
0.354
-0.574  |     *|      | 
0.033
        3 
3.4177
2.7641
0.1008
0.6537
0.374
1.746  |      |***   | 
0.110
        4 
2.8736
2.7141
0.1205
0.1594
0.369
0.433  |      |      | 
0.010
        5 
2.3224
2.6497
0.1608
-0.3273
0.353
-0.928  |     *|      | 
0.089
        6 
3.2658
2.7228
0.1161
0.5429
0.370
1.467  |      |**    | 
0.106
        7 
2.7912
2.7307
0.1124
0.0604
0.371
0.163  |      |      | 
0.001
        8 
2.7537
2.6660
0.1496
0.0876
0.358
0.245  |      |      | 
0.005
        9 
2.1552
2.8902
0.1280
-0.7349
0.366
-2.008  |  ****|      | 
0.246
       10 
3.0106
2.9123
0.1414
0.0983
0.361
0.272  |      |      | 
0.006
       11 
2.8848
2.8827
0.1238 0.002109
0.368
0.00574  |      |      | 
0.000
       12 
2.8332
2.9108
0.1405
-0.0776
0.361
-0.215  |      |      | 
0.003
       13 
3.0634
2.9178
0.1450
0.1456
0.360
0.405  |      |      | 
0.013
       14 
3.2504
2.9316
0.1543
0.3188
0.356
0.896  |      |*     | 
0.075
       15 
3.0493
2.9106
0.1404
0.1387
0.361
0.384  |      |      | 
0.011
       16 
2.1529
2.8365
0.1035
-0.6836
0.374
-1.829  |   ***|      | 
0.128
 Sum of Residuals 
0
 Sum of Squared Residuals 
2.10519
 Predicted Residual SS (PRESS) 2.60039


11:14 Monday, February 12, 2018
18
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,S)-M18
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:14 Monday, February 12, 2018
18
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,S)-M18
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=10 Param=lnAUCT
 Number of Observations Read 16
 Number of Observations Used 16
Analysis of Variance
Source
DF Sum of
Squares
Mean
Square
F Value Pr > F
 Model 
1 0.42771 0.42771
6.88 0.0200
 Error 
14 0.87017 0.06215
 Corrected Total 15 1.29787
 Root MSE 
0.24931  R-Square 0.3295
 Dependent Mean 5.66345  Adj R-Sq 0.2817
 Coeff Var 
4.40206    
Parameter Estimates
Variable
Label
DF Parameter
Estimate
Standard
Error
t Value Pr > |t|
95%
Confidence Limits
 Intercept Intercept
1
5.92879
0.11881
49.90
<.0001
5.67397
6.18362
 CrCL 
CrCL
1
-0.00310
0.00118
-2.62
0.0200 -0.00564 -0.00056627


11:14 Monday, February 12, 2018
19
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,S)-M18
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:14 Monday, February 12, 2018
19
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,S)-M18
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=10 Param=lnAUCT
Output Statistics
Obs
Dependent
Variable
Predicted
Value
Std Error
Mean Predict
Residual Std Error
Residual
Student
Residual
-2-1 0 1 2
Cook's
D
        1 
5.5258
5.4201
0.1118
0.1057
0.223
0.474  |      |      | 
0.028
        2 
5.4685
5.4543
0.1012
0.0143
0.228
0.0626  |      |      | 
0.000
        3 
6.0180
5.6169
0.0648
0.4011
0.241
1.666  |      |***   | 
0.101
        4 
5.5231
5.5427
0.0775
-0.0197
0.237
-0.0830  |      |      | 
0.000
        5 
4.9457
5.4470
0.1034
-0.5013
0.227
-2.210  |  ****|      | 
0.507
        6 
5.6861
5.5557
0.0747
0.1304
0.238
0.548  |      |*     | 
0.015
        7 
5.5705
5.5674
0.0723 0.003045
0.239
0.0128  |      |      | 
0.000
        8 
5.6989
5.4713
0.0962
0.2276
0.230
0.990  |      |*     | 
0.086
        9 
5.4228
5.8043
0.0823
-0.3816
0.235
-1.621  |   ***|      | 
0.161
       10 
5.7716
5.8372
0.0909
-0.0655
0.232
-0.282  |      |      | 
0.006
       11 
5.8736
5.7932
0.0796
0.0804
0.236
0.340  |      |      | 
0.007
       12 
5.9766
5.8350
0.0903
0.1417
0.232
0.610  |      |*     | 
0.028
       13 
5.9718
5.8453
0.0932
0.1265
0.231
0.547  |      |*     | 
0.024
       14 
6.0647
5.8659
0.0992
0.1988
0.229
0.869  |      |*     | 
0.071
       15 
5.7436
5.8346
0.0902
-0.0911
0.232
-0.392  |      |      | 
0.012
       16 
5.3542
5.7246
0.0665
-0.3704
0.240
-1.542  |   ***|      | 
0.091
 Sum of Residuals 
0
 Sum of Squared Residuals 
0.87017
 Predicted Residual SS (PRESS) 1.13301


11:14 Monday, February 12, 2018
20
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,S)-M18
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:14 Monday, February 12, 2018
20
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,S)-M18
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=11 Param=lnAUCinf
 Number of Observations Read 16
 Number of Observations Used 16
Analysis of Variance
Source
DF Sum of
Squares
Mean
Square
F Value Pr > F
 Model 
1 0.84028 0.84028
24.85 0.0002
 Error 
14 0.47341 0.03382
 Corrected Total 15 1.31370
 Root MSE 
0.18389  R-Square 0.6396
 Dependent Mean 5.85568  Adj R-Sq 0.6139
 Coeff Var 
3.14036    
Parameter Estimates
Variable
Label
DF Parameter
Estimate
Standard
Error
t Value Pr > |t|
95%
Confidence
Limits
 Intercept Intercept
1
6.22760
0.08763
71.06
<.0001
6.03964
6.41555
 CrCL 
CrCL
1
-0.00435 0.00087302
-4.98
0.0002 -0.00622 -0.00248


11:14 Monday, February 12, 2018
21
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,S)-M18
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:14 Monday, February 12, 2018
21
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,S)-M18
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=11 Param=lnAUCinf
Output Statistics
Obs
Dependent
Variable
Predicted
Value
Std Error
Mean Predict
Residual Std Error
Residual
Student
Residual
-2-1 0 1 2
Cook's
D
        1 
5.6749
5.5145
0.0824
0.1604
0.164
0.976  |      |*     | 
0.120
        2 
5.5705
5.5625
0.0747 0.008005
0.168
0.0476  |      |      | 
0.000
        3 
6.0422
5.7904
0.0478
0.2517
0.178
1.417  |      |**    | 
0.073
        4 
5.6521
5.6865
0.0571
-0.0344
0.175
-0.197  |      |      | 
0.002
        5 
5.1091
5.5523
0.0763
-0.4432
0.167
-2.649  | *****|      | 
0.729
        6 
5.7910
5.7046
0.0551
0.0865
0.175
0.493  |      |      | 
0.012
        7 
5.6705
5.7211
0.0533
-0.0505
0.176
-0.287  |      |      | 
0.004
        8 
5.7538
5.5863
0.0709
0.1675
0.170
0.988  |      |*     | 
0.085
        9 
5.8867
6.0531
0.0607
-0.1664
0.174
-0.959  |     *|      | 
0.056
       10 
5.9757
6.0992
0.0671
-0.1235
0.171
-0.721  |     *|      | 
0.040
       11 
6.1409
6.0375
0.0587
0.1034
0.174
0.593  |      |*     | 
0.020
       12 
6.1942
6.0961
0.0666
0.0982
0.171
0.573  |      |*     | 
0.025
       13 
6.1416
6.1105
0.0688
0.0311
0.171
0.182  |      |      | 
0.003
       14 
6.3279
6.1394
0.0732
0.1885
0.169
1.117  |      |**    | 
0.117
       15 
5.8848
6.0956
0.0666
-0.2108
0.171
-1.230  |    **|      | 
0.114
       16 
5.8750
5.9414
0.0491
-0.0664
0.177
-0.374  |      |      | 
0.005
 Sum of Residuals 
0
 Sum of Squared Residuals 
0.47341
 Predicted Residual SS (PRESS) 0.64860


11:14 Monday, February 12, 2018
22
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,S)-M18
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:14 Monday, February 12, 2018
22
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,S)-M18
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=12 Param=lnAe
 Number of Observations Read 16
 Number of Observations Used 16
Analysis of Variance
Source
DF Sum of
Squares
Mean
Square
F Value Pr > F
 Model 
1 4.63980 4.63980
12.76 0.0031
 Error 
14 5.09012 0.36358
 Corrected Total 15 9.72992
 Root MSE 
0.60298  R-Square 0.4769
 Dependent Mean 
-1.66294  Adj R-Sq 0.4395
 Coeff Var 
-36.25967    
Parameter Estimates
Variable
Label
DF Parameter
Estimate
Standard
Error
t Value Pr > |t|
95%
Confidence
Limits
 Intercept Intercept
1
-2.53687
0.28735
-8.83
<.0001 -3.15318 -1.92056
 CrCL 
CrCL
1
0.01023
0.00286
3.57
0.0031
0.00409
0.01637


11:14 Monday, February 12, 2018
23
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,S)-M18
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:14 Monday, February 12, 2018
23
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,S)-M18
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=12 Param=lnAe
Output Statistics
Obs
Dependent
Variable
Predicted
Value
Std Error
Mean Predict
Residual Std Error
Residual
Student
Residual
-2-1 0 1 2
Cook's
D
        1 
-1.2369
-0.8613
0.2703
-0.3756
0.539
-0.697  |     *|      | 
0.061
        2 
-1.0127
-0.9739
0.2448
-0.0388
0.551
-0.0704  |      |      | 
0.000
        3 
-0.3716
-1.5096
0.1567
1.1381
0.582
1.955  |      |***   | 
0.138
        4 
-1.0298
-1.2653
0.1874
0.2355
0.573
0.411  |      |      | 
0.009
        5 
-1.7590
-0.9500
0.2501
-0.8090
0.549
-1.474  |    **|      | 
0.226
        6 
-0.6947
-1.3079
0.1806
0.6131
0.575
1.066  |      |**    | 
0.056
        7 
-1.0252
-1.3466
0.1748
0.3215
0.577
0.557  |      |*     | 
0.014
        8 
-1.0308
-1.0299
0.2326 -0.000885
0.556
-0.0016  |      |      | 
0.000
        9 
-2.9666
-2.1269
0.1990
-0.8397
0.569
-1.475  |    **|      | 
0.133
       10 
-2.2848
-2.2351
0.2199
-0.0497
0.561
-0.0885  |      |      | 
0.001
       11 
-1.2575
-2.0902
0.1924
0.8327
0.571
1.457  |      |**    | 
0.120
       12 
-1.9208
-2.2278
0.2185
0.3071
0.562
0.546  |      |*     | 
0.023
       13 
-2.4204
-2.2618
0.2254
-0.1586
0.559
-0.284  |      |      | 
0.007
       14 
-2.4969
-2.3296
0.2399
-0.1673
0.553
-0.302  |      |      | 
0.009
       15 
-2.2801
-2.2267
0.2182
-0.0534
0.562
-0.0951  |      |      | 
0.001
       16 
-2.8192
-1.8643
0.1609
-0.9549
0.581
-1.643  |   ***|      | 
0.104
 Sum of Residuals 
0
 Sum of Squared Residuals 
5.09012
 Predicted Residual SS (PRESS) 6.32252


11:14 Monday, February 12, 2018
24
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,S)-M18
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:14 Monday, February 12, 2018
24
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,S)-M18
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=13 Param=lnLambda_z
 Number of Observations Read 16
 Number of Observations Used 16
Analysis of Variance
Source
DF Sum of
Squares
Mean
Square
F Value Pr > F
 Model 
1 1.30324 1.30324
11.44 0.0045
 Error 
14 1.59509 0.11394
 Corrected Total 15 2.89833
 Root MSE 
0.33754  R-Square 0.4497
 Dependent Mean 
-2.80597  Adj R-Sq 0.4103
 Coeff Var 
-12.02945    
Parameter Estimates
Variable
Label
DF Parameter
Estimate
Standard
Error
t Value Pr > |t|
95%
Confidence
Limits
 Intercept Intercept
1
-3.26914
0.16086
-20.32
<.0001 -3.61415 -2.92413
 CrCL 
CrCL
1
0.00542
0.00160
3.38
0.0045
0.00198
0.00886


11:14 Monday, February 12, 2018
25
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,S)-M18
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:14 Monday, February 12, 2018
25
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,S)-M18
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=13 Param=lnLambda_z
Output Statistics
Obs
Dependent
Variable
Predicted
Value
Std Error
Mean Predict
Residual Std Error
Residual
Student
Residual
-2-1 0 1 2
Cook's
D
        1 
-2.8080
-2.3811
0.1513
-0.4269
0.302
-1.415  |    **|      | 
0.252
        2 
-2.6333
-2.4408
0.1370
-0.1925
0.308
-0.624  |     *|      | 
0.038
        3 
-2.1798
-2.7247
0.0877
0.5449
0.326
1.672  |      |***   | 
0.101
        4 
-2.2763
-2.5953
0.1049
0.3189
0.321
0.994  |      |*     | 
0.053
        5 
-2.4575
-2.4281
0.1400
-0.0294
0.307
-0.0958  |      |      | 
0.001
        6 
-2.2465
-2.6178
0.1011
0.3713
0.322
1.153  |      |**    | 
0.065
        7 
-2.7044
-2.6383
0.0979
-0.0661
0.323
-0.205  |      |      | 
0.002
        8 
-2.3188
-2.4705
0.1302
0.1517
0.311
0.487  |      |      | 
0.021
        9 
-3.5181
-3.0519
0.1114
-0.4662
0.319
-1.463  |    **|      | 
0.131
       10 
-3.0523
-3.1092
0.1231
0.0569
0.314
0.181  |      |      | 
0.003
       11 
-3.1382
-3.0324
0.1077
-0.1058
0.320
-0.331  |      |      | 
0.006
       12 
-2.9749
-3.1054
0.1223
0.1304
0.315
0.415  |      |      | 
0.013
       13 
-2.9265
-3.1233
0.1262
0.1968
0.313
0.629  |      |*     | 
0.032
       14 
-3.2484
-3.1593
0.1343
-0.0891
0.310
-0.288  |      |      | 
0.008
       15 
-2.8346
-3.1048
0.1222
0.2701
0.315
0.858  |      |*     | 
0.056
       16 
-3.5779
-2.9127
0.0901
-0.6652
0.325
-2.045  |  ****|      | 
0.160
 Sum of Residuals 
0
 Sum of Squared Residuals 
1.59509
 Predicted Residual SS (PRESS) 1.99707


11:14 Monday, February 12, 2018
26
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,S)-M18
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:14 Monday, February 12, 2018
26
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,S)-M18
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=14 Param=RkTmax
 Number of Observations Read 16
 Number of Observations Used 16
Analysis of Variance
Source
DF
Sum of
Squares
Mean
Square
F Value Pr > F
 Model 
1
3.31172
3.31172
0.14 0.7112
 Error 
14 324.68828 23.19202
 Corrected Total 15 328.00000
 Root MSE 
4.81581  R-Square 
0.0101
 Dependent Mean 
8.50000  Adj R-Sq -0.0606
 Coeff Var 
56.65658    
Parameter Estimates
Variable
Label
DF Parameter
Estimate
Standard
Error
t Value Pr > |t|
95%
Confidence
Limits
 Intercept Intercept
1
7.76166
2.29503
3.38
0.0045
2.83932 12.68400
 CrCL 
CrCL
1
0.00864
0.02286
0.38
0.7112 -0.04040
0.05768


11:14 Monday, February 12, 2018
27
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,S)-M18
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:14 Monday, February 12, 2018
27
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,S)-M18
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=14 Param=RkTmax
Output Statistics
Obs
Dependent
Variable
Predicted
Value
Std Error
Mean Predict
Residual Std Error
Residual
Student
Residual
-2-1 0 1 2
Cook's
D
        1 
5.0000
9.1773
2.1591
-4.1773
4.305
-0.970  |     *|      | 
0.118
        2 
9.5000
9.0821
1.9552
0.4179
4.401
0.0949  |      |      | 
0.001
        3 
5.0000
8.6295
1.2518
-3.6295
4.650
-0.780  |     *|      | 
0.022
        4 
8.0000
8.8359
1.4966
-0.8359
4.577
-0.183  |      |      | 
0.002
        5 
9.5000
9.1024
1.9976
0.3976
4.382
0.0907  |      |      | 
0.001
        6 
5.0000
8.8000
1.4421
-3.8000
4.595
-0.827  |     *|      | 
0.034
        7 
13.0000
8.7672
1.3963
4.2328
4.609
0.918  |      |*     | 
0.039
        8 
11.5000
9.0348
1.8581
2.4652
4.443
0.555  |      |*     | 
0.027
        9 
11.5000
8.1080
1.5892
3.3920
4.546
0.746  |      |*     | 
0.034
       10 
5.0000
8.0166
1.7567
-3.0166
4.484
-0.673  |     *|      | 
0.035
       11 
14.5000
8.1390
1.5369
6.3610
4.564
1.394  |      |**    | 
0.110
       12 
14.5000
8.0227
1.7449
6.4773
4.489
1.443  |      |**    | 
0.157
       13 
1.5000
7.9941
1.8006
-6.4941
4.467
-1.454  |    **|      | 
0.172
       14 
1.5000
7.9368
1.9160
-6.4368
4.418
-1.457  |    **|      | 
0.200
       15 
5.0000
8.0237
1.7430
-3.0237
4.489
-0.674  |     *|      | 
0.034
       16 
16.0000
8.3299
1.2854
7.6701
4.641
1.653  |      |***   | 
0.105
 Sum of Residuals 
0
 Sum of Squared Residuals 
324.68828
 Predicted Residual SS (PRESS) 419.12128


11:14 Monday, February 12, 2018
28
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,S)-M18
(Healthy vs Severe)
ANOVA analysis
NON-PARAMETRIC TEST OF FIXED EFFECT for Tmax parameter
--------------------- SUMMARY REPORT ---------------------
The NPAR1WAY Procedure
11:14 Monday, February 12, 2018
28
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,S)-M18
(Healthy vs Severe)
ANOVA analysis
NON-PARAMETRIC TEST OF FIXED EFFECT for Tmax parameter
--------------------- SUMMARY REPORT ---------------------
The NPAR1WAY Procedure
Wilcoxon Scores (Rank Sums) for Variable Value
Classified by Variable Group
Group
N
Sum of
Scores
Expected
Under H0
Std Dev
Under H0
Mean
Score
 1 
8
66.50
68.0 9.352362 8.31250
 2 
8
69.50
68.0 9.352362 8.68750
Average scores were used for ties.
Wilcoxon Two-Sample Test
 Statistic 
66.5000
   
 Normal Approximation 
 Z 
-0.1069
 One-Sided Pr <  Z 
0.4574
 Two-Sided Pr > |Z| 
0.9148
   
 t Approximation 
 One-Sided Pr <  Z 
0.4581
 Two-Sided Pr > |Z| 
0.9163
Z includes a continuity correction of 0.5.
Kruskal-Wallis Test
 Chi-Square 
0.0257
 DF 
1
 Pr > Chi-Square 
0.8726
Hodges-Lehmann Estimation
Location Shift (1 - 2)    0.0000
Type
90%
Confidence
Limits
Interval
Midpoint
Asymptotic
Standard Error
 Asymptotic (Moses) -6.0000 2.0000
-2.0000
2.4318
 Exact 
-6.0000 2.0000
-2.0000


10:04 Monday, January 22, 2018
1
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,S)-M18 - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
RAW DATA
--------------------- SUMMARY REPORT ---------------------
10:04 Monday, January 22, 2018
1
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,S)-M18 - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
RAW DATA
--------------------- SUMMARY REPORT ---------------------
Renal Function Group=Normal
Obs Subject
Cmax
Tmax
AUCT
Thalf
Ae
AUCinf
Res_Area Lambda_z lnCmax
lnAUCT
 1 101
11.60000 4.00000 251.07875 11.49043 0.29028 291.46523 13.85636
0.06032 2.45101 5.52577
 2 102
11.60000 6.00000 237.11000
9.64792 0.36323 262.55454
9.69115
0.07184 2.45101 5.46852
 3 103
30.50000 4.00000 410.77500
6.13046 0.68963 420.79761
2.38181
0.11307 3.41773 6.01805
 4 104
17.70000 4.05000 250.40233
6.75169 0.35708 284.88339 12.10357
0.10266 2.87356 5.52307
 5 105
10.20000 6.00000 140.57375
8.09317 0.17223 165.52203 15.07248
0.08565 2.32239 4.94573
 6 106
26.20000 4.00000 294.73500
6.55312 0.49921 327.35368
9.96435
0.10577 3.26576 5.68608
 7 107
16.30000 8.03333 262.55675 10.35958 0.35874 290.19352
9.52357
0.06691 2.79117 5.57047
 8 108
15.70000 8.00000 298.52700
7.04445 0.35671 315.40243
5.35045
0.09840 2.75366 5.69886
Obs lnAUCinf
lnAe
lnLambda_z RkTmax
eGFR
CrCL
 1 
5.67492 -1.23692
-2.80803
5.0 115.00000 163.85000
 2 
5.57046 -1.01271
-2.63325
9.5 102.00000 152.84000
 3 
6.04215 -0.37160
-2.17978
5.0
94.00000 100.45000
 4 
5.65208 -1.02980
-2.27631
8.0 109.00000 124.34000
 5 
5.10910 -1.75895
-2.45753
9.5 102.00000 155.18000
 6 
5.79104 -0.69474
-2.24645
5.0 116.00000 120.18000
 7 
5.67055 -1.02517
-2.70442
13.0
98.00000 116.39000
 8 
5.75385 -1.03082
-2.31875
11.5 118.00000 147.36000


10:04 Monday, January 22, 2018
2
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,S)-M18 - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
RAW DATA
--------------------- SUMMARY REPORT ---------------------
10:04 Monday, January 22, 2018
2
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,S)-M18 - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
RAW DATA
--------------------- SUMMARY REPORT ---------------------
Renal Function Group=Severe
Obs Subject
Cmax
Tmax
AUCT
Thalf
Ae
AUCinf
Res_Area Lambda_z lnCmax
lnAUCT
 9 013-01
20.30000
4.00000 321.06250 14.67003 0.10180 393.73800 18.45783
0.04725 3.01062 5.77164
 10 013-02
21.40000
3.00000 392.19250 12.93609 0.08889 464.78850 15.61915
0.05358 3.06339 5.97175
 11 013-03
17.90000 12.00000 355.50900 15.98556 0.28436 464.47530 23.46008
0.04336 2.88480 5.87355
 12 013-04
8.61000 12.08333 211.49083 24.81341 0.05965 356.02825 40.59718
0.02793 2.15292 5.35418
 13 013-05
25.80000
3.00000 430.38083 17.84727 0.08234 559.95407 23.13998
0.03884 3.25037 6.06467
 14 013-06
8.63000
8.00000 226.50375 23.37308 0.05148 360.22751 37.12203
0.02966 2.15524 5.42276
 15 013-07
17.00000 12.00000 394.10558 13.57770 0.14649 489.91608 19.55651
0.05105 2.83321 5.97662
 16 013-08
21.10000
4.00000 312.17500 11.80038 0.10227 359.52637 13.17049
0.05874 3.04927 5.74356
Obs lnAUCinf
lnAe
lnLambda_z RkTmax
eGFR
CrCL
 9 
5.97569 -2.28477
-3.05232
5.0 23.00000 29.51000
 10 
6.14158 -2.42039
-2.92653
1.5 27.00000 26.90000
 11 
6.14091 -1.25750
-3.13820
14.5 26.00000 43.68000
 12 
5.87501 -2.81924
-3.57790
16.0 28.00000 65.77000
 13 
6.32785 -2.49689
-3.24836
1.5 16.00000 20.27000
 14 
5.88674 -2.96660
-3.51810
11.5 26.00000 40.09000
 15 
6.19423 -1.92077
-2.97494
14.5 19.00000 30.22000
 16 
5.88479 -2.28014
-2.83464
5.0 21.00000 30.33000


10:04 Monday, January 22, 2018
3
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,S)-M18 - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
DESCRIPTIVE RESULTS (OVERALL)
--------------------- SUMMARY REPORT ---------------------
10:04 Monday, January 22, 2018
3
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,S)-M18 - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
DESCRIPTIVE RESULTS (OVERALL)
--------------------- SUMMARY REPORT ---------------------
Parameter
Renal
Function
Group
n
Min
Mean
Geometric
Mean
Median
Max
Standard
Deviation
Coefficient
of
Variation
Cmax
Normal
8
10.20000
17.47500
16.29379
16.00000
30.50000
7.29300
41.7339
Cmax
Severe
8
8.61000
17.59250
16.44432
19.10000
25.80000
6.12898
34.8386
Tmax
Normal
8
4.00000
5.51042
5.27522
5.02500
8.03333
1.77359
32.1862
Tmax
Severe
8
3.00000
7.26042
6.13409
6.00000
12.08333
4.24765
58.5042
AUCT
Normal
8 140.57375 268.21982 258.41524 256.81775 410.77500
75.44937
28.1297
AUCT
Severe
8 211.49083 330.42750 321.28929 338.28575 430.38083
79.15310
23.9548
Thalf
Normal
8
6.13046
8.25885
8.05710
7.56881
11.49043
1.99997
24.2160
Thalf
Severe
8
11.80038
16.87544
16.31952
15.32780
24.81341
4.84002
28.6809
Ae
Normal
8
0.17223
0.38589
0.36056
0.35791
0.68963
0.15252
39.5232
Ae
Severe
8
0.05148
0.11466
0.09968
0.09534
0.28436
0.07451
64.9800
AUCinf
Normal
8 165.52203 294.77155 286.58045 290.82938 420.79761
70.95555
24.0714
AUCinf
Severe
8 356.02825 431.08176 425.53613 429.10665 559.95407
75.10840
17.4232
Res_Area
Normal
8
2.38181
9.74297
8.58932
9.82775
15.07248
4.21692
43.2817
Res_Area
Severe
8
13.17049
23.89041
22.28147
21.34824
40.59718
9.90358
41.4542
Lambda_z
Normal
8
0.06032
0.08808
0.08603
0.09202
0.11307
0.01980
22.4815
Lambda_z
Severe
8
0.02793
0.04380
0.04247
0.04531
0.05874
0.01108
25.3046
lnCmax
Normal
8
2.32239
2.79078
2.77241
3.41773
0.39228
14.0563
lnCmax
Severe
8
2.15292
2.79998
2.94771
3.25037
0.41772
14.9186
lnAUCT
Normal
8
4.94573
5.55457
5.54812
6.01805
0.30073
5.4142
lnAUCT
Severe
8
5.35418
5.77234
5.82259
6.06467
0.26052
4.5132
lnAUCinf
Normal
8
5.10910
5.65802
5.67273
6.04215
0.26292
4.6469
lnAUCinf
Severe
8
5.87501
6.05335
6.05830
6.32785
0.17099
2.8247
lnAe
Normal
8
-1.75895
-1.02009
-1.02748
-0.37160
0.39993
-39.2056
lnAe
Severe
8
-2.96660
-2.30579
-2.35258
-1.25750
0.53428
-23.1713
lnLambda_z Normal
8
-2.80803
-2.45307
-2.38814
-2.17978
0.23553
-9.6015
lnLambda_z Severe
8
-3.57790
-3.15887
-3.09526
-2.83464
0.27186
-8.6062
RkTmax
Normal
8
5.00000
8.31250
7.78504
8.75000
13.00000
3.11606
37.4864
RkTmax
Severe
8
1.50000
8.68750
6.19740
8.25000
16.00000
6.08826
70.0807


10:04 Monday, January 22, 2018
4
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,S)-M18 - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
--------------------- SUMMARY REPORT ---------------------
The Mixed Procedure
10:04 Monday, January 22, 2018
4
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,S)-M18 - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
--------------------- SUMMARY REPORT ---------------------
The Mixed Procedure
Order=1 Param=Cmax
Model Information
 Data Set 
WORK.KINDATA
 Dependent Variable 
Value
 Covariance Structure 
Variance Components
 Group Effect 
FunctionGroup
 Estimation Method 
REML
 Residual Variance Method 
None
 Fixed Effects SE Method 
Model-Based
 Degrees of Freedom Method Between-Within
Class Level Information
Class
Levels
Values
 FunctionGroup 
2 Severe Normal
Dimensions
 Covariance Parameters 
2
 Columns in X 
3
 Columns in Z 
0
 Subjects 
16
 Max Obs per Subject 
1
Number of Observations
 Number of Observations Read 
16
 Number of Observations Used 
16
 Number of Observations Not Used 
0
Iteration History
Iteration Evaluations -2 Res Log Like Criterion
      0 
1
97.29896280
      1 
1
97.08836376 0.00000000
Convergence criteria met.
Covariance Parameter Estimates
Cov Parm
Group
Estimate
 Residual FunctionGroup Severe
37.5644
 Residual FunctionGroup Normal
53.1879
Fit Statistics
 -2 Res Log Likelihood 
97.1
 AIC (Smaller is Better) 
101.1
 AICC (Smaller is Better) 102.2
 BIC (Smaller is Better) 
102.6
Null Model Likelihood
Ratio Test
DF
Chi-Square Pr > ChiSq
1
0.21
0.6463
Type 3 Tests of Fixed Effects
Effect
Num
DF
Den
DF
F Value Pr > F
 FunctionGroup 
1
14
0.00 0.9727
Least Squares Means
Effect
Renal
Function
Group
Estimate Standard
Error
DF t Value Pr > |t| Alpha
Lower
Upper
 FunctionGroup Severe
17.5925
2.1669 14
8.12
<.0001
0.1 13.7759 21.4091
 FunctionGroup Normal
17.4750
2.5785 14
6.78
<.0001
0.1 12.9335 22.0165
Differences of Least Squares Means
Effect
Renal
Function
Group
Renal
Function
Group
Estimate Standard
Error
DF t Value Pr > |t| Alpha
Lower
Upper
 FunctionGroup Severe
Normal
0.1175
3.3681 14
0.03
0.9727
0.1 -5.8148 6.0498


10:04 Monday, January 22, 2018
5
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,S)-M18 - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
--------------------- SUMMARY REPORT ---------------------
The Mixed Procedure
10:04 Monday, January 22, 2018
5
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,S)-M18 - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
--------------------- SUMMARY REPORT ---------------------
The Mixed Procedure
Order=3 Param=AUCT
Model Information
 Data Set 
WORK.KINDATA
 Dependent Variable 
Value
 Covariance Structure 
Variance Components
 Group Effect 
FunctionGroup
 Estimation Method 
REML
 Residual Variance Method 
None
 Fixed Effects SE Method 
Model-Based
 Degrees of Freedom Method Between-Within
Class Level Information
Class
Levels
Values
 FunctionGroup 
2 Severe Normal
Dimensions
 Covariance Parameters 
2
 Columns in X 
3
 Columns in Z 
0
 Subjects 
16
 Max Obs per Subject 
1
Number of Observations
 Number of Observations Read 
16
 Number of Observations Used 
16
 Number of Observations Not Used 
0
Iteration History
Iteration Evaluations -2 Res Log Like Criterion
      0 
1
165.63307285
      1 
1
165.61700324 0.00000000
Convergence criteria met.
Covariance Parameter Estimates
Cov Parm
Group
Estimate
 Residual FunctionGroup Severe
6265.21
 Residual FunctionGroup Normal
5692.61
Fit Statistics
 -2 Res Log Likelihood 
165.6
 AIC (Smaller is Better) 
169.6
 AICC (Smaller is Better) 170.7
 BIC (Smaller is Better) 
171.2
Null Model Likelihood
Ratio Test
DF
Chi-Square Pr > ChiSq
1
0.02
0.8991
Type 3 Tests of Fixed Effects
Effect
Num
DF
Den
DF
F Value Pr > F
 FunctionGroup 
1
14
2.59 0.1299
Least Squares Means
Effect
Renal
Function
Group
Estimate Standard
Error
DF t Value Pr > |t| Alpha
Lower
Upper
 FunctionGroup Severe
330.43
27.9848 14
11.81
<.0001
0.1 281.14 379.72
 FunctionGroup Normal
268.22
26.6754 14
10.05
<.0001
0.1 221.24 315.20
Differences of Least Squares Means
Effect
Renal
Function
Group
Renal
Function
Group
Estimate Standard
Error
DF t Value Pr > |t| Alpha
Lower
Upper
 FunctionGroup Severe
Normal
62.2077
38.6617 14
1.61
0.1299
0.1 -5.8876 130.30


10:04 Monday, January 22, 2018
6
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,S)-M18 - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
--------------------- SUMMARY REPORT ---------------------
The Mixed Procedure
10:04 Monday, January 22, 2018
6
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,S)-M18 - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
--------------------- SUMMARY REPORT ---------------------
The Mixed Procedure
Order=6 Param=AUCinf
Model Information
 Data Set 
WORK.KINDATA
 Dependent Variable 
Value
 Covariance Structure 
Variance Components
 Group Effect 
FunctionGroup
 Estimation Method 
REML
 Residual Variance Method 
None
 Fixed Effects SE Method 
Model-Based
 Degrees of Freedom Method Between-Within
Class Level Information
Class
Levels
Values
 FunctionGroup 
2 Severe Normal
Dimensions
 Covariance Parameters 
2
 Columns in X 
3
 Columns in Z 
0
 Subjects 
16
 Max Obs per Subject 
1
Number of Observations
 Number of Observations Read 
16
 Number of Observations Used 
16
 Number of Observations Not Used 
0
Iteration History
Iteration Evaluations -2 Res Log Like Criterion
      0 
1
164.04560222
      1 
1
164.02296805 0.00000000
Convergence criteria met.
Covariance Parameter Estimates
Cov Parm
Group
Estimate
 Residual FunctionGroup Severe
5641.27
 Residual FunctionGroup Normal
5034.69
Fit Statistics
 -2 Res Log Likelihood 
164.0
 AIC (Smaller is Better) 
168.0
 AICC (Smaller is Better) 169.1
 BIC (Smaller is Better) 
169.6
Null Model Likelihood
Ratio Test
DF
Chi-Square Pr > ChiSq
1
0.02
0.8804
Type 3 Tests of Fixed Effects
Effect
Num
DF
Den
DF
F Value Pr > F
 FunctionGroup 
1
14
13.92 0.0022
Least Squares Means
Effect
Renal
Function
Group
Estimate Standard
Error
DF t Value Pr > |t| Alpha
Lower
Upper
 FunctionGroup Severe
431.08
26.5548 14
16.23
<.0001
0.1 384.31 477.85
 FunctionGroup Normal
294.77
25.0866 14
11.75
<.0001
0.1 250.59 338.96
Differences of Least Squares Means
Effect
Renal
Function
Group
Renal
Function
Group
Estimate Standard
Error
DF t Value Pr > |t| Alpha
Lower
Upper
 FunctionGroup Severe
Normal
136.31
36.5307 14
3.73
0.0022
0.1 71.9682 200.65


10:04 Monday, January 22, 2018
7
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,S)-M18 - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
--------------------- SUMMARY REPORT ---------------------
The Mixed Procedure
10:04 Monday, January 22, 2018
7
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,S)-M18 - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
--------------------- SUMMARY REPORT ---------------------
The Mixed Procedure
Order=9 Param=lnCmax
Model Information
 Data Set 
WORK.KINDATA
 Dependent Variable 
Value
 Covariance Structure 
Variance Components
 Group Effect 
FunctionGroup
 Estimation Method 
REML
 Residual Variance Method 
None
 Fixed Effects SE Method 
Model-Based
 Degrees of Freedom Method Between-Within
Class Level Information
Class
Levels
Values
 FunctionGroup 
2 Severe Normal
Dimensions
 Covariance Parameters 
2
 Columns in X 
3
 Columns in Z 
0
 Subjects 
16
 Max Obs per Subject 
1
Number of Observations
 Number of Observations Read 
16
 Number of Observations Used 
16
 Number of Observations Not Used 
0
Iteration History
Iteration Evaluations -2 Res Log Like Criterion
      0 
1
18.59459448
      1 
1
18.56697737 0.00000000
Convergence criteria met.
Covariance Parameter Estimates
Cov Parm
Group
Estimate
 Residual FunctionGroup Severe
0.1745
 Residual FunctionGroup Normal
0.1539
Fit Statistics
 -2 Res Log Likelihood 
18.6
 AIC (Smaller is Better) 
22.6
 AICC (Smaller is Better) 
23.7
 BIC (Smaller is Better) 
24.1
Null Model Likelihood
Ratio Test
DF
Chi-Square Pr > ChiSq
1
0.03
0.8680
Type 3 Tests of Fixed Effects
Effect
Num
DF
Den
DF
F Value Pr > F
 FunctionGroup 
1
14
0.00 0.9644
Least Squares Means
Effect
Renal
Function
Group
Estimate Standard
Error
DF t Value Pr > |t| Alpha
Lower
Upper
 FunctionGroup Severe
2.8000
0.1477 14
18.96
<.0001
0.1 2.5399 3.0601
 FunctionGroup Normal
2.7908
0.1387 14
20.12
<.0001
0.1 2.5465 3.0351
Differences of Least Squares Means
Effect
Renal
Function
Group
Renal
Function
Group
Estimate Standard
Error
DF t Value Pr > |t| Alpha
Lower
Upper
 FunctionGroup Severe
Normal
0.009196
0.2026 14
0.05
0.9644
0.1 -0.3476 0.3660


10:04 Monday, January 22, 2018
8
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,S)-M18 - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
--------------------- SUMMARY REPORT ---------------------
The Mixed Procedure
10:04 Monday, January 22, 2018
8
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,S)-M18 - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
--------------------- SUMMARY REPORT ---------------------
The Mixed Procedure
Order=10 Param=lnAUCT
Model Information
 Data Set 
WORK.KINDATA
 Dependent Variable 
Value
 Covariance Structure 
Variance Components
 Group Effect 
FunctionGroup
 Estimation Method 
REML
 Residual Variance Method 
None
 Fixed Effects SE Method 
Model-Based
 Degrees of Freedom Method Between-Within
Class Level Information
Class
Levels
Values
 FunctionGroup 
2 Severe Normal
Dimensions
 Covariance Parameters 
2
 Columns in X 
3
 Columns in Z 
0
 Subjects 
16
 Max Obs per Subject 
1
Number of Observations
 Number of Observations Read 
16
 Number of Observations Used 
16
 Number of Observations Not Used 
0
Iteration History
Iteration Evaluations -2 Res Log Like Criterion
      0 
1
8.38031706
      1 
1
8.23655439 0.00000000
Convergence criteria met.
Covariance Parameter Estimates
Cov Parm
Group
Estimate
 Residual FunctionGroup Severe
0.06787
 Residual FunctionGroup Normal
0.09044
Fit Statistics
 -2 Res Log Likelihood 
8.2
 AIC (Smaller is Better) 
12.2
 AICC (Smaller is Better) 
13.3
 BIC (Smaller is Better) 
13.8
Null Model Likelihood
Ratio Test
DF
Chi-Square Pr > ChiSq
1
0.14
0.7046
Type 3 Tests of Fixed Effects
Effect
Num
DF
Den
DF
F Value Pr > F
 FunctionGroup 
1
14
2.40 0.1439
Least Squares Means
Effect
Renal
Function
Group
Estimate Standard
Error
DF t Value Pr > |t| Alpha
Lower
Upper
 FunctionGroup Severe
5.7723
0.09211 14
62.67
<.0001
0.1 5.6101 5.9346
 FunctionGroup Normal
5.5546
0.1063 14
52.24
<.0001
0.1 5.3673 5.7418
Differences of Least Squares Means
Effect
Renal
Function
Group
Renal
Function
Group
Estimate Standard
Error
DF t Value Pr > |t| Alpha
Lower
Upper
 FunctionGroup Severe
Normal
0.2178
0.1407 14
1.55
0.1439
0.1 -0.02999 0.4655


10:04 Monday, January 22, 2018
9
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,S)-M18 - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
--------------------- SUMMARY REPORT ---------------------
The Mixed Procedure
10:04 Monday, January 22, 2018
9
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,S)-M18 - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
--------------------- SUMMARY REPORT ---------------------
The Mixed Procedure
Order=11 Param=lnAUCinf
Model Information
 Data Set 
WORK.KINDATA
 Dependent Variable 
Value
 Covariance Structure 
Variance Components
 Group Effect 
FunctionGroup
 Estimation Method 
REML
 Residual Variance Method 
None
 Fixed Effects SE Method 
Model-Based
 Degrees of Freedom Method Between-Within
Class Level Information
Class
Levels
Values
 FunctionGroup 
2 Severe Normal
Dimensions
 Covariance Parameters 
2
 Columns in X 
3
 Columns in Z 
0
 Subjects 
16
 Max Obs per Subject 
1
Number of Observations
 Number of Observations Read 
16
 Number of Observations Used 
16
 Number of Observations Not Used 
0
Iteration History
Iteration Evaluations -2 Res Log Like Criterion
      0 
1
1.71804990
      1 
1
0.46038460 0.00000000
Convergence criteria met.
Covariance Parameter Estimates
Cov Parm
Group
Estimate
 Residual FunctionGroup Severe
0.02924
 Residual FunctionGroup Normal
0.06913
Fit Statistics
 -2 Res Log Likelihood 
0.5
 AIC (Smaller is Better) 
4.5
 AICC (Smaller is Better) 
5.6
 BIC (Smaller is Better) 
6.0
Null Model Likelihood
Ratio Test
DF
Chi-Square Pr > ChiSq
1
1.26
0.2621
Type 3 Tests of Fixed Effects
Effect
Num
DF
Den
DF
F Value Pr > F
 FunctionGroup 
1
14
12.71 0.0031
Least Squares Means
Effect
Renal
Function
Group
Estimate Standard
Error
DF t Value Pr > |t| Alpha
Lower
Upper
 FunctionGroup Severe
6.0533
0.06045 14
100.13
<.0001
0.1 5.9469 6.1598
 FunctionGroup Normal
5.6580
0.09296 14
60.87
<.0001
0.1 5.4943 5.8217
Differences of Least Squares Means
Effect
Renal
Function
Group
Renal
Function
Group
Estimate Standard
Error
DF t Value Pr > |t| Alpha
Lower
Upper
 FunctionGroup Severe
Normal
0.3953
0.1109 14
3.57
0.0031
0.1 0.2000 0.5906


10:04 Monday, January 22, 2018
10
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,S)-M18 - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
--------------------- SUMMARY REPORT ---------------------
The Mixed Procedure
10:04 Monday, January 22, 2018
10
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,S)-M18 - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
--------------------- SUMMARY REPORT ---------------------
The Mixed Procedure
Order=14 Param=RkTmax
Model Information
 Data Set 
WORK.KINDATA
 Dependent Variable 
Value
 Covariance Structure 
Variance Components
 Group Effect 
FunctionGroup
 Estimation Method 
REML
 Residual Variance Method 
None
 Fixed Effects SE Method 
Model-Based
 Degrees of Freedom Method Between-Within
Class Level Information
Class
Levels
Values
 FunctionGroup 
2 Severe Normal
Dimensions
 Covariance Parameters 
2
 Columns in X 
3
 Columns in Z 
0
 Subjects 
16
 Max Obs per Subject 
1
Number of Observations
 Number of Observations Read 
16
 Number of Observations Used 
16
 Number of Observations Not Used 
0
Iteration History
Iteration Evaluations -2 Res Log Like Criterion
      0 
1
88.02052016
      1 
1
85.09021011 0.00000000
Convergence criteria met.
Covariance Parameter Estimates
Cov Parm
Group
Estimate
 Residual FunctionGroup Severe
37.0670
 Residual FunctionGroup Normal
9.7098
Fit Statistics
 -2 Res Log Likelihood 
85.1
 AIC (Smaller is Better) 
89.1
 AICC (Smaller is Better) 
90.2
 BIC (Smaller is Better) 
90.6
Null Model Likelihood
Ratio Test
DF
Chi-Square Pr > ChiSq
1
2.93
0.0869
Type 3 Tests of Fixed Effects
Effect
Num
DF
Den
DF
F Value Pr > F
 FunctionGroup 
1
14
0.02 0.8790
Least Squares Means
Effect
Renal
Function
Group
Estimate Standard
Error
DF t Value Pr > |t| Alpha
Lower
Upper
 FunctionGroup Severe
8.6875
2.1525 14
4.04
0.0012
0.1 4.8962 12.4788
 FunctionGroup Normal
8.3125
1.1017 14
7.55
<.0001
0.1 6.3721 10.2529
Differences of Least Squares Means
Effect
Renal
Function
Group
Renal
Function
Group
Estimate Standard
Error
DF t Value Pr > |t| Alpha
Lower
Upper
 FunctionGroup Severe
Normal
0.3750
2.4181 14
0.16
0.8790
0.1 -3.8840 4.6340


10:04 Monday, January 22, 2018
11
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,S)-M18 - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
Geometric LSmeans
--------------------- SUMMARY REPORT ---------------------
10:04 Monday, January 22, 2018
11
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,S)-M18 - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
Geometric LSmeans
--------------------- SUMMARY REPORT ---------------------
Obs Parameters Group GeoLSmeans
 1 lnCmax
Severe
16.4443
 2 lnCmax
Normal
16.2938
 3 lnAUCT
Severe
321.29
 4 lnAUCT
Normal
258.42
 5 lnAUCinf
Severe
425.54
 6 lnAUCinf
Normal
286.58


10:04 Monday, January 22, 2018
12
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,S)-M18 - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
RATIO ESTIMATE BASED ON ln-TRANSFORMED PARAMETERS
--------------------- SUMMARY REPORT ---------------------
10:04 Monday, January 22, 2018
12
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - (S,S)-M18 - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
RATIO ESTIMATE BASED ON ln-TRANSFORMED PARAMETERS
--------------------- SUMMARY REPORT ---------------------
Obs Parameters Group
vs
Group
Ratio
(%)
L90
U90
 1 lnCmax
Severe Normal 100.924
70.635 144.201
 2 lnAUCT
Severe Normal 124.331
97.045 159.288
 3 lnAUCinf
Severe Normal 148.487 122.144 180.513


Clinical Study Report  
Project No COL MIG-113/H8H-CD-LAHN 
 
16.1.9.6 Documentation of statistical analysis – SAS® output of M7 
 
Legend:  
AUCinf= AUC(0−∞) 
AUCT=AUC(0-tlast) 
Vz_F= VZ/F 
CL_F= CL/F 
LambdaZ = λZ 
lCmax= ln(Cmax) 
lAUCT= ln(AUC(0-tlast)) 
lAUCinf= ln(AUC(0−∞)) 
lCLF= ln(CL/F) 
lLambdaZ = ln(λZ) 
lVz_F= ln(VZ/F) 
RkTmax= Rank of Tmax 


11:29 Monday, February 12, 2018
1
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M7
(Healthy vs Severe)
ANOVA analysis
RAW DATA
--------------------- SUMMARY REPORT ---------------------
11:29 Monday, February 12, 2018
1
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M7
(Healthy vs Severe)
ANOVA analysis
RAW DATA
--------------------- SUMMARY REPORT ---------------------
Renal Function Group=Normal
Obs Subject
Cmax
Tmax
AUCT
Thalf
Ae
AUCinf
Res_Area Lambda_z lnCmax
lnAUCT
 1 101
42.00000 2.00000 388.30000 6.86451 0.00079 399.05876
2.69603
0.10098 3.73767 5.96178
 2 102
63.80000 2.50000 665.35750 6.44652 0.00198 681.17001
2.32138
0.10752 4.15575 6.50032
 3 103
101.00000 1.25000 526.88250 3.01629 0.00249 541.63949
2.72450
0.22980 4.61512 6.26698
 4 104
99.80000 2.00000 707.53067 4.37683 0.00249 725.99535
2.54336
0.15837 4.60317 6.56178
 5 105
59.20000 1.00000 439.38500 4.65142
453.00695
3.00701
0.14902 4.08092 6.08538
 6 106
71.60000 2.00000 440.10750 3.77330 0.00149 446.82229
1.50279
0.18370 4.27110 6.08702
 7 107
72.30000 3.00000 767.57700 5.65628 0.00248 779.01561
1.46834
0.12254 4.28082 6.64324
 8 108
60.80000 2.50000 581.04250 6.13125 0.00339 591.19310
1.71697
0.11305 4.10759 6.36482
Obs lnAUCinf
lnAe
lnLambda_z RkTmax
eGFR
CrLR
 1 
5.98911 -7.14378
-2.29288
8.5 115.00000 163.85000
 2 
6.52381 -6.22294
-2.23005
12.5 102.00000 152.84000
 3 
6.29460 -5.99463
-1.47054
3.0
94.00000 100.45000
 4 
6.58754 -5.99405
-1.84284
8.5 109.00000 124.34000
 5 
6.11591
-1.90368
1.5 102.00000 155.18000
 6 
6.10216 -6.50710
-1.69446
8.5 116.00000 120.18000
 7 
6.65803 -5.99982
-2.09928
15.0
98.00000 116.39000
 8 
6.38214 -5.68805
-2.17991
12.5 118.00000 147.36000


11:29 Monday, February 12, 2018
2
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M7
(Healthy vs Severe)
ANOVA analysis
RAW DATA
--------------------- SUMMARY REPORT ---------------------
11:29 Monday, February 12, 2018
2
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M7
(Healthy vs Severe)
ANOVA analysis
RAW DATA
--------------------- SUMMARY REPORT ---------------------
Renal Function Group=Severe
Obs Subject
Cmax
Tmax
AUCT
Thalf
Ae
AUCinf
Res_Area Lambda_z lnCmax
lnAUCT
 9 201
36.10000 1.00000
480.53000
9.70927 0.00136
517.98321
7.23058
0.07139 3.58629 6.17489
 10 202
80.40000 2.00000
581.41500
4.55733 0.00040
599.24800
2.97590
0.15209 4.38701 6.36546
 11 203
97.10000 4.00000 1312.96000
9.78691 0.00635 1423.69135
7.77776
0.07082 4.57574 7.18004
 12 204
70.20000 2.00000
595.48083
6.36062 0.00531
604.46565
1.48641
0.10897 4.25135 6.38937
 13 205
247.00000 1.50000 3662.33500 10.49066 0.00220 4049.76869
9.56681
0.06607 5.50939 8.20586
 14 206
157.00000 1.86667 1449.96833 11.33526 0.00541 1569.00249
7.58661
0.06115 5.05625 7.27930
 15 207
124.00000 2.00000
826.49500
9.67678 0.00194
863.75748
4.31400
0.07163 4.82028 6.71719
 16 208
30.30000 2.56667
373.34958
7.81383 0.00127
390.93106
4.49734
0.08871 3.41115 5.92252
Obs lnAUCinf
lnAe
lnLambda_z RkTmax
eGFR
CrLR
 9 
6.24994 -6.60174
-2.63959
1.5 26.00000 40.09000
 10 
6.39568 -7.83410
-1.88325
8.5 23.00000 29.51000
 11 
7.26101 -5.05902
-2.64756
16.0 26.00000 43.68000
 12 
6.40434 -5.23737
-2.21664
8.5 19.00000 30.22000
 13 
8.30642 -6.11803
-2.71700
4.0 27.00000 26.90000
 14 
7.35820 -5.21913
-2.79443
5.0 16.00000 20.27000
 15 
6.76129 -6.24641
-2.63624
8.5 21.00000 30.33000
 16 
5.96853 -6.66858
-2.42241
14.0 28.00000 65.77000


11:29 Monday, February 12, 2018
3
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M7
(Healthy vs Severe)
ANOVA analysis
DESCRIPTIVE RESULTS (OVERALL)
--------------------- SUMMARY REPORT ---------------------
11:29 Monday, February 12, 2018
3
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M7
(Healthy vs Severe)
ANOVA analysis
DESCRIPTIVE RESULTS (OVERALL)
--------------------- SUMMARY REPORT ---------------------
Parameter
Renal
Function
Group
n
Min
Mean
Geometric
Mean
Median
Max
Standard
Deviation
Coefficient
of
Variation
Cmax
Normal
8
42.00000
71.31250
68.82161
67.70000
101.00000
20.23727
28.3783
Cmax
Severe
8
30.30000
105.26250
85.59976
88.75000
247.00000
71.14809
67.5911
Tmax
Normal
8
1.00000
2.03125
1.92365
2.00000
3.00000
0.66059
32.5215
Tmax
Severe
8
1.00000
2.11667
1.97338
2.00000
4.00000
0.88479
41.8012
AUCT
Normal
8 388.30000
564.52283 549.44841 553.96250
767.57700
139.24936
24.6667
AUCT
Severe
8 373.34958 1160.31672 879.47766 710.98792 3662.33500 1083.27048
93.3599
Thalf
Normal
8
3.01629
5.11455
4.94162
5.15385
6.86451
1.36926
26.7718
Thalf
Severe
8
4.55733
8.71633
8.39912
9.69302
11.33526
2.29044
26.2775
Ae
Normal
7
0.00079
0.00216
0.00199
0.00248
0.00339
0.00083
38.6537
Ae
Severe
8
0.00040
0.00303
0.00219
0.00207
0.00635
0.00229
75.4936
AUCinf
Normal
8 399.05876
577.23770 562.09079 566.41629
779.01561
141.06547
24.4380
AUCinf
Severe
8 390.93106 1252.35599 932.78585 734.11156 4049.76869 1209.12103
96.5477
Res_Area
Normal
8
1.46834
2.24755
2.17132
2.43237
3.00701
0.60258
26.8105
Res_Area
Severe
8
1.48641
5.67943
4.93235
5.86396
9.56681
2.77000
48.7726
Lambda_z
Normal
8
0.10098
0.14562
0.14027
0.13578
0.22980
0.04432
30.4331
Lambda_z
Severe
8
0.06115
0.08636
0.08253
0.07151
0.15209
0.03063
35.4702
lnCmax
Normal
8
3.73767
4.23152
4.21342
4.61512
0.28709
6.7845
lnCmax
Severe
8
3.41115
4.44968
4.48138
5.50939
0.70826
15.9170
lnAUCT
Normal
8
5.96178
6.30891
6.31590
6.64324
0.24984
3.9601
lnAUCT
Severe
8
5.92252
6.77933
6.55328
8.20586
0.74376
10.9709
lnAUCinf
Normal
8
5.98911
6.33166
6.33837
6.65803
0.24767
3.9117
lnAUCinf
Severe
8
5.96853
6.83818
6.58282
8.30642
0.76505
11.1880
lnAe
Normal
7
-7.14378
-6.22148
-5.99982
-5.68805
0.47768
-7.6780
lnAe
Severe
8
-7.83410
-6.12305
-6.18222
-5.05902
0.94138
-15.3743
lnLambda_z Normal
8
-2.29288
-1.96421
-2.00148
-1.47054
0.28744
-14.6337
lnLambda_z Severe
8
-2.79443
-2.49464
-2.63792
-1.88325
0.30707
-12.3094
RkTmax
Normal
8
1.50000
8.75000
7.10269
8.50000
15.00000
4.67516
53.4304
RkTmax
Severe
8
1.50000
8.25000
6.71357
8.50000
16.00000
4.89168
59.2931


11:29 Monday, February 12, 2018
4
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M7
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:29 Monday, February 12, 2018
4
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M7
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=9 Param=lnCmax
 Number of Observations Read 16
 Number of Observations Used 16
Analysis of Variance
Source
DF Sum of
Squares
Mean
Square
F Value Pr > F
 Model 
1 0.27548 0.27548
0.96 0.3430
 Error 
14 4.00323 0.28595
 Corrected Total 15 4.27871
 Root MSE 
0.53474  R-Square 
0.0644
 Dependent Mean 
4.34060  Adj R-Sq -0.0024
 Coeff Var 
12.31946    
Parameter Estimates
Variable
Label
DF Parameter
Estimate
Standard
Error
t Value Pr > |t|
95%
Confidence
Limits
 Intercept Intercept
1
4.54238
0.24522
18.52
<.0001
4.01643 5.06833
 eGFR 
eGFR
1
-0.00310
0.00316
-0.98
0.3430 -0.00989 0.00368


11:29 Monday, February 12, 2018
5
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M7
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:29 Monday, February 12, 2018
5
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M7
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=9 Param=lnCmax
Output Statistics
Obs
Dependent
Variable
Predicted
Value
Std Error
Mean Predict
Residual Std Error
Residual
Student
Residual
-2-1 0 1 2
Cook's
D
        1 
3.7377
4.1854
0.2071
-0.4477
0.493
-0.908  |     *|      | 
0.073
        2 
4.1558
4.2257
0.1777
-0.0700
0.504
-0.139  |      |      | 
0.001
        3 
4.6151
4.2506
0.1621
0.3645
0.510
0.715  |      |*     | 
0.026
        4 
4.6032
4.2040
0.1930
0.3992
0.499
0.800  |      |*     | 
0.048
        5 
4.0809
4.2257
0.1777
-0.1448
0.504
-0.287  |      |      | 
0.005
        6 
4.2711
4.1823
0.2095
0.0888
0.492
0.181  |      |      | 
0.003
        7 
4.2808
4.2382
0.1696
0.0427
0.507
0.0841  |      |      | 
0.000
        8 
4.1076
4.1761
0.2144
-0.0685
0.490
-0.140  |      |      | 
0.002
        9 
3.5863
4.4617
0.1819
-0.8754
0.503
-1.741  |   ***|      | 
0.198
       10 
4.3870
4.4710
0.1885
-0.0840
0.500
-0.168  |      |      | 
0.002
       11 
4.5757
4.4617
0.1819
0.1141
0.503
0.227  |      |      | 
0.003
       12 
4.2513
4.4834
0.1976
-0.2321
0.497
-0.467  |      |      | 
0.017
       13 
5.5094
4.4586
0.1798
1.0508
0.504
2.087  |      |****  | 
0.277
       14 
5.0562
4.4927
0.2047
0.5635
0.494
1.141  |      |**    | 
0.112
       15 
4.8203
4.4772
0.1930
0.3431
0.499
0.688  |      |*     | 
0.035
       16 
3.4111
4.4555
0.1777
-1.0443
0.504
-2.071  |  ****|      | 
0.266
 Sum of Residuals 
0
 Sum of Squared Residuals 
4.00323
 Predicted Residual SS (PRESS) 5.15290


11:29 Monday, February 12, 2018
6
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M7
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:29 Monday, February 12, 2018
6
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M7
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=10 Param=lnAUCT
 Number of Observations Read 16
 Number of Observations Used 16
Analysis of Variance
Source
DF Sum of
Squares
Mean
Square
F Value Pr > F
 Model 
1 0.94179 0.94179
3.10 0.1001
 Error 
14 4.25252 0.30375
 Corrected Total 15 5.19431
 Root MSE 
0.55114  R-Square 0.1813
 Dependent Mean 6.54412  Adj R-Sq 0.1228
 Coeff Var 
8.42185    
Parameter Estimates
Variable
Label
DF Parameter
Estimate
Standard
Error
t Value Pr > |t|
95%
Confidence
Limits
 Intercept Intercept
1
6.91721
0.25274
27.37
<.0001
6.37513 7.45929
 eGFR 
eGFR
1
-0.00574
0.00326
-1.76
0.1001 -0.01273 0.00125


11:29 Monday, February 12, 2018
7
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M7
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:29 Monday, February 12, 2018
7
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M7
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=10 Param=lnAUCT
Output Statistics
Obs
Dependent
Variable
Predicted
Value
Std Error
Mean Predict
Residual Std Error
Residual
Student
Residual
-2-1 0 1 2
Cook's
D
        1 
5.9618
6.2571
0.2134
-0.2954
0.508
-0.581  |     *|      | 
0.030
        2 
6.5003
6.3317
0.1831
0.1686
0.520
0.324  |      |      | 
0.007
        3 
6.2670
6.3777
0.1671
-0.1107
0.525
-0.211  |      |      | 
0.002
        4 
6.5618
6.2916
0.1989
0.2702
0.514
0.526  |      |*     | 
0.021
        5 
6.0854
6.3317
0.1831
-0.2464
0.520
-0.474  |      |      | 
0.014
        6 
6.0870
6.2514
0.2159
-0.1644
0.507
-0.324  |      |      | 
0.010
        7 
6.6432
6.3547
0.1748
0.2885
0.523
0.552  |      |*     | 
0.017
        8 
6.3648
6.2399
0.2210
0.1249
0.505
0.247  |      |      | 
0.006
        9 
6.1749
6.7680
0.1875
-0.5931
0.518
-1.144  |    **|      | 
0.086
       10 
6.3655
6.7852
0.1942
-0.4197
0.516
-0.814  |     *|      | 
0.047
       11 
7.1800
6.7680
0.1875
0.4121
0.518
0.795  |      |*     | 
0.041
       12 
6.3894
6.8082
0.2036
-0.4188
0.512
-0.818  |     *|      | 
0.053
       13 
8.2059
6.7622
0.1853
1.4436
0.519
2.781  |      |***** | 
0.493
       14 
7.2793
6.8254
0.2109
0.4539
0.509
0.891  |      |*     | 
0.068
       15 
6.7172
6.7967
0.1989
-0.0795
0.514
-0.155  |      |      | 
0.002
       16 
5.9225
6.7565
0.1831
-0.8340
0.520
-1.604  |   ***|      | 
0.160
 Sum of Residuals 
0
 Sum of Squared Residuals 
4.25252
 Predicted Residual SS (PRESS) 5.45834


11:29 Monday, February 12, 2018
8
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M7
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:29 Monday, February 12, 2018
8
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M7
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=11 Param=lnAUCinf
 Number of Observations Read 16
 Number of Observations Used 16
Analysis of Variance
Source
DF Sum of
Squares
Mean
Square
F Value Pr > F
 Model 
1 1.08329 1.08329
3.39 0.0867
 Error 
14 4.46949 0.31925
 Corrected Total 15 5.55278
 Root MSE 
0.56502  R-Square 0.1951
 Dependent Mean 6.58492  Adj R-Sq 0.1376
 Coeff Var 
8.58054    
Parameter Estimates
Variable
Label
DF Parameter
Estimate
Standard
Error
t Value Pr > |t|
95%
Confidence
Limits
 Intercept Intercept
1
6.98506
0.25911
26.96
<.0001
6.42932 7.54079
 eGFR 
eGFR
1
-0.00616
0.00334
-1.84
0.0867 -0.01332 0.00101


11:29 Monday, February 12, 2018
9
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M7
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:29 Monday, February 12, 2018
9
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M7
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=11 Param=lnAUCinf
Output Statistics
Obs
Dependent
Variable
Predicted
Value
Std Error
Mean Predict
Residual Std Error
Residual
Student
Residual
-2-1 0 1 2
Cook's
D
        1 
5.9891
6.2771
0.2188
-0.2880
0.521
-0.553  |     *|      | 
0.027
        2 
6.5238
6.3571
0.1877
0.1667
0.533
0.313  |      |      | 
0.006
        3 
6.2946
6.4064
0.1713
-0.1118
0.538
-0.208  |      |      | 
0.002
        4 
6.5875
6.3141
0.2039
0.2735
0.527
0.519  |      |*     | 
0.020
        5 
6.1159
6.3571
0.1877
-0.2412
0.533
-0.453  |      |      | 
0.013
        6 
6.1022
6.2710
0.2214
-0.1688
0.520
-0.325  |      |      | 
0.010
        7 
6.6580
6.3818
0.1792
0.2763
0.536
0.516  |      |*     | 
0.015
        8 
6.3821
6.2587
0.2265
0.1235
0.518
0.239  |      |      | 
0.005
        9 
6.2499
6.8250
0.1922
-0.5751
0.531
-1.082  |    **|      | 
0.077
       10 
6.3957
6.8435
0.1991
-0.4478
0.529
-0.847  |     *|      | 
0.051
       11 
7.2610
6.8250
0.1922
0.4360
0.531
0.821  |      |*     | 
0.044
       12 
6.4043
6.8681
0.2088
-0.4637
0.525
-0.883  |     *|      | 
0.062
       13 
8.3064
6.8188
0.1899
1.4876
0.532
2.795  |      |***** | 
0.498
       14 
7.3582
6.8866
0.2163
0.4716
0.522
0.904  |      |*     | 
0.070
       15 
6.7613
6.8558
0.2039
-0.0945
0.527
-0.179  |      |      | 
0.002
       16 
5.9685
6.8127
0.1877
-0.8442
0.533
-1.584  |   ***|      | 
0.156
 Sum of Residuals 
0
 Sum of Squared Residuals 
4.46949
 Predicted Residual SS (PRESS) 5.73936


11:29 Monday, February 12, 2018
10
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M7
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:29 Monday, February 12, 2018
10
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M7
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=12 Param=lnAe
 Number of Observations Read 
16
 Number of Observations Used 
15
 Number of Observations with Missing Values 
1
Analysis of Variance
Source
DF Sum of
Squares
Mean
Square
F Value Pr > F
 Model 
1 0.09243 0.09243
0.16 0.6958
 Error 
13 7.51617 0.57817
 Corrected Total 14 7.60860
 Root MSE 
0.76037  R-Square 
0.0121
 Dependent Mean 
-6.16898  Adj R-Sq -0.0638
 Coeff Var 
-12.32574    
Parameter Estimates
Variable
Label
DF Parameter
Estimate
Standard
Error
t Value Pr > |t|
95%
Confidence
Limits
 Intercept Intercept
1
-6.05355
0.34913
-17.34
<.0001 -6.80780 -5.29930
 eGFR 
eGFR
1
-0.00185
0.00462
-0.40
0.6958 -0.01182
0.00813


11:29 Monday, February 12, 2018
11
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M7
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:29 Monday, February 12, 2018
11
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M7
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=12 Param=lnAe
Output Statistics
Obs
Dependent
Variable
Predicted
Value
Std Error
Mean Predict
Residual Std Error
Residual
Student
Residual
-2-1 0 1 2
Cook's
D
        1 
-7.1438
-6.2658
0.3118
-0.8779
0.694
-1.266  |    **|      | 
0.162
        2 
-6.2229
-6.2418
0.2679
0.0189
0.712
0.0266  |      |      | 
0.000
        3 
-5.9946
-6.2271
0.2442
0.2324
0.720
0.323  |      |      | 
0.006
        4 
-5.9941
-6.2548
0.2908
0.2607
0.703
0.371  |      |      | 
0.012
        5 
-6.2418
0.2679
                 
        6 
-6.5071
-6.2677
0.3154
-0.2394
0.692
-0.346  |      |      | 
0.012
        7 
-5.9998
-6.2345
0.2556
0.2346
0.716
0.328  |      |      | 
0.007
        8 
-5.6880
-6.2714
0.3227
0.5833
0.689
0.847  |      |*     | 
0.079
        9 
-6.6017
-6.1015
0.2588
-0.5002
0.715
-0.700  |     *|      | 
0.032
       10 
-7.8341
-6.0960
0.2681
-1.7381
0.712
-2.443  |  ****|      | 
0.423
       11 
-5.0590
-6.1015
0.2588
1.0425
0.715
1.458  |      |**    | 
0.139
       12 
-5.2374
-6.0886
0.2810
0.8512
0.707
1.205  |      |**    | 
0.115
       13 
-6.1180
-6.1034
0.2558
-0.0146
0.716
-0.0204  |      |      | 
0.000
       14 
-5.2191
-6.0831
0.2910
0.8640
0.702
1.230  |      |**    | 
0.130
       15 
-6.2464
-6.0923
0.2744
-0.1541
0.709
-0.217  |      |      | 
0.004
       16 
-6.6686
-6.1052
0.2529
-0.5633
0.717
-0.786  |     *|      | 
0.038
 Sum of Residuals 
0
 Sum of Squared Residuals 
7.51617
 Predicted Residual SS (PRESS) 10.01373


11:29 Monday, February 12, 2018
12
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M7
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:29 Monday, February 12, 2018
12
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M7
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=13 Param=lnLambda_z
 Number of Observations Read 16
 Number of Observations Used 16
Analysis of Variance
Source
DF Sum of
Squares
Mean
Square
F Value Pr > F
 Model 
1 1.01701 1.01701
10.57 0.0058
 Error 
14 1.34683 0.09620
 Corrected Total 15 2.36384
 Root MSE 
0.31016  R-Square 0.4302
 Dependent Mean 
-2.22942  Adj R-Sq 0.3895
 Coeff Var 
-13.91234    
Parameter Estimates
Variable
Label
DF Parameter
Estimate
Standard
Error
t Value Pr > |t|
95%
Confidence
Limits
 Intercept Intercept
1
-2.61713
0.14224
-18.40
<.0001 -2.92219 -2.31206
 eGFR 
eGFR
1
0.00596
0.00183
3.25
0.0058
0.00203
0.00990


11:29 Monday, February 12, 2018
13
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M7
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:29 Monday, February 12, 2018
13
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M7
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=13 Param=lnLambda_z
Output Statistics
Obs
Dependent
Variable
Predicted
Value
Std Error
Mean Predict
Residual Std Error
Residual
Student
Residual
-2-1 0 1 2
Cook's
D
        1 
-2.2929
-1.9312
0.1201
-0.3617
0.286
-1.265  |    **|      | 
0.141
        2 
-2.2301
-2.0087
0.1031
-0.2213
0.293
-0.757  |     *|      | 
0.036
        3 
-1.4705
-2.0564
0.0940
0.5859
0.296
1.982  |      |***   | 
0.199
        4 
-1.8428
-1.9670
0.1119
0.1241
0.289
0.429  |      |      | 
0.014
        5 
-1.9037
-2.0087
0.1031
0.1050
0.293
0.359  |      |      | 
0.008
        6 
-1.6945
-1.9252
0.1215
0.2308
0.285
0.809  |      |*     | 
0.059
        7 
-2.0993
-2.0326
0.0984
-0.0667
0.294
-0.227  |      |      | 
0.003
        8 
-2.1799
-1.9133
0.1244
-0.2666
0.284
-0.938  |     *|      | 
0.084
        9 
-2.6396
-2.4620
0.1055
-0.1775
0.292
-0.609  |     *|      | 
0.024
       10 
-1.8833
-2.4799
0.1093
0.5967
0.290
2.056  |      |****  | 
0.300
       11 
-2.6476
-2.4620
0.1055
-0.1855
0.292
-0.636  |     *|      | 
0.026
       12 
-2.2166
-2.5038
0.1146
0.2872
0.288
0.996  |      |*     | 
0.078
       13 
-2.7170
-2.4561
0.1043
-0.2609
0.292
-0.893  |     *|      | 
0.051
       14 
-2.7944
-2.5217
0.1187
-0.2727
0.287
-0.952  |     *|      | 
0.078
       15 
-2.6362
-2.4919
0.1119
-0.1444
0.289
-0.499  |      |      | 
0.019
       16 
-2.4224
-2.4501
0.1031
0.0277
0.293
0.0947  |      |      | 
0.001
 Sum of Residuals 
0
 Sum of Squared Residuals 
1.34683
 Predicted Residual SS (PRESS) 1.75057


11:29 Monday, February 12, 2018
14
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M7
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:29 Monday, February 12, 2018
14
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M7
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=14 Param=RkTmax
 Number of Observations Read 16
 Number of Observations Used 16
Analysis of Variance
Source
DF
Sum of
Squares
Mean
Square
F Value Pr > F
 Model 
1
2.65515
2.65515
0.12 0.7378
 Error 
14 318.84485 22.77463
 Corrected Total 15 321.50000
 Root MSE 
4.77228  R-Square 
0.0083
 Dependent Mean 
8.50000  Adj R-Sq -0.0626
 Coeff Var 
56.14444    
Parameter Estimates
Variable
Label
DF Parameter
Estimate
Standard
Error
t Value Pr > |t|
95%
Confidence
Limits
 Intercept Intercept
1
7.87356
2.18849
3.60
0.0029
3.17971 12.56741
 eGFR 
eGFR
1
0.00964
0.02823
0.34
0.7378 -0.05090
0.07018


11:29 Monday, February 12, 2018
15
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M7
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:29 Monday, February 12, 2018
15
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M7
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=14 Param=RkTmax
Output Statistics
Obs
Dependent
Variable
Predicted
Value
Std Error
Mean Predict
Residual Std Error
Residual
Student
Residual
-2-1 0 1 2
Cook's
D
        1 
8.5000
8.9819
1.8480
-0.4819
4.400
-0.110  |      |      | 
0.001
        2 
12.5000
8.8566
1.5856
3.6434
4.501
0.809  |      |*     | 
0.041
        3 
3.0000
8.7795
1.4469
-5.7795
4.548
-1.271  |    **|      | 
0.082
        4 
8.5000
8.9241
1.7222
-0.4241
4.451
-0.0953  |      |      | 
0.001
        5 
1.5000
8.8566
1.5856
-7.3566
4.501
-1.634  |   ***|      | 
0.166
        6 
8.5000
8.9915
1.8697
-0.4915
4.391
-0.112  |      |      | 
0.001
        7 
15.0000
8.8180
1.5136
6.1820
4.526
1.366  |      |**    | 
0.104
        8 
12.5000
9.0108
1.9135
3.4892
4.372
0.798  |      |*     | 
0.061
        9 
1.5000
8.1241
1.6233
-6.6241
4.488
-1.476  |    **|      | 
0.143
       10 
8.5000
8.0952
1.6819
0.4048
4.466
0.0906  |      |      | 
0.001
       11 
16.0000
8.1241
1.6233
7.8759
4.488
1.755  |      |***   | 
0.202
       12 
8.5000
8.0567
1.7633
0.4433
4.435
0.1000  |      |      | 
0.001
       13 
4.0000
8.1338
1.6043
-4.1338
4.495
-0.920  |     *|      | 
0.054
       14 
5.0000
8.0278
1.8266
-3.0278
4.409
-0.687  |     *|      | 
0.040
       15 
8.5000
8.0759
1.7222
0.4241
4.451
0.0953  |      |      | 
0.001
       16 
14.0000
8.1434
1.5856
5.8566
4.501
1.301  |      |**    | 
0.105
 Sum of Residuals 
0
 Sum of Squared Residuals 
318.84485
 Predicted Residual SS (PRESS) 404.88659


11:29 Monday, February 12, 2018
16
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M7
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:29 Monday, February 12, 2018
16
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M7
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=9 Param=lnCmax
 Number of Observations Read 16
 Number of Observations Used 16
Analysis of Variance
Source
DF Sum of
Squares
Mean
Square
F Value Pr > F
 Model 
1 0.71970 0.71970
2.83 0.1146
 Error 
14 3.55901 0.25421
 Corrected Total 15 4.27871
 Root MSE 
0.50420  R-Square 0.1682
 Dependent Mean 
4.34060  Adj R-Sq 0.1088
 Coeff Var 
11.61584    
Parameter Estimates
Variable
Label
DF Parameter
Estimate
Standard
Error
t Value Pr > |t|
95%
Confidence
Limits
 Intercept Intercept
1
4.68479
0.24028
19.50
<.0001
4.16944 5.20015
 CrLR 
CrLR
1
-0.00403
0.00239
-1.68
0.1146 -0.00916 0.00111


11:29 Monday, February 12, 2018
17
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M7
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:29 Monday, February 12, 2018
17
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M7
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=9 Param=lnCmax
Output Statistics
Obs
Dependent
Variable
Predicted
Value
Std Error
Mean Predict
Residual Std Error
Residual
Student
Residual
-2-1 0 1 2
Cook's
D
        1 
3.7377
4.0249
0.2260
-0.2872
0.451
-0.637  |     *|      | 
0.051
        2 
4.1558
4.0692
0.2047
0.0865
0.461
0.188  |      |      | 
0.003
        3 
4.6151
4.2802
0.1311
0.3349
0.487
0.688  |      |*     | 
0.017
        4 
4.6032
4.1840
0.1567
0.4192
0.479
0.875  |      |*     | 
0.041
        5 
4.0809
4.0598
0.2091
0.0211
0.459
0.0460  |      |      | 
0.000
        6 
4.2711
4.2008
0.1510
0.0703
0.481
0.146  |      |      | 
0.001
        7 
4.2808
4.2160
0.1462
0.0648
0.483
0.134  |      |      | 
0.001
        8 
4.1076
4.0913
0.1945
0.0163
0.465
0.0350  |      |      | 
0.000
        9 
3.5863
4.5233
0.1664
-0.9370
0.476
-1.969  |   ***|      | 
0.237
       10 
4.3870
4.5659
0.1839
-0.1789
0.469
-0.381  |      |      | 
0.011
       11 
4.5757
4.5089
0.1609
0.0669
0.478
0.140  |      |      | 
0.001
       12 
4.2513
4.5631
0.1827
-0.3117
0.470
-0.663  |     *|      | 
0.033
       13 
5.5094
4.5765
0.1885
0.9329
0.468
1.995  |      |***   | 
0.323
       14 
5.0562
4.6032
0.2006
0.4531
0.463
0.979  |      |*     | 
0.090
       15 
4.8203
4.5626
0.1825
0.2576
0.470
0.548  |      |*     | 
0.023
       16 
3.4111
4.4199
0.1346
-1.0088
0.486
-2.076  |  ****|      | 
0.165
 Sum of Residuals 
0
 Sum of Squared Residuals 
3.55901
 Predicted Residual SS (PRESS) 4.51243


11:29 Monday, February 12, 2018
18
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M7
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:29 Monday, February 12, 2018
18
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M7
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=10 Param=lnAUCT
 Number of Observations Read 16
 Number of Observations Used 16
Analysis of Variance
Source
DF Sum of
Squares
Mean
Square
F Value Pr > F
 Model 
1 1.31743 1.31743
4.76 0.0467
 Error 
14 3.87688 0.27692
 Corrected Total 15 5.19431
 Root MSE 
0.52623  R-Square 0.2536
 Dependent Mean 6.54412  Adj R-Sq 0.2003
 Coeff Var 
8.04129    
Parameter Estimates
Variable
Label
DF Parameter
Estimate
Standard
Error
t Value Pr > |t|
95%
Confidence Limits
 Intercept Intercept
1
7.00981
0.25078
27.95
<.0001
6.47193
7.54768
 CrLR 
CrLR
1
-0.00545
0.00250
-2.18
0.0467 -0.01081 -0.00009085


11:29 Monday, February 12, 2018
19
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M7
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:29 Monday, February 12, 2018
19
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M7
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=10 Param=lnAUCT
Output Statistics
Obs
Dependent
Variable
Predicted
Value
Std Error
Mean Predict
Residual Std Error
Residual
Student
Residual
-2-1 0 1 2
Cook's
D
        1 
5.9618
6.1170
0.2359
-0.1552
0.470
-0.330  |      |      | 
0.014
        2 
6.5003
6.1770
0.2136
0.3234
0.481
0.672  |      |*     | 
0.045
        3 
6.2670
6.4624
0.1368
-0.1955
0.508
-0.385  |      |      | 
0.005
        4 
6.5618
6.3323
0.1635
0.2295
0.500
0.459  |      |      | 
0.011
        5 
6.0854
6.1642
0.2183
-0.0788
0.479
-0.165  |      |      | 
0.003
        6 
6.0870
6.3549
0.1576
-0.2679
0.502
-0.534  |     *|      | 
0.014
        7 
6.6432
6.3756
0.1526
0.2677
0.504
0.531  |      |*     | 
0.013
        8 
6.3648
6.2068
0.2030
0.1580
0.485
0.325  |      |      | 
0.009
        9 
6.1749
6.7913
0.1737
-0.6165
0.497
-1.241  |    **|      | 
0.094
       10 
6.3655
6.8490
0.1920
-0.4835
0.490
-0.987  |     *|      | 
0.075
       11 
7.1800
6.7718
0.1679
0.4083
0.499
0.819  |      |*     | 
0.038
       12 
6.3894
6.8451
0.1907
-0.4558
0.490
-0.929  |     *|      | 
0.065
       13 
8.2059
6.8632
0.1968
1.3426
0.488
2.751  |      |***** | 
0.615
       14 
7.2793
6.8994
0.2094
0.3799
0.483
0.787  |      |*     | 
0.058
       15 
6.7172
6.8445
0.1905
-0.1273
0.491
-0.260  |      |      | 
0.005
       16 
5.9225
6.6514
0.1405
-0.7289
0.507
-1.437  |    **|      | 
0.079
 Sum of Residuals 
0
 Sum of Squared Residuals 
3.87688
 Predicted Residual SS (PRESS) 5.06049


11:29 Monday, February 12, 2018
20
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M7
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:29 Monday, February 12, 2018
20
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M7
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=11 Param=lnAUCinf
 Number of Observations Read 16
 Number of Observations Used 16
Analysis of Variance
Source
DF Sum of
Squares
Mean
Square
F Value Pr > F
 Model 
1 1.47846 1.47846
5.08 0.0408
 Error 
14 4.07432 0.29102
 Corrected Total 15 5.55278
 Root MSE 
0.53947  R-Square 0.2663
 Dependent Mean 6.58492  Adj R-Sq 0.2138
 Coeff Var 
8.19243    
Parameter Estimates
Variable
Label
DF Parameter
Estimate
Standard
Error
t Value Pr > |t|
95%
Confidence Limits
 Intercept Intercept
1
7.07824
0.25709
27.53
<.0001
6.52685
7.62964
 CrLR 
CrLR
1
-0.00577
0.00256
-2.25
0.0408 -0.01127 -0.00027954


11:29 Monday, February 12, 2018
21
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M7
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:29 Monday, February 12, 2018
21
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M7
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=11 Param=lnAUCinf
Output Statistics
Obs
Dependent
Variable
Predicted
Value
Std Error
Mean Predict
Residual Std Error
Residual
Student
Residual
-2-1 0 1 2
Cook's
D
        1 
5.9891
6.1324
0.2419
-0.1433
0.482
-0.297  |      |      | 
0.011
        2 
6.5238
6.1960
0.2190
0.3278
0.493
0.665  |      |*     | 
0.044
        3 
6.2946
6.4984
0.1402
-0.2038
0.521
-0.391  |      |      | 
0.006
        4 
6.5875
6.3605
0.1676
0.2271
0.513
0.443  |      |      | 
0.010
        5 
6.1159
6.1825
0.2238
-0.0665
0.491
-0.136  |      |      | 
0.002
        6 
6.1022
6.3845
0.1615
-0.2823
0.515
-0.549  |     *|      | 
0.015
        7 
6.6580
6.4064
0.1564
0.2517
0.516
0.487  |      |      | 
0.011
        8 
6.3821
6.2276
0.2081
0.1545
0.498
0.311  |      |      | 
0.008
        9 
6.2499
6.8468
0.1780
-0.5969
0.509
-1.172  |    **|      | 
0.084
       10 
6.3957
6.9079
0.1968
-0.5122
0.502
-1.020  |    **|      | 
0.080
       11 
7.2610
6.8261
0.1722
0.4349
0.511
0.851  |      |*     | 
0.041
       12 
6.4043
6.9038
0.1955
-0.4995
0.503
-0.993  |     *|      | 
0.075
       13 
8.3064
6.9230
0.2017
1.3835
0.500
2.765  |      |***** | 
0.621
       14 
7.3582
6.9612
0.2146
0.3970
0.495
0.802  |      |*     | 
0.060
       15 
6.7613
6.9032
0.1953
-0.1419
0.503
-0.282  |      |      | 
0.006
       16 
5.9685
6.6986
0.1440
-0.7301
0.520
-1.404  |    **|      | 
0.076
 Sum of Residuals 
0
 Sum of Squared Residuals 
4.07432
 Predicted Residual SS (PRESS) 5.32456


11:29 Monday, February 12, 2018
22
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M7
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:29 Monday, February 12, 2018
22
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M7
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=12 Param=lnAe
 Number of Observations Read 
16
 Number of Observations Used 
15
 Number of Observations with Missing Values 
1
Analysis of Variance
Source
DF Sum of
Squares
Mean
Square
F Value Pr > F
 Model 
1 0.17671 0.17671
0.31 0.5877
 Error 
13 7.43189 0.57168
 Corrected Total 14 7.60860
 Root MSE 
0.75610  R-Square 
0.0232
 Dependent Mean 
-6.16898  Adj R-Sq -0.0519
 Coeff Var 
-12.25644    
Parameter Estimates
Variable
Label
DF Parameter
Estimate
Standard
Error
t Value Pr > |t|
95%
Confidence
Limits
 Intercept Intercept
1
-5.99737
0.36523
-16.42
<.0001 -6.78640 -5.20833
 CrLR 
CrLR
1
-0.00212
0.00382
-0.56
0.5877 -0.01038
0.00613


11:29 Monday, February 12, 2018
23
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M7
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:29 Monday, February 12, 2018
23
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M7
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=12 Param=lnAe
Output Statistics
Obs
Dependent
Variable
Predicted
Value
Std Error
Mean Predict
Residual Std Error
Residual
Student
Residual
-2-1 0 1 2
Cook's
D
        1 
-7.1438
-6.3453
0.3724
-0.7985
0.658
-1.213  |    **|      | 
0.236
        2 
-6.2229
-6.3219
0.3374
0.0990
0.677
0.146  |      |      | 
0.003
        3 
-5.9946
-6.2107
0.2091
0.2161
0.727
0.297  |      |      | 
0.004
        4 
-5.9941
-6.2614
0.2564
0.2674
0.711
0.376  |      |      | 
0.009
        5 
-6.3269
0.3447
                 
        6 
-6.5071
-6.2526
0.2464
-0.2545
0.715
-0.356  |      |      | 
0.008
        7 
-5.9998
-6.2445
0.2379
0.2447
0.718
0.341  |      |      | 
0.006
        8 
-5.6880
-6.3103
0.3205
0.6223
0.685
0.909  |      |*     | 
0.090
        9 
-6.6017
-6.0825
0.2496
-0.5192
0.714
-0.728  |     *|      | 
0.032
       10 
-7.8341
-6.0600
0.2766
-1.7741
0.704
-2.521  | *****|      | 
0.491
       11 
-5.0590
-6.0901
0.2413
1.0311
0.717
1.439  |      |**    | 
0.117
       12 
-5.2374
-6.0615
0.2747
0.8242
0.704
1.170  |      |**    | 
0.104
       13 
-6.1180
-6.0545
0.2838
-0.0635
0.701
-0.0907  |      |      | 
0.001
       14 
-5.2191
-6.0404
0.3026
0.8213
0.693
1.185  |      |**    | 
0.134
       15 
-6.2464
-6.0618
0.2744
-0.1846
0.705
-0.262  |      |      | 
0.005
       16 
-6.6686
-6.1370
0.2035
-0.5315
0.728
-0.730  |     *|      | 
0.021
 Sum of Residuals 
0
 Sum of Squared Residuals 
7.43189
 Predicted Residual SS (PRESS) 10.09273


11:29 Monday, February 12, 2018
24
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M7
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:29 Monday, February 12, 2018
24
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M7
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=13 Param=lnLambda_z
 Number of Observations Read 16
 Number of Observations Used 16
Analysis of Variance
Source
DF Sum of
Squares
Mean
Square
F Value Pr > F
 Model 
1 0.70917 0.70917
6.00 0.0281
 Error 
14 1.65468 0.11819
 Corrected Total 15 2.36384
 Root MSE 
0.34379  R-Square 0.3000
 Dependent Mean 
-2.22942  Adj R-Sq 0.2500
 Coeff Var 
-15.42056    
Parameter Estimates
Variable
Label
DF Parameter
Estimate
Standard
Error
t Value Pr > |t|
95%
Confidence Limits
 Intercept Intercept
1
-2.57109
0.16384
-15.69
<.0001
-2.92248 -2.21969
 CrLR 
CrLR
1
0.00400
0.00163
2.45
0.0281 0.00049737
0.00750


11:29 Monday, February 12, 2018
25
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M7
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:29 Monday, February 12, 2018
25
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M7
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=13 Param=lnLambda_z
Output Statistics
Obs
Dependent
Variable
Predicted
Value
Std Error
Mean Predict
Residual Std Error
Residual
Student
Residual
-2-1 0 1 2
Cook's
D
        1 
-2.2929
-1.9160
0.1541
-0.3769
0.307
-1.226  |    **|      | 
0.189
        2 
-2.2301
-1.9600
0.1396
-0.2700
0.314
-0.859  |     *|      | 
0.073
        3 
-1.4705
-2.1695
0.0894
0.6990
0.332
2.105  |      |****  | 
0.161
        4 
-1.8428
-2.0740
0.1068
0.2311
0.327
0.707  |      |*     | 
0.027
        5 
-1.9037
-1.9507
0.1426
0.0470
0.313
0.150  |      |      | 
0.002
        6 
-1.6945
-2.0906
0.1029
0.3962
0.328
1.208  |      |**    | 
0.072
        7 
-2.0993
-2.1058
0.0997 0.006487
0.329
0.0197  |      |      | 
0.000
        8 
-2.1799
-1.9819
0.1326
-0.1980
0.317
-0.624  |     *|      | 
0.034
        9 
-2.6396
-2.4108
0.1134
-0.2288
0.325
-0.705  |     *|      | 
0.030
       10 
-1.8833
-2.4531
0.1254
0.5699
0.320
1.780  |      |***   | 
0.243
       11 
-2.6476
-2.3965
0.1097
-0.2511
0.326
-0.771  |     *|      | 
0.034
       12 
-2.2166
-2.4503
0.1246
0.2336
0.320
0.729  |      |*     | 
0.040
       13 
-2.7170
-2.4635
0.1285
-0.2535
0.319
-0.795  |     *|      | 
0.051
       14 
-2.7944
-2.4901
0.1368
-0.3044
0.315
-0.965  |     *|      | 
0.088
       15 
-2.6362
-2.4498
0.1244
-0.1864
0.320
-0.582  |     *|      | 
0.026
       16 
-2.4224
-2.3081
0.0918
-0.1143
0.331
-0.345  |      |      | 
0.005
 Sum of Residuals 
0
 Sum of Squared Residuals 
1.65468
 Predicted Residual SS (PRESS) 2.12830


11:29 Monday, February 12, 2018
26
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M7
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:29 Monday, February 12, 2018
26
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M7
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=14 Param=RkTmax
 Number of Observations Read 16
 Number of Observations Used 16
Analysis of Variance
Source
DF
Sum of
Squares
Mean
Square
F Value Pr > F
 Model 
1
6.45865
6.45865
0.29 0.6005
 Error 
14 315.04135 22.50295
 Corrected Total 15 321.50000
 Root MSE 
4.74373  R-Square 
0.0201
 Dependent Mean 
8.50000  Adj R-Sq -0.0499
 Coeff Var 
55.80856    
Parameter Estimates
Variable
Label
DF Parameter
Estimate
Standard
Error
t Value Pr > |t|
95%
Confidence
Limits
 Intercept Intercept
1
7.46890
2.26067
3.30
0.0052
2.62024 12.31757
 CrLR 
CrLR
1
0.01207
0.02252
0.54
0.6005 -0.03624
0.06037


11:29 Monday, February 12, 2018
27
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M7
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:29 Monday, February 12, 2018
27
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M7
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=14 Param=RkTmax
Output Statistics
Obs
Dependent
Variable
Predicted
Value
Std Error
Mean Predict
Residual Std Error
Residual
Student
Residual
-2-1 0 1 2
Cook's
D
        1 
8.5000
9.4458
2.1268
-0.9458
4.240
-0.223  |      |      | 
0.006
        2 
12.5000
9.3130
1.9259
3.1870
4.335
0.735  |      |*     | 
0.053
        3 
3.0000
8.6809
1.2330
-5.6809
4.581
-1.240  |    **|      | 
0.056
        4 
8.5000
8.9691
1.4742
-0.4691
4.509
-0.104  |      |      | 
0.001
        5 
1.5000
9.3412
1.9677
-7.8412
4.316
-1.817  |   ***|      | 
0.343
        6 
8.5000
8.9189
1.4205
-0.4189
4.526
-0.0926  |      |      | 
0.000
        7 
15.0000
8.8732
1.3754
6.1268
4.540
1.350  |      |**    | 
0.084
        8 
12.5000
9.2468
1.8302
3.2532
4.376
0.743  |      |*     | 
0.048
        9 
1.5000
7.9526
1.5654
-6.4526
4.478
-1.441  |    **|      | 
0.127
       10 
8.5000
7.8249
1.7304
0.6751
4.417
0.153  |      |      | 
0.002
       11 
16.0000
7.9959
1.5139
8.0041
4.496
1.780  |      |***   | 
0.180
       12 
8.5000
7.8335
1.7188
0.6665
4.421
0.151  |      |      | 
0.002
       13 
4.0000
7.7935
1.7736
-3.7935
4.400
-0.862  |     *|      | 
0.060
       14 
5.0000
7.7135
1.8873
-2.7135
4.352
-0.623  |     *|      | 
0.037
       15 
8.5000
7.8348
1.7170
0.6652
4.422
0.150  |      |      | 
0.002
       16 
14.0000
8.2624
1.2661
5.7376
4.572
1.255  |      |**    | 
0.060
 Sum of Residuals 
0
 Sum of Squared Residuals 
315.04135
 Predicted Residual SS (PRESS) 404.24623


11:29 Monday, February 12, 2018
28
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M7
(Healthy vs Severe)
ANOVA analysis
NON-PARAMETRIC TEST OF FIXED EFFECT for Tmax parameter
--------------------- SUMMARY REPORT ---------------------
The NPAR1WAY Procedure
11:29 Monday, February 12, 2018
28
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M7
(Healthy vs Severe)
ANOVA analysis
NON-PARAMETRIC TEST OF FIXED EFFECT for Tmax parameter
--------------------- SUMMARY REPORT ---------------------
The NPAR1WAY Procedure
Wilcoxon Scores (Rank Sums) for Variable Value
Classified by Variable Group
Group
N
Sum of
Scores
Expected
Under H0
Std Dev
Under H0
Mean
Score
 1 
8
70.0
68.0 9.259230
8.750
 2 
8
66.0
68.0 9.259230
8.250
Average scores were used for ties.
Wilcoxon Two-Sample Test
 Statistic 
70.0000
   
 Normal Approximation 
 Z 
0.1620
 One-Sided Pr >  Z 
0.4357
 Two-Sided Pr > |Z| 
0.8713
   
 t Approximation 
 One-Sided Pr >  Z 
0.4367
 Two-Sided Pr > |Z| 
0.8735
Z includes a continuity correction of 0.5.
Kruskal-Wallis Test
 Chi-Square 
0.0467
 DF 
1
 Pr > Chi-Square 
0.8290
Hodges-Lehmann Estimation
Location Shift (1 - 2)    0.0000
Type
90%
Confidence
Limits
Interval
Midpoint
Asymptotic
Standard Error
 Asymptotic (Moses) -0.7500 0.5000
-0.1250
0.3800
 Exact 
-0.7500 0.5000
-0.1250


10:15 Monday, January 22, 2018
1
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M7 - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
RAW DATA
--------------------- SUMMARY REPORT ---------------------
10:15 Monday, January 22, 2018
1
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M7 - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
RAW DATA
--------------------- SUMMARY REPORT ---------------------
Renal Function Group=Normal
Obs Subject
Cmax
Tmax
AUCT
Thalf
Ae
AUCinf
Res_Area Lambda_z lnCmax
lnAUCT
 1 101
42.00000 2.00000 388.30000 6.86451 0.00079 399.05876
2.69603
0.10098 3.73767 5.96178
 2 102
63.80000 2.50000 665.35750 6.44652 0.00198 681.17001
2.32138
0.10752 4.15575 6.50032
 3 103
101.00000 1.25000 526.88250 3.01629 0.00249 541.63949
2.72450
0.22980 4.61512 6.26698
 4 104
99.80000 2.00000 707.53067 4.37683 0.00249 725.99535
2.54336
0.15837 4.60317 6.56178
 5 105
59.20000 1.00000 439.38500 4.65142
453.00695
3.00701
0.14902 4.08092 6.08538
 6 106
71.60000 2.00000 440.10750 3.77330 0.00149 446.82229
1.50279
0.18370 4.27110 6.08702
 7 107
72.30000 3.00000 767.57700 5.65628 0.00248 779.01561
1.46834
0.12254 4.28082 6.64324
 8 108
60.80000 2.50000 581.04250 6.13125 0.00339 591.19310
1.71697
0.11305 4.10759 6.36482
Obs lnAUCinf
lnAe
lnLambda_z RkTmax
eGFR
CrLR
 1 
5.98911 -7.14378
-2.29288
8.5 115.00000 163.85000
 2 
6.52381 -6.22294
-2.23005
12.5 102.00000 152.84000
 3 
6.29460 -5.99463
-1.47054
3.0
94.00000 100.45000
 4 
6.58754 -5.99405
-1.84284
8.5 109.00000 124.34000
 5 
6.11591
-1.90368
1.5 102.00000 155.18000
 6 
6.10216 -6.50710
-1.69446
8.5 116.00000 120.18000
 7 
6.65803 -5.99982
-2.09928
15.0
98.00000 116.39000
 8 
6.38214 -5.68805
-2.17991
12.5 118.00000 147.36000


10:15 Monday, January 22, 2018
2
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M7 - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
RAW DATA
--------------------- SUMMARY REPORT ---------------------
10:15 Monday, January 22, 2018
2
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M7 - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
RAW DATA
--------------------- SUMMARY REPORT ---------------------
Renal Function Group=Severe
Obs Subject
Cmax
Tmax
AUCT
Thalf
Ae
AUCinf
Res_Area Lambda_z lnCmax
lnAUCT
 9 013-01
80.40000 2.00000
581.41500
4.55733 0.00040
599.24800
2.97590
0.15209 4.38701 6.36546
 10 013-02
247.00000 1.50000 3662.33500 10.49066 0.00220 4049.76869
9.56681
0.06607 5.50939 8.20586
 11 013-03
97.10000 4.00000 1312.96000
9.78691 0.00635 1423.69135
7.77776
0.07082 4.57574 7.18004
 12 013-04
30.30000 2.56667
373.34958
7.81383 0.00127
390.93106
4.49734
0.08871 3.41115 5.92252
 13 013-05
157.00000 1.86667 1449.96833 11.33526 0.00541 1569.00249
7.58661
0.06115 5.05625 7.27930
 14 013-06
36.10000 1.00000
480.53000
9.70927 0.00136
517.98321
7.23058
0.07139 3.58629 6.17489
 15 013-07
70.20000 2.00000
595.48083
6.36062 0.00531
604.46565
1.48641
0.10897 4.25135 6.38937
 16 013-08
124.00000 2.00000
826.49500
9.67678 0.00194
863.75748
4.31400
0.07163 4.82028 6.71719
Obs lnAUCinf
lnAe
lnLambda_z RkTmax
eGFR
CrLR
 9 
6.39568 -7.83410
-1.88325
8.5 23.00000 29.51000
 10 
8.30642 -6.11803
-2.71700
4.0 27.00000 26.90000
 11 
7.26101 -5.05902
-2.64756
16.0 26.00000 43.68000
 12 
5.96853 -6.66858
-2.42241
14.0 28.00000 65.77000
 13 
7.35820 -5.21913
-2.79443
5.0 16.00000 20.27000
 14 
6.24994 -6.60174
-2.63959
1.5 26.00000 40.09000
 15 
6.40434 -5.23737
-2.21664
8.5 19.00000 30.22000
 16 
6.76129 -6.24641
-2.63624
8.5 21.00000 30.33000


10:15 Monday, January 22, 2018
3
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M7 - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
DESCRIPTIVE RESULTS (OVERALL)
--------------------- SUMMARY REPORT ---------------------
10:15 Monday, January 22, 2018
3
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M7 - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
DESCRIPTIVE RESULTS (OVERALL)
--------------------- SUMMARY REPORT ---------------------
Parameter
Renal
Function
Group
n
Min
Mean
Geometric
Mean
Median
Max
Standard
Deviation
Coefficient
of
Variation
Cmax
Normal
8
42.00000
71.31250
68.82161
67.70000
101.00000
20.23727
28.3783
Cmax
Severe
8
30.30000
105.26250
85.59976
88.75000
247.00000
71.14809
67.5911
Tmax
Normal
8
1.00000
2.03125
1.92365
2.00000
3.00000
0.66059
32.5215
Tmax
Severe
8
1.00000
2.11667
1.97338
2.00000
4.00000
0.88479
41.8012
AUCT
Normal
8 388.30000
564.52283 549.44841 553.96250
767.57700
139.24936
24.6667
AUCT
Severe
8 373.34958 1160.31672 879.47766 710.98792 3662.33500 1083.27048
93.3599
Thalf
Normal
8
3.01629
5.11455
4.94162
5.15385
6.86451
1.36926
26.7718
Thalf
Severe
8
4.55733
8.71633
8.39912
9.69302
11.33526
2.29044
26.2775
Ae
Normal
7
0.00079
0.00216
0.00199
0.00248
0.00339
0.00083
38.6537
Ae
Severe
8
0.00040
0.00303
0.00219
0.00207
0.00635
0.00229
75.4936
AUCinf
Normal
8 399.05876
577.23770 562.09079 566.41629
779.01561
141.06547
24.4380
AUCinf
Severe
8 390.93106 1252.35599 932.78585 734.11156 4049.76869 1209.12103
96.5477
Res_Area
Normal
8
1.46834
2.24755
2.17132
2.43237
3.00701
0.60258
26.8105
Res_Area
Severe
8
1.48641
5.67943
4.93235
5.86396
9.56681
2.77000
48.7726
Lambda_z
Normal
8
0.10098
0.14562
0.14027
0.13578
0.22980
0.04432
30.4331
Lambda_z
Severe
8
0.06115
0.08636
0.08253
0.07151
0.15209
0.03063
35.4702
lnCmax
Normal
8
3.73767
4.23152
4.21342
4.61512
0.28709
6.7845
lnCmax
Severe
8
3.41115
4.44968
4.48138
5.50939
0.70826
15.9170
lnAUCT
Normal
8
5.96178
6.30891
6.31590
6.64324
0.24984
3.9601
lnAUCT
Severe
8
5.92252
6.77933
6.55328
8.20586
0.74376
10.9709
lnAUCinf
Normal
8
5.98911
6.33166
6.33837
6.65803
0.24767
3.9117
lnAUCinf
Severe
8
5.96853
6.83818
6.58282
8.30642
0.76505
11.1880
lnAe
Normal
7
-7.14378
-6.22148
-5.99982
-5.68805
0.47768
-7.6780
lnAe
Severe
8
-7.83410
-6.12305
-6.18222
-5.05902
0.94138
-15.3743
lnLambda_z Normal
8
-2.29288
-1.96421
-2.00148
-1.47054
0.28744
-14.6337
lnLambda_z Severe
8
-2.79443
-2.49464
-2.63792
-1.88325
0.30707
-12.3094
RkTmax
Normal
8
1.50000
8.75000
7.10269
8.50000
15.00000
4.67516
53.4304
RkTmax
Severe
8
1.50000
8.25000
6.71357
8.50000
16.00000
4.89168
59.2931


10:15 Monday, January 22, 2018
4
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M7 - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
--------------------- SUMMARY REPORT ---------------------
The Mixed Procedure
10:15 Monday, January 22, 2018
4
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M7 - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
--------------------- SUMMARY REPORT ---------------------
The Mixed Procedure
Order=1 Param=Cmax
Model Information
 Data Set 
WORK.KINDATA
 Dependent Variable 
Value
 Covariance Structure 
Variance Components
 Group Effect 
FunctionGroup
 Estimation Method 
REML
 Residual Variance Method 
None
 Fixed Effects SE Method 
Model-Based
 Degrees of Freedom Method Between-Within
Class Level Information
Class
Levels
Values
 FunctionGroup 
2 Severe Normal
Dimensions
 Covariance Parameters 
2
 Columns in X 
3
 Columns in Z 
0
 Subjects 
16
 Max Obs per Subject 
1
Number of Observations
 Number of Observations Read 
16
 Number of Observations Used 
16
 Number of Observations Not Used 
0
Iteration History
Iteration Evaluations -2 Res Log Like Criterion
      0 
1
154.68766592
      1 
1
145.70121256 0.00000000
Convergence criteria met.
Covariance Parameter Estimates
Cov Parm
Group
Estimate
 Residual FunctionGroup Severe
5062.05
 Residual FunctionGroup Normal
409.55
Fit Statistics
 -2 Res Log Likelihood 
145.7
 AIC (Smaller is Better) 
149.7
 AICC (Smaller is Better) 150.8
 BIC (Smaller is Better) 
151.2
Null Model Likelihood
Ratio Test
DF
Chi-Square Pr > ChiSq
1
8.99
0.0027
Type 3 Tests of Fixed Effects
Effect
Num
DF
Den
DF
F Value Pr > F
 FunctionGroup 
1
14
1.69 0.2152
Least Squares Means
Effect
Renal
Function
Group
Estimate Standard
Error
DF t Value Pr > |t| Alpha
Lower
Upper
 FunctionGroup Severe
105.26
25.1546 14
4.18
0.0009
0.1 60.9574
149.57
 FunctionGroup Normal
71.3125
7.1550 14
9.97
<.0001
0.1 58.7104 83.9146
Differences of Least Squares Means
Effect
Renal
Function
Group
Renal
Function
Group
Estimate Standard
Error
DF t Value Pr > |t| Alpha
Lower
Upper
 FunctionGroup Severe
Normal
33.9500
26.1524 14
1.30
0.2152
0.1 -12.1125 80.0125


10:15 Monday, January 22, 2018
5
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M7 - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
--------------------- SUMMARY REPORT ---------------------
The Mixed Procedure
10:15 Monday, January 22, 2018
5
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M7 - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
--------------------- SUMMARY REPORT ---------------------
The Mixed Procedure
Order=3 Param=AUCT
Model Information
 Data Set 
WORK.KINDATA
 Dependent Variable 
Value
 Covariance Structure 
Variance Components
 Group Effect 
FunctionGroup
 Estimation Method 
REML
 Residual Variance Method 
None
 Fixed Effects SE Method 
Model-Based
 Degrees of Freedom Method Between-Within
Class Level Information
Class
Levels
Values
 FunctionGroup 
2 Severe Normal
Dimensions
 Covariance Parameters 
2
 Columns in X 
3
 Columns in Z 
0
 Subjects 
16
 Max Obs per Subject 
1
Number of Observations
 Number of Observations Read 
16
 Number of Observations Used 
16
 Number of Observations Not Used 
0
Iteration History
Iteration Evaluations -2 Res Log Like Criterion
      0 
1
230.07126462
      1 
1
210.82524991 0.00000000
Convergence criteria met.
Covariance Parameter Estimates
Cov Parm
Group
Estimate
 Residual FunctionGroup Severe
1173475
 Residual FunctionGroup Normal
19390
Fit Statistics
 -2 Res Log Likelihood 
210.8
 AIC (Smaller is Better) 
214.8
 AICC (Smaller is Better) 215.9
 BIC (Smaller is Better) 
216.4
Null Model Likelihood
Ratio Test
DF
Chi-Square Pr > ChiSq
1
19.25
<.0001
Type 3 Tests of Fixed Effects
Effect
Num
DF
Den
DF
F Value Pr > F
 FunctionGroup 
1
14
2.38 0.1451
Least Squares Means
Effect
Renal
Function
Group
Estimate Standard
Error
DF t Value Pr > |t| Alpha
Lower
Upper
 FunctionGroup Severe
1160.32
382.99 14
3.03
0.0090
0.1 485.75 1834.89
 FunctionGroup Normal
564.52
49.2321 14
11.47
<.0001
0.1 477.81
651.24
Differences of Least Squares Means
Effect
Renal
Function
Group
Renal
Function
Group
Estimate Standard
Error
DF t Value Pr > |t| Alpha
Lower
Upper
 FunctionGroup Severe
Normal
595.79
386.15 14
1.54
0.1451
0.1 -84.3277 1275.92


10:15 Monday, January 22, 2018
6
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M7 - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
--------------------- SUMMARY REPORT ---------------------
The Mixed Procedure
10:15 Monday, January 22, 2018
6
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M7 - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
--------------------- SUMMARY REPORT ---------------------
The Mixed Procedure
Order=6 Param=AUCinf
Model Information
 Data Set 
WORK.KINDATA
 Dependent Variable 
Value
 Covariance Structure 
Variance Components
 Group Effect 
FunctionGroup
 Estimation Method 
REML
 Residual Variance Method 
None
 Fixed Effects SE Method 
Model-Based
 Degrees of Freedom Method Between-Within
Class Level Information
Class
Levels
Values
 FunctionGroup 
2 Severe Normal
Dimensions
 Covariance Parameters 
2
 Columns in X 
3
 Columns in Z 
0
 Subjects 
16
 Max Obs per Subject 
1
Number of Observations
 Number of Observations Read 
16
 Number of Observations Used 
16
 Number of Observations Not Used 
0
Iteration History
Iteration Evaluations -2 Res Log Like Criterion
      0 
1
233.10854613
      1 
1
212.54538495 0.00000000
Convergence criteria met.
Covariance Parameter Estimates
Cov Parm
Group
Estimate
 Residual FunctionGroup Severe
1461974
 Residual FunctionGroup Normal
19899
Fit Statistics
 -2 Res Log Likelihood 
212.5
 AIC (Smaller is Better) 
216.5
 AICC (Smaller is Better) 217.6
 BIC (Smaller is Better) 
218.1
Null Model Likelihood
Ratio Test
DF
Chi-Square Pr > ChiSq
1
20.56
<.0001
Type 3 Tests of Fixed Effects
Effect
Num
DF
Den
DF
F Value Pr > F
 FunctionGroup 
1
14
2.46 0.1391
Least Squares Means
Effect
Renal
Function
Group
Estimate Standard
Error
DF t Value Pr > |t| Alpha
Lower
Upper
 FunctionGroup Severe
1252.36
427.49 14
2.93
0.0110
0.1 499.42 2005.30
 FunctionGroup Normal
577.24
49.8742 14
11.57
<.0001
0.1 489.39
665.08
Differences of Least Squares Means
Effect
Renal
Function
Group
Renal
Function
Group
Estimate Standard
Error
DF t Value Pr > |t| Alpha
Lower
Upper
 FunctionGroup Severe
Normal
675.12
430.39 14
1.57
0.1391
0.1 -82.9291 1433.17


10:15 Monday, January 22, 2018
7
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M7 - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
--------------------- SUMMARY REPORT ---------------------
The Mixed Procedure
10:15 Monday, January 22, 2018
7
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M7 - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
--------------------- SUMMARY REPORT ---------------------
The Mixed Procedure
Order=9 Param=lnCmax
Model Information
 Data Set 
WORK.KINDATA
 Dependent Variable 
Value
 Covariance Structure 
Variance Components
 Group Effect 
FunctionGroup
 Estimation Method 
REML
 Residual Variance Method 
None
 Fixed Effects SE Method 
Model-Based
 Degrees of Freedom Method Between-Within
Class Level Information
Class
Levels
Values
 FunctionGroup 
2 Severe Normal
Dimensions
 Covariance Parameters 
2
 Columns in X 
3
 Columns in Z 
0
 Subjects 
16
 Max Obs per Subject 
1
Number of Observations
 Number of Observations Read 
16
 Number of Observations Used 
16
 Number of Observations Not Used 
0
Iteration History
Iteration Evaluations -2 Res Log Like Criterion
      0 
1
26.65625828
      1 
1
21.58833865 0.00000000
Convergence criteria met.
Covariance Parameter Estimates
Cov Parm
Group
Estimate
 Residual FunctionGroup Severe
0.5016
 Residual FunctionGroup Normal
0.08242
Fit Statistics
 -2 Res Log Likelihood 
21.6
 AIC (Smaller is Better) 
25.6
 AICC (Smaller is Better) 
26.7
 BIC (Smaller is Better) 
27.1
Null Model Likelihood
Ratio Test
DF
Chi-Square Pr > ChiSq
1
5.07
0.0244
Type 3 Tests of Fixed Effects
Effect
Num
DF
Den
DF
F Value Pr > F
 FunctionGroup 
1
14
0.65 0.4329
Least Squares Means
Effect
Renal
Function
Group
Estimate Standard
Error
DF t Value Pr > |t| Alpha
Lower
Upper
 FunctionGroup Severe
4.4497
0.2504 14
17.77
<.0001
0.1 4.0086 4.8907
 FunctionGroup Normal
4.2315
0.1015 14
41.69
<.0001
0.1 4.0527 4.4103
Differences of Least Squares Means
Effect
Renal
Function
Group
Renal
Function
Group
Estimate Standard
Error
DF t Value Pr > |t| Alpha
Lower
Upper
 FunctionGroup Severe
Normal
0.2182
0.2702 14
0.81
0.4329
0.1 -0.2577 0.6941


10:15 Monday, January 22, 2018
8
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M7 - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
--------------------- SUMMARY REPORT ---------------------
The Mixed Procedure
10:15 Monday, January 22, 2018
8
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M7 - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
--------------------- SUMMARY REPORT ---------------------
The Mixed Procedure
Order=10 Param=lnAUCT
Model Information
 Data Set 
WORK.KINDATA
 Dependent Variable 
Value
 Covariance Structure 
Variance Components
 Group Effect 
FunctionGroup
 Estimation Method 
REML
 Residual Variance Method 
None
 Fixed Effects SE Method 
Model-Based
 Degrees of Freedom Method Between-Within
Class Level Information
Class
Levels
Values
 FunctionGroup 
2 Severe Normal
Dimensions
 Covariance Parameters 
2
 Columns in X 
3
 Columns in Z 
0
 Subjects 
16
 Max Obs per Subject 
1
Number of Observations
 Number of Observations Read 
16
 Number of Observations Used 
16
 Number of Observations Not Used 
0
Iteration History
Iteration Evaluations -2 Res Log Like Criterion
      0 
1
27.39274070
      1 
1
20.32759078 0.00000000
Convergence criteria met.
Covariance Parameter Estimates
Cov Parm
Group
Estimate
 Residual FunctionGroup Severe
0.5532
 Residual FunctionGroup Normal
0.06242
Fit Statistics
 -2 Res Log Likelihood 
20.3
 AIC (Smaller is Better) 
24.3
 AICC (Smaller is Better) 
25.4
 BIC (Smaller is Better) 
25.9
Null Model Likelihood
Ratio Test
DF
Chi-Square Pr > ChiSq
1
7.07
0.0079
Type 3 Tests of Fixed Effects
Effect
Num
DF
Den
DF
F Value Pr > F
 FunctionGroup 
1
14
2.88 0.1120
Least Squares Means
Effect
Renal
Function
Group
Estimate Standard
Error
DF t Value Pr > |t| Alpha
Lower
Upper
 FunctionGroup Severe
6.7793
0.2630 14
25.78
<.0001
0.1 6.3162 7.2425
 FunctionGroup Normal
6.3089
0.08833 14
71.42
<.0001
0.1 6.1533 6.4645
Differences of Least Squares Means
Effect
Renal
Function
Group
Renal
Function
Group
Estimate Standard
Error
DF t Value Pr > |t| Alpha
Lower
Upper
 FunctionGroup Severe
Normal
0.4704
0.2774 14
1.70
0.1120
0.1 -0.01817 0.9590


10:15 Monday, January 22, 2018
9
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M7 - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
--------------------- SUMMARY REPORT ---------------------
The Mixed Procedure
10:15 Monday, January 22, 2018
9
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M7 - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
--------------------- SUMMARY REPORT ---------------------
The Mixed Procedure
Order=11 Param=lnAUCinf
Model Information
 Data Set 
WORK.KINDATA
 Dependent Variable 
Value
 Covariance Structure 
Variance Components
 Group Effect 
FunctionGroup
 Estimation Method 
REML
 Residual Variance Method 
None
 Fixed Effects SE Method 
Model-Based
 Degrees of Freedom Method Between-Within
Class Level Information
Class
Levels
Values
 FunctionGroup 
2 Severe Normal
Dimensions
 Covariance Parameters 
2
 Columns in X 
3
 Columns in Z 
0
 Subjects 
16
 Max Obs per Subject 
1
Number of Observations
 Number of Observations Read 
16
 Number of Observations Used 
16
 Number of Observations Not Used 
0
Iteration History
Iteration Evaluations -2 Res Log Like Criterion
      0 
1
28.08183081
      1 
1
20.60090093 0.00000000
Convergence criteria met.
Covariance Parameter Estimates
Cov Parm
Group
Estimate
 Residual FunctionGroup Severe
0.5853
 Residual FunctionGroup Normal
0.06134
Fit Statistics
 -2 Res Log Likelihood 
20.6
 AIC (Smaller is Better) 
24.6
 AICC (Smaller is Better) 
25.7
 BIC (Smaller is Better) 
26.1
Null Model Likelihood
Ratio Test
DF
Chi-Square Pr > ChiSq
1
7.48
0.0062
Type 3 Tests of Fixed Effects
Effect
Num
DF
Den
DF
F Value Pr > F
 FunctionGroup 
1
14
3.17 0.0965
Least Squares Means
Effect
Renal
Function
Group
Estimate Standard
Error
DF t Value Pr > |t| Alpha
Lower
Upper
 FunctionGroup Severe
6.8382
0.2705 14
25.28
<.0001
0.1 6.3618 7.3146
 FunctionGroup Normal
6.3317
0.08757 14
72.31
<.0001
0.1 6.1774 6.4859
Differences of Least Squares Means
Effect
Renal
Function
Group
Renal
Function
Group
Estimate Standard
Error
DF t Value Pr > |t| Alpha
Lower
Upper
 FunctionGroup Severe
Normal
0.5065
0.2843 14
1.78
0.0965
0.1 0.005757 1.0073


10:15 Monday, January 22, 2018
10
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M7 - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
--------------------- SUMMARY REPORT ---------------------
The Mixed Procedure
10:15 Monday, January 22, 2018
10
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M7 - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
--------------------- SUMMARY REPORT ---------------------
The Mixed Procedure
Order=14 Param=RkTmax
Model Information
 Data Set 
WORK.KINDATA
 Dependent Variable 
Value
 Covariance Structure 
Variance Components
 Group Effect 
FunctionGroup
 Estimation Method 
REML
 Residual Variance Method 
None
 Fixed Effects SE Method 
Model-Based
 Degrees of Freedom Method Between-Within
Class Level Information
Class
Levels
Values
 FunctionGroup 
2 Severe Normal
Dimensions
 Covariance Parameters 
2
 Columns in X 
3
 Columns in Z 
0
 Subjects 
16
 Max Obs per Subject 
1
Number of Observations
 Number of Observations Read 
16
 Number of Observations Used 
16
 Number of Observations Not Used 
0
Iteration History
Iteration Evaluations -2 Res Log Like Criterion
      0 
1
87.72071127
      1 
1
87.70636883 0.00000000
Convergence criteria met.
Covariance Parameter Estimates
Cov Parm
Group
Estimate
 Residual FunctionGroup Severe
23.9286
 Residual FunctionGroup Normal
21.8571
Fit Statistics
 -2 Res Log Likelihood 
87.7
 AIC (Smaller is Better) 
91.7
 AICC (Smaller is Better) 
92.8
 BIC (Smaller is Better) 
93.3
Null Model Likelihood
Ratio Test
DF
Chi-Square Pr > ChiSq
1
0.01
0.9047
Type 3 Tests of Fixed Effects
Effect
Num
DF
Den
DF
F Value Pr > F
 FunctionGroup 
1
14
0.04 0.8375
Least Squares Means
Effect
Renal
Function
Group
Estimate Standard
Error
DF t Value Pr > |t| Alpha
Lower
Upper
 FunctionGroup Severe
8.2500
1.7295 14
4.77
0.0003
0.1 5.2039 11.2961
 FunctionGroup Normal
8.7500
1.6529 14
5.29
0.0001
0.1 5.8387 11.6613
Differences of Least Squares Means
Effect
Renal
Function
Group
Renal
Function
Group
Estimate Standard
Error
DF t Value Pr > |t| Alpha
Lower
Upper
 FunctionGroup Severe
Normal
-0.5000
2.3923 14
-0.21
0.8375
0.1 -4.7136 3.7136


10:15 Monday, January 22, 2018
11
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M7 - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
Geometric LSmeans
--------------------- SUMMARY REPORT ---------------------
10:15 Monday, January 22, 2018
11
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M7 - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
Geometric LSmeans
--------------------- SUMMARY REPORT ---------------------
Obs Parameters Group GeoLSmeans
 1 lnCmax
Severe
85.5998
 2 lnCmax
Normal
68.8216
 3 lnAUCT
Severe
879.48
 4 lnAUCT
Normal
549.45
 5 lnAUCinf
Severe
932.79
 6 lnAUCinf
Normal
562.09


10:15 Monday, January 22, 2018
12
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M7 - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
RATIO ESTIMATE BASED ON ln-TRANSFORMED PARAMETERS
--------------------- SUMMARY REPORT ---------------------
10:15 Monday, January 22, 2018
12
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M7 - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
RATIO ESTIMATE BASED ON ln-TRANSFORMED PARAMETERS
--------------------- SUMMARY REPORT ---------------------
Obs Parameters Group
vs
Group
Ratio
(%)
L90
U90
 1 lnCmax
Severe Normal 124.379
77.280 200.183
 2 lnAUCT
Severe Normal 160.066
98.199 260.907
 3 lnAUCinf
Severe Normal 165.949 100.577 273.811


Clinical Study Report  
Project No COL MIG-113/H8H-CD-LAHN 
 
16.1.9.7 Documentation of statistical analysis – SAS® output of M3 
Legend:  
AUCinf= AUC(0−∞) 
AUCT=AUC(0-tlast) 
Vz_F= VZ/F 
CL_F= CL/F 
LambdaZ = λZ 
lCmax= ln(Cmax) 
lAUCT= ln(AUC(0-tlast)) 
lAUCinf= ln(AUC(0−∞)) 
lCLF= ln(CL/F) 
lLambdaZ = ln(λZ) 
lVz_F= ln(VZ/F) 
RkTmax= Rank of Tmax 


11:22 Monday, February 12, 2018
1
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M3
(Healthy vs Severe)
ANOVA analysis
RAW DATA
--------------------- SUMMARY REPORT ---------------------
11:22 Monday, February 12, 2018
1
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M3
(Healthy vs Severe)
ANOVA analysis
RAW DATA
--------------------- SUMMARY REPORT ---------------------
Renal Function Group=Normal
Obs Subject
Cmax
Tmax
AUCT
Thalf
Ae
AUCinf
Res_Area Lambda_z lnCmax
lnAUCT
 1 101
14.00000 1.75000 45.30750 1.75421 1.34999 48.38157
6.35381
0.39513 2.63906 3.81347
 2 102
11.40000 2.00000 53.04500 2.87180 0.96915 57.14841
7.18026
0.24136 2.43361 3.97114
 3 103
14.70000 1.00000 33.71875 1.50087 0.69261 36.46914
7.54168
0.46183 2.68785 3.51805
 4 104
16.80000 1.58333 60.92925 3.29157 1.02231 66.09954
7.82198
0.21058 2.82138 4.10971
 5 105
24.30000 1.00000 71.99000 1.91495 2.54294 77.28180
6.84741
0.36197 3.19048 4.27653
 6 106
13.80000 2.00000 45.91250 1.81268 0.87162 49.50813
7.26270
0.38239 2.62467 3.82674
 7 107
11.90000 2.50000 62.35925 2.72587 1.10029 66.96819
6.88229
0.25428 2.47654 4.13291
 8 108
10.70000 1.75000 42.65250 2.55262 0.90420 50.04505 14.77180
0.27154 2.37024 3.75309
Obs lnAUCinf
lnAe
lnLambda_z RkTmax
eGFR
CrLR
 1 
3.87912
0.30010
-0.92853
8.5 115.00000 163.85000
 2 
4.04565 -0.03133
-1.42145
12.0 102.00000 152.84000
 3 
3.59647 -0.36729
-0.77256
3.5
94.00000 100.45000
 4 
4.19116
0.02206
-1.55788
7.0 109.00000 124.34000
 5 
4.34746
0.93332
-1.01621
3.5 102.00000 155.18000
 6 
3.90214 -0.13740
-0.96132
12.0 116.00000 120.18000
 7 
4.20422
0.09557
-1.36930
14.5
98.00000 116.39000
 8 
3.91292 -0.10071
-1.30363
8.5 118.00000 147.36000


11:22 Monday, February 12, 2018
2
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M3
(Healthy vs Severe)
ANOVA analysis
RAW DATA
--------------------- SUMMARY REPORT ---------------------
11:22 Monday, February 12, 2018
2
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M3
(Healthy vs Severe)
ANOVA analysis
RAW DATA
--------------------- SUMMARY REPORT ---------------------
Renal Function Group=Severe
Obs Subject
Cmax
Tmax
AUCT
Thalf
Ae
AUCinf
Res_Area Lambda_z lnCmax
lnAUCT
 9 201
13.80000 1.00000
82.06500 5.00063 0.17496
91.27968 10.09500
0.13861 2.62467 4.40751
 10 202
17.30000 2.00000
71.44500 2.83059 0.19433
76.21265
6.25572
0.24488 2.85071 4.26893
 11 203
15.90000 2.50000 105.23750 5.32130 0.41027 121.19195 13.16462
0.13026 2.76632 4.65622
 12 204
40.00000 1.81667 195.71667 3.39472 0.56391 203.01562
3.59527
0.20418 3.68888 5.27667
 13 205
28.60000 1.50000 120.06250 3.96358 0.32675 126.79522
5.30992
0.17488 3.35341 4.78801
 14 206
19.50000 0.75000
70.00292 3.40484 0.08056
75.62775
7.43752
0.20358 2.97041 4.24854
 15 207
21.20000 1.00000 102.14750 3.48605 0.35844 107.28247
4.78640
0.19883 3.05400 4.62642
 16 208
5.57000 2.56667
23.83792 2.33870 0.12406
27.53273 13.41972
0.29638 1.71740 3.17128
Obs lnAUCinf
lnAe
lnLambda_z RkTmax
eGFR
CrLR
 9 
4.51393 -1.74318
-1.97608
3.5 26.00000 40.09000
 10 
4.33353 -1.63820
-1.40700
12.0 23.00000 29.51000
 11 
4.79738 -0.89094
-2.03823
14.5 26.00000 43.68000
 12 
5.31328 -0.57287
-1.58873
10.0 19.00000 30.22000
 13 
4.84257 -1.11858
-1.74366
6.0 27.00000 26.90000
 14 
4.32582 -2.51873
-1.59171
1.0 16.00000 20.27000
 15 
4.67547 -1.02600
-1.61528
3.5 21.00000 30.33000
 16 
3.31538 -2.08697
-1.21611
16.0 28.00000 65.77000


11:22 Monday, February 12, 2018
3
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M3
(Healthy vs Severe)
ANOVA analysis
DESCRIPTIVE RESULTS (OVERALL)
--------------------- SUMMARY REPORT ---------------------
11:22 Monday, February 12, 2018
3
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M3
(Healthy vs Severe)
ANOVA analysis
DESCRIPTIVE RESULTS (OVERALL)
--------------------- SUMMARY REPORT ---------------------
Parameter
Renal
Function
Group
n
Min
Mean
Geometric
Mean
Median
Max
Standard
Deviation
Coefficient
of
Variation
Cmax
Normal
8 10.70000
14.70000
14.23179 13.90000
24.30000
4.35234
29.608
Cmax
Severe
8
5.57000
20.23375
17.78266 18.40000
40.00000
10.32319
51.020
Tmax
Normal
8
1.00000
1.69792
1.62445
1.75000
2.50000
0.50970
30.019
Tmax
Severe
8
0.75000
1.64167
1.50434
1.65833
2.56667
0.69591
42.390
AUCT
Normal
8 33.71875
51.98934
50.66348 49.47875
71.99000
12.48521
24.015
AUCT
Severe
8 23.83792
96.31438
83.96890 92.10625 195.71667
49.74951
51.653
Thalf
Normal
8
1.50087
2.30307
2.22520
2.23379
3.29157
0.64115
27.839
Thalf
Severe
8
2.33870
3.71755
3.59875
3.44544
5.32130
1.01576
27.323
Ae
Normal
8
0.69261
1.18164
1.09340
0.99573
2.54294
0.58197
49.252
Ae
Severe
8
0.08056
0.27916
0.23470
0.26054
0.56391
0.16404
58.763
AUCinf
Normal
8 36.46914
56.48773
55.14091 53.59673
77.28180
13.04790
23.099
AUCinf
Severe
8 27.53273 103.61726
91.34732 99.28108 203.01562
51.01128
49.230
Res_Area
Normal
8
6.35381
8.08274
7.79325
7.22148
14.77180
2.73985
33.898
Res_Area
Severe
8
3.59527
8.00802
7.24393
6.84662
13.41972
3.79397
47.377
Lambda_z
Normal
8
0.21058
0.32239
0.31150
0.31675
0.46183
0.08959
27.791
Lambda_z
Severe
8
0.13026
0.19895
0.19261
0.20121
0.29638
0.05423
27.260
lnCmax
Normal
8
2.37024
2.65548
2.63186
3.19048
0.26148
9.847
lnCmax
Severe
8
1.71740
2.87822
2.91056
3.68888
0.57909
20.120
lnAUCT
Normal
8
3.51805
3.92521
3.89894
4.27653
0.24504
6.243
lnAUCT
Severe
8
3.17128
4.43045
4.51696
5.27667
0.60693
13.699
lnAUCinf
Normal
8
3.59647
4.00989
3.97929
4.34746
0.23751
5.923
lnAUCinf
Severe
8
3.31538
4.51467
4.59470
5.31328
0.58038
12.855
lnAe
Normal
8 -0.36729
0.08929
-0.00464
0.93332
0.39131
438.252
lnAe
Severe
8 -2.51873
-1.44943
-1.37839
-0.57287
0.65909
-45.472
lnLambda_z Normal
8 -1.55788
-1.16636
-1.15992
-0.77256
0.28148
-24.133
lnLambda_z Severe
8 -2.03823
-1.64710
-1.60350
-1.21611
0.27293
-16.570
RkTmax
Normal
8
3.50000
8.68750
7.74418
8.50000
14.50000
4.00836
46.139
RkTmax
Severe
8
1.00000
8.31250
6.14992
8.00000
16.00000
5.59296
67.284


11:22 Monday, February 12, 2018
4
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M3
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:22 Monday, February 12, 2018
4
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M3
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=9 Param=lnCmax
 Number of Observations Read 16
 Number of Observations Used 16
Analysis of Variance
Source
DF Sum of
Squares
Mean
Square
F Value Pr > F
 Model 
1 0.26616 0.26616
1.35 0.2646
 Error 
14 2.75837 0.19703
 Corrected Total 15 3.02453
 Root MSE 
0.44388  R-Square 0.0880
 Dependent Mean 
2.76685  Adj R-Sq 0.0229
 Coeff Var 
16.04265    
Parameter Estimates
Variable
Label
DF Parameter
Estimate
Standard
Error
t Value Pr > |t|
95%
Confidence
Limits
 Intercept Intercept
1
2.96519
0.20355
14.57
<.0001
2.52861 3.40177
 eGFR 
eGFR
1
-0.00305
0.00263
-1.16
0.2646 -0.00868 0.00258


11:22 Monday, February 12, 2018
5
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M3
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:22 Monday, February 12, 2018
5
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M3
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=9 Param=lnCmax
Output Statistics
Obs
Dependent
Variable
Predicted
Value
Std Error
Mean Predict
Residual Std Error
Residual
Student
Residual
-2-1 0 1 2
Cook's
D
        1 
2.6391
2.6143
0.1719
0.0248
0.409
0.0605  |      |      | 
0.000
        2 
2.4336
2.6539
0.1475
-0.2203
0.419
-0.526  |     *|      | 
0.017
        3 
2.6878
2.6784
0.1346 0.009487
0.423
0.0224  |      |      | 
0.000
        4 
2.8214
2.6326
0.1602
0.1888
0.414
0.456  |      |      | 
0.016
        5 
3.1905
2.6539
0.1475
0.5365
0.419
1.282  |      |**    | 
0.102
        6 
2.6247
2.6112
0.1739
0.0134
0.408
0.0329  |      |      | 
0.000
        7 
2.4765
2.6662
0.1408
-0.1896
0.421
-0.450  |      |      | 
0.011
        8 
2.3702
2.6051
0.1780
-0.2349
0.407
-0.578  |     *|      | 
0.032
        9 
2.6247
2.8859
0.1510
-0.2612
0.417
-0.626  |     *|      | 
0.026
       10 
2.8507
2.8950
0.1564
-0.0443
0.415
-0.107  |      |      | 
0.001
       11 
2.7663
2.8859
0.1510
-0.1195
0.417
-0.286  |      |      | 
0.005
       12 
3.6889
2.9072
0.1640
0.7817
0.412
1.895  |      |***   | 
0.284
       13 
3.3534
2.8828
0.1492
0.4706
0.418
1.126  |      |**    | 
0.081
       14 
2.9704
2.9164
0.1699
0.0540
0.410
0.132  |      |      | 
0.001
       15 
3.0540
2.9011
0.1602
0.1529
0.414
0.369  |      |      | 
0.010
       16 
1.7174
2.8798
0.1475
-1.1624
0.419
-2.776  | *****|      | 
0.478
 Sum of Residuals 
0
 Sum of Squared Residuals 
2.75837
 Predicted Residual SS (PRESS) 3.54732


11:22 Monday, February 12, 2018
6
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M3
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:22 Monday, February 12, 2018
6
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M3
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=10 Param=lnAUCT
 Number of Observations Read 16
 Number of Observations Used 16
Analysis of Variance
Source
DF Sum of
Squares
Mean
Square
F Value Pr > F
 Model 
1 1.10064 1.10064
5.28 0.0375
 Error 
14 2.91927 0.20852
 Corrected Total 15 4.01991
 Root MSE 
0.45664  R-Square 0.2738
 Dependent Mean 
4.17783  Adj R-Sq 0.2219
 Coeff Var 
10.93006    
Parameter Estimates
Variable
Label
DF Parameter
Estimate
Standard
Error
t Value Pr > |t|
95%
Confidence Limits
 Intercept Intercept
1
4.58116
0.20941
21.88
<.0001
4.13202
5.03029
 eGFR 
eGFR
1
-0.00621
0.00270
-2.30
0.0375 -0.01200 -0.00041238


11:22 Monday, February 12, 2018
7
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M3
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:22 Monday, February 12, 2018
7
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M3
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=10 Param=lnAUCT
Output Statistics
Obs
Dependent
Variable
Predicted
Value
Std Error
Mean Predict
Residual Std Error
Residual
Student
Residual
-2-1 0 1 2
Cook's
D
        1 
3.8135
3.8676
0.1768
-0.0541
0.421
-0.128  |      |      | 
0.001
        2 
3.9711
3.9482
0.1517
0.0229
0.431
0.0532  |      |      | 
0.000
        3 
3.5181
3.9979
0.1384
-0.4798
0.435
-1.103  |    **|      | 
0.062
        4 
4.1097
3.9048
0.1648
0.2049
0.426
0.481  |      |      | 
0.017
        5 
4.2765
3.9482
0.1517
0.3283
0.431
0.762  |      |*     | 
0.036
        6 
3.8267
3.8614
0.1789
-0.0346
0.420
-0.0824  |      |      | 
0.001
        7 
4.1329
3.9731
0.1448
0.1599
0.433
0.369  |      |      | 
0.008
        8 
3.7531
3.8490
0.1831
-0.0959
0.418
-0.229  |      |      | 
0.005
        9 
4.4075
4.4198
0.1553
-0.0123
0.429
-0.0287  |      |      | 
0.000
       10 
4.2689
4.4384
0.1609
-0.1695
0.427
-0.397  |      |      | 
0.011
       11 
4.6562
4.4198
0.1553
0.2364
0.429
0.551  |      |*     | 
0.020
       12 
5.2767
4.4633
0.1687
0.8134
0.424
1.917  |      |***   | 
0.290
       13 
4.7880
4.4136
0.1535
0.3744
0.430
0.871  |      |*     | 
0.048
       14 
4.2485
4.4819
0.1748
-0.2333
0.422
-0.553  |     *|      | 
0.026
       15 
4.6264
4.4508
0.1648
0.1756
0.426
0.412  |      |      | 
0.013
       16 
3.1713
4.4074
0.1517
-1.2361
0.431
-2.870  | *****|      | 
0.511
 Sum of Residuals 
0
 Sum of Squared Residuals 
2.91927
 Predicted Residual SS (PRESS) 3.74286


11:22 Monday, February 12, 2018
8
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M3
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:22 Monday, February 12, 2018
8
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M3
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=11 Param=lnAUCinf
 Number of Observations Read 16
 Number of Observations Used 16
Analysis of Variance
Source
DF Sum of
Squares
Mean
Square
F Value Pr > F
 Model 
1 1.07856 1.07856
5.61 0.0328
 Error 
14 2.69339 0.19238
 Corrected Total 15 3.77195
 Root MSE 
0.43862  R-Square 0.2859
 Dependent Mean 
4.26228  Adj R-Sq 0.2349
 Coeff Var 
10.29067    
Parameter Estimates
Variable
Label
DF Parameter
Estimate
Standard
Error
t Value Pr > |t|
95%
Confidence Limits
 Intercept Intercept
1
4.66154
0.20114
23.18
<.0001
4.23013
5.09295
 eGFR 
eGFR
1
-0.00614
0.00259
-2.37
0.0328 -0.01171 -0.00057843


11:22 Monday, February 12, 2018
9
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M3
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:22 Monday, February 12, 2018
9
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M3
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=11 Param=lnAUCinf
Output Statistics
Obs
Dependent
Variable
Predicted
Value
Std Error
Mean Predict
Residual Std Error
Residual
Student
Residual
-2-1 0 1 2
Cook's
D
        1 
3.8791
3.9552
0.1699
-0.0760
0.404
-0.188  |      |      | 
0.003
        2 
4.0457
4.0350
0.1457
0.0106
0.414
0.0257  |      |      | 
0.000
        3 
3.5965
4.0841
0.1330
-0.4877
0.418
-1.167  |    **|      | 
0.069
        4 
4.1912
3.9920
0.1583
0.1992
0.409
0.487  |      |      | 
0.018
        5 
4.3475
4.0350
0.1457
0.3125
0.414
0.755  |      |*     | 
0.035
        6 
3.9021
3.9490
0.1718
-0.0469
0.404
-0.116  |      |      | 
0.001
        7 
4.2042
4.0596
0.1391
0.1446
0.416
0.348  |      |      | 
0.007
        8 
3.9129
3.9367
0.1759
-0.0238
0.402
-0.0592  |      |      | 
0.000
        9 
4.5139
4.5018
0.1492
0.0121
0.412
0.0293  |      |      | 
0.000
       10 
4.3335
4.5203
0.1546
-0.1867
0.410
-0.455  |      |      | 
0.015
       11 
4.7974
4.5018
0.1492
0.2955
0.412
0.717  |      |*     | 
0.034
       12 
5.3133
4.5448
0.1621
0.7684
0.408
1.885  |      |***   | 
0.281
       13 
4.8426
4.4957
0.1475
0.3469
0.413
0.840  |      |*     | 
0.045
       14 
4.3258
4.5633
0.1679
-0.2374
0.405
-0.586  |     *|      | 
0.029
       15 
4.6755
4.5326
0.1583
0.1429
0.409
0.349  |      |      | 
0.009
       16 
3.3154
4.4896
0.1457
-1.1742
0.414
-2.838  | *****|      | 
0.500
 Sum of Residuals 
0
 Sum of Squared Residuals 
2.69339
 Predicted Residual SS (PRESS) 3.45084


11:22 Monday, February 12, 2018
10
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M3
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:22 Monday, February 12, 2018
10
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M3
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=12 Param=lnAe
 Number of Observations Read 16
 Number of Observations Used 16
Analysis of Variance
Source
DF
Sum of
Squares
Mean
Square
F Value Pr > F
 Model 
1
9.30262 9.30262
30.42 <.0001
 Error 
14
4.28074 0.30577
 Corrected Total 15 13.58335
 Root MSE 
0.55296  R-Square 0.6849
 Dependent Mean 
-0.68007  Adj R-Sq 0.6623
 Coeff Var 
-81.30945    
Parameter Estimates
Variable
Label
DF Parameter
Estimate
Standard
Error
t Value Pr > |t|
95%
Confidence
Limits
 Intercept Intercept
1
-1.85264
0.25358
-7.31
<.0001 -2.39652 -1.30877
 eGFR 
eGFR
1
0.01804
0.00327
5.52
<.0001
0.01102
0.02505


11:22 Monday, February 12, 2018
11
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M3
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:22 Monday, February 12, 2018
11
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M3
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=12 Param=lnAe
Output Statistics
Obs
Dependent
Variable
Predicted
Value
Std Error
Mean Predict
Residual Std Error
Residual
Student
Residual
-2-1 0 1 2
Cook's
D
        1 
0.3001
0.2219
0.2141
0.0782
0.510
0.153  |      |      | 
0.002
        2 
-0.0313
-0.0126
0.1837
-0.0187
0.522
-0.0359  |      |      | 
0.000
        3 
-0.3673
-0.1569
0.1676
-0.2104
0.527
-0.399  |      |      | 
0.008
        4 
0.0221
0.1137
0.1995
-0.0916
0.516
-0.178  |      |      | 
0.002
        5 
0.9333
-0.0126
0.1837
0.9459
0.522
1.814  |      |***   | 
0.204
        6 
-0.1374
0.2399
0.2166
-0.3773
0.509
-0.742  |     *|      | 
0.050
        7 
0.0956
-0.0848
0.1754
0.1803
0.524
0.344  |      |      | 
0.007
        8 
-0.1007
0.2760
0.2217
-0.3767
0.507
-0.744  |     *|      | 
0.053
        9 
-1.7432
-1.3836
0.1881
-0.3596
0.520
-0.691  |     *|      | 
0.031
       10 
-1.6382
-1.4377
0.1949
-0.2005
0.517
-0.387  |      |      | 
0.011
       11 
-0.8909
-1.3836
0.1881
0.4927
0.520
0.947  |      |*     | 
0.059
       12 
-0.5729
-1.5099
0.2043
0.9370
0.514
1.824  |      |***   | 
0.263
       13 
-1.1186
-1.3656
0.1859
0.2470
0.521
0.474  |      |      | 
0.014
       14 
-2.5187
-1.5640
0.2116
-0.9547
0.511
-1.869  |   ***|      | 
0.300
       15 
-1.0260
-1.4738
0.1995
0.4478
0.516
0.868  |      |*     | 
0.056
       16 
-2.0870
-1.3475
0.1837
-0.7394
0.522
-1.418  |    **|      | 
0.125
 Sum of Residuals 
0
 Sum of Squared Residuals 
4.28074
 Predicted Residual SS (PRESS) 5.63517


11:22 Monday, February 12, 2018
12
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M3
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:22 Monday, February 12, 2018
12
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M3
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=13 Param=lnLambda_z
 Number of Observations Read 16
 Number of Observations Used 16
Analysis of Variance
Source
DF Sum of
Squares
Mean
Square
F Value Pr > F
 Model 
1 0.87526 0.87526
10.89 0.0053
 Error 
14 1.12522 0.08037
 Corrected Total 15 2.00048
 Root MSE 
0.28350  R-Square 0.4375
 Dependent Mean 
-1.40673  Adj R-Sq 0.3973
 Coeff Var 
-20.15320    
Parameter Estimates
Variable
Label
DF Parameter
Estimate
Standard
Error
t Value Pr > |t|
95%
Confidence
Limits
 Intercept Intercept
1
-1.76640
0.13001
-13.59
<.0001 -2.04524 -1.48756
 eGFR 
eGFR
1
0.00553
0.00168
3.30
0.0053
0.00194
0.00913


11:22 Monday, February 12, 2018
13
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M3
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:22 Monday, February 12, 2018
13
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M3
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=13 Param=lnLambda_z
Output Statistics
Obs
Dependent
Variable
Predicted
Value
Std Error
Mean Predict
Residual Std Error
Residual
Student
Residual
-2-1 0 1 2
Cook's
D
        1 
-0.9285
-1.1301
0.1098
0.2015
0.261
0.771  |      |*     | 
0.052
        2 
-1.4215
-1.2020
0.0942
-0.2195
0.267
-0.821  |     *|      | 
0.042
        3 
-0.7726
-1.2463
0.0860
0.4737
0.270
1.753  |      |***   | 
0.156
        4 
-1.5579
-1.1633
0.1023
-0.3946
0.264
-1.493  |    **|      | 
0.167
        5 
-1.0162
-1.2020
0.0942
0.1858
0.267
0.695  |      |*     | 
0.030
        6 
-0.9613
-1.1245
0.1111
0.1632
0.261
0.626  |      |*     | 
0.035
        7 
-1.3693
-1.2241
0.0899
-0.1452
0.269
-0.540  |     *|      | 
0.016
        8 
-1.3036
-1.1135
0.1137
-0.1902
0.260
-0.732  |     *|      | 
0.051
        9 
-1.9761
-1.6225
0.0964
-0.3535
0.267
-1.326  |    **|      | 
0.115
       10 
-1.4070
-1.6391
0.0999
0.2321
0.265
0.875  |      |*     | 
0.054
       11 
-2.0382
-1.6225
0.0964
-0.4157
0.267
-1.559  |   ***|      | 
0.159
       12 
-1.5887
-1.6613
0.1048
0.0725
0.263
0.275  |      |      | 
0.006
       13 
-1.7437
-1.6170
0.0953
-0.1267
0.267
-0.474  |      |      | 
0.014
       14 
-1.5917
-1.6779
0.1085
0.0862
0.262
0.329  |      |      | 
0.009
       15 
-1.6153
-1.6502
0.1023
0.0349
0.264
0.132  |      |      | 
0.001
       16 
-1.2161
-1.6115
0.0942
0.3954
0.267
1.479  |      |**    | 
0.136
 Sum of Residuals 
0
 Sum of Squared Residuals 
1.12522
 Predicted Residual SS (PRESS) 1.44105


11:22 Monday, February 12, 2018
14
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M3
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:22 Monday, February 12, 2018
14
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M3
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=14 Param=RkTmax
 Number of Observations Read 16
 Number of Observations Used 16
Analysis of Variance
Source
DF
Sum of
Squares
Mean
Square
F Value Pr > F
 Model 
1
2.36479
2.36479
0.10 0.7560
 Error 
14 329.63521 23.54537
 Corrected Total 15 332.00000
 Root MSE 
4.85236  R-Square 
0.0071
 Dependent Mean 
8.50000  Adj R-Sq -0.0638
 Coeff Var 
57.08656    
Parameter Estimates
Variable
Label
DF Parameter
Estimate
Standard
Error
t Value Pr > |t|
95%
Confidence
Limits
 Intercept Intercept
1
7.90880
2.22522
3.55
0.0032
3.13619 12.68141
 eGFR 
eGFR
1
0.00910
0.02870
0.32
0.7560 -0.05246
0.07065


11:22 Monday, February 12, 2018
15
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M3
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:22 Monday, February 12, 2018
15
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M3
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of eGFR at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=14 Param=RkTmax
Output Statistics
Obs
Dependent
Variable
Predicted
Value
Std Error
Mean Predict
Residual Std Error
Residual
Student
Residual
-2-1 0 1 2
Cook's
D
        1 
8.5000
8.9548
1.8790
-0.4548
4.474
-0.102  |      |      | 
0.001
        2 
12.0000
8.8365
1.6122
3.1635
4.577
0.691  |      |*     | 
0.030
        3 
3.5000
8.7638
1.4712
-5.2638
4.624
-1.138  |    **|      | 
0.066
        4 
7.0000
8.9002
1.7511
-1.9002
4.525
-0.420  |      |      | 
0.013
        5 
3.5000
8.8365
1.6122
-5.3365
4.577
-1.166  |    **|      | 
0.084
        6 
12.0000
8.9639
1.9010
3.0361
4.464
0.680  |      |*     | 
0.042
        7 
14.5000
8.8001
1.5390
5.6999
4.602
1.239  |      |**    | 
0.086
        8 
8.5000
8.9821
1.9456
-0.4821
4.445
-0.108  |      |      | 
0.001
        9 
3.5000
8.1453
1.6506
-4.6453
4.563
-1.018  |    **|      | 
0.068
       10 
12.0000
8.1180
1.7101
3.8820
4.541
0.855  |      |*     | 
0.052
       11 
14.5000
8.1453
1.6506
6.3547
4.563
1.393  |      |**    | 
0.127
       12 
10.0000
8.0816
1.7929
1.9184
4.509
0.425  |      |      | 
0.014
       13 
6.0000
8.1544
1.6312
-2.1544
4.570
-0.471  |      |      | 
0.014
       14 
1.0000
8.0543
1.8572
-7.0543
4.483
-1.574  |   ***|      | 
0.213
       15 
3.5000
8.0998
1.7511
-4.5998
4.525
-1.016  |    **|      | 
0.077
       16 
16.0000
8.1635
1.6122
7.8365
4.577
1.712  |      |***   | 
0.182
 Sum of Residuals 
0
 Sum of Squared Residuals 
329.63521
 Predicted Residual SS (PRESS) 424.24351


11:22 Monday, February 12, 2018
16
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M3
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:22 Monday, February 12, 2018
16
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M3
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=9 Param=lnCmax
 Number of Observations Read 16
 Number of Observations Used 16
Analysis of Variance
Source
DF Sum of
Squares
Mean
Square
F Value Pr > F
 Model 
1 0.39512 0.39512
2.10 0.1690
 Error 
14 2.62941 0.18781
 Corrected Total 15 3.02453
 Root MSE 
0.43338  R-Square 0.1306
 Dependent Mean 
2.76685  Adj R-Sq 0.0685
 Coeff Var 
15.66315    
Parameter Estimates
Variable
Label
DF Parameter
Estimate
Standard
Error
t Value Pr > |t|
95%
Confidence
Limits
 Intercept Intercept
1
3.02188
0.20653
14.63
<.0001
2.57892 3.46485
 CrLR 
CrLR
1
-0.00298
0.00206
-1.45
0.1690 -0.00740 0.00143


11:22 Monday, February 12, 2018
17
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M3
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:22 Monday, February 12, 2018
17
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M3
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=9 Param=lnCmax
Output Statistics
Obs
Dependent
Variable
Predicted
Value
Std Error
Mean Predict
Residual Std Error
Residual
Student
Residual
-2-1 0 1 2
Cook's
D
        1 
2.6391
2.5329
0.1943
0.1061
0.387
0.274  |      |      | 
0.009
        2 
2.4336
2.5658
0.1759
-0.1322
0.396
-0.334  |      |      | 
0.011
        3 
2.6878
2.7221
0.1126
-0.0343
0.418
-0.0819  |      |      | 
0.000
        4 
2.8214
2.6508
0.1347
0.1706
0.412
0.414  |      |      | 
0.009
        5 
3.1905
2.5588
0.1798
0.6317
0.394
1.602  |      |***   | 
0.267
        6 
2.6247
2.6632
0.1298
-0.0386
0.413
-0.0933  |      |      | 
0.000
        7 
2.4765
2.6745
0.1257
-0.1980
0.415
-0.477  |      |      | 
0.010
        8 
2.3702
2.5821
0.1672
-0.2119
0.400
-0.530  |     *|      | 
0.025
        9 
2.6247
2.9022
0.1430
-0.2776
0.409
-0.679  |     *|      | 
0.028
       10 
2.8507
2.9338
0.1581
-0.0831
0.404
-0.206  |      |      | 
0.003
       11 
2.7663
2.8915
0.1383
-0.1252
0.411
-0.305  |      |      | 
0.005
       12 
3.6889
2.9317
0.1570
0.7572
0.404
1.875  |      |***   | 
0.265
       13 
3.3534
2.9416
0.1620
0.4118
0.402
1.025  |      |**    | 
0.085
       14 
2.9704
2.9614
0.1724 0.009022
0.398
0.0227  |      |      | 
0.000
       15 
3.0540
2.9314
0.1569
0.1226
0.404
0.304  |      |      | 
0.007
       16 
1.7174
2.8256
0.1157
-1.1082
0.418
-2.653  | *****|      | 
0.270
 Sum of Residuals 
0
 Sum of Squared Residuals 
2.62941
 Predicted Residual SS (PRESS) 3.33060


11:22 Monday, February 12, 2018
18
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M3
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:22 Monday, February 12, 2018
18
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M3
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=10 Param=lnAUCT
 Number of Observations Read 16
 Number of Observations Used 16
Analysis of Variance
Source
DF Sum of
Squares
Mean
Square
F Value Pr > F
 Model 
1 1.18686 1.18686
5.87 0.0296
 Error 
14 2.83305 0.20236
 Corrected Total 15 4.01991
 Root MSE 
0.44984  R-Square 0.2952
 Dependent Mean 
4.17783  Adj R-Sq 0.2449
 Coeff Var 
10.76744    
Parameter Estimates
Variable
Label
DF Parameter
Estimate
Standard
Error
t Value Pr > |t|
95%
Confidence Limits
 Intercept Intercept
1
4.61983
0.21438
21.55
<.0001
4.16004
5.07963
 CrLR 
CrLR
1
-0.00517
0.00214
-2.42
0.0296 -0.00975 -0.00059159


11:22 Monday, February 12, 2018
19
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M3
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:22 Monday, February 12, 2018
19
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M3
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=10 Param=lnAUCT
Output Statistics
Obs
Dependent
Variable
Predicted
Value
Std Error
Mean Predict
Residual Std Error
Residual
Student
Residual
-2-1 0 1 2
Cook's
D
        1 
3.8135
3.7724
0.2017
0.0411
0.402
0.102  |      |      | 
0.001
        2 
3.9711
3.8293
0.1826
0.1418
0.411
0.345  |      |      | 
0.012
        3 
3.5181
4.1003
0.1169
-0.5822
0.434
-1.340  |    **|      | 
0.065
        4 
4.1097
3.9767
0.1398
0.1330
0.428
0.311  |      |      | 
0.005
        5 
4.2765
3.8172
0.1866
0.4593
0.409
1.122  |      |**    | 
0.131
        6 
3.8267
3.9983
0.1347
-0.1715
0.429
-0.400  |      |      | 
0.008
        7 
4.1329
4.0179
0.1304
0.1151
0.431
0.267  |      |      | 
0.003
        8 
3.7531
3.8577
0.1736
-0.1046
0.415
-0.252  |      |      | 
0.006
        9 
4.4075
4.4125
0.1484 -0.004972
0.425
-0.0117  |      |      | 
0.000
       10 
4.2689
4.4672
0.1641
-0.1983
0.419
-0.473  |      |      | 
0.017
       11 
4.6562
4.3939
0.1436
0.2623
0.426
0.615  |      |*     | 
0.021
       12 
5.2767
4.4635
0.1630
0.8131
0.419
1.939  |      |***   | 
0.284
       13 
4.7880
4.4807
0.1682
0.3073
0.417
0.737  |      |*     | 
0.044
       14 
4.2485
4.5150
0.1790
-0.2665
0.413
-0.646  |     *|      | 
0.039
       15 
4.6264
4.4630
0.1628
0.1635
0.419
0.390  |      |      | 
0.011
       16 
3.1713
4.2797
0.1201
-1.1084
0.434
-2.557  | *****|      | 
0.251
 Sum of Residuals 
0
 Sum of Squared Residuals 
2.83305
 Predicted Residual SS (PRESS) 3.51836


11:22 Monday, February 12, 2018
20
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M3
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:22 Monday, February 12, 2018
20
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M3
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=11 Param=lnAUCinf
 Number of Observations Read 16
 Number of Observations Used 16
Analysis of Variance
Source
DF Sum of
Squares
Mean
Square
F Value Pr > F
 Model 
1 1.14550 1.14550
6.11 0.0269
 Error 
14 2.62645 0.18760
 Corrected Total 15 3.77195
 Root MSE 
0.43313  R-Square 0.3037
 Dependent Mean 
4.26228  Adj R-Sq 0.2540
 Coeff Var 
10.16199    
Parameter Estimates
Variable
Label
DF Parameter
Estimate
Standard
Error
t Value Pr > |t|
95%
Confidence Limits
 Intercept Intercept
1
4.69652
0.20641
22.75
<.0001
4.25380
5.13923
 CrLR 
CrLR
1
-0.00508
0.00206
-2.47
0.0269 -0.00949 -0.00067084


11:22 Monday, February 12, 2018
21
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M3
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:22 Monday, February 12, 2018
21
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M3
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=11 Param=lnAUCinf
Output Statistics
Obs
Dependent
Variable
Predicted
Value
Std Error
Mean Predict
Residual Std Error
Residual
Student
Residual
-2-1 0 1 2
Cook's
D
        1 
3.8791
3.8640
0.1942
0.0152
0.387
0.0391  |      |      | 
0.000
        2 
4.0457
3.9199
0.1758
0.1257
0.396
0.318  |      |      | 
0.010
        3 
3.5965
4.1861
0.1126
-0.5896
0.418
-1.410  |    **|      | 
0.072
        4 
4.1912
4.0647
0.1346
0.1264
0.412
0.307  |      |      | 
0.005
        5 
4.3475
3.9080
0.1797
0.4394
0.394
1.115  |      |**    | 
0.129
        6 
3.9021
4.0859
0.1297
-0.1837
0.413
-0.445  |      |      | 
0.010
        7 
4.2042
4.1051
0.1256
0.0991
0.415
0.239  |      |      | 
0.003
        8 
3.9129
3.9478
0.1671
-0.0348
0.400
-0.0872  |      |      | 
0.001
        9 
4.5139
4.4928
0.1429
0.0211
0.409
0.0516  |      |      | 
0.000
       10 
4.3335
4.5466
0.1580
-0.2130
0.403
-0.528  |     *|      | 
0.021
       11 
4.7974
4.4746
0.1382
0.3228
0.410
0.786  |      |*     | 
0.035
       12 
5.3133
4.5430
0.1569
0.7703
0.404
1.908  |      |***   | 
0.275
       13 
4.8426
4.5598
0.1619
0.2827
0.402
0.704  |      |*     | 
0.040
       14 
4.3258
4.5935
0.1723
-0.2677
0.397
-0.674  |     *|      | 
0.043
       15 
4.6755
4.5424
0.1568
0.1331
0.404
0.330  |      |      | 
0.008
       16 
3.3154
4.3623
0.1156
-1.0470
0.417
-2.508  | *****|      | 
0.241
 Sum of Residuals 
0
 Sum of Squared Residuals 
2.62645
 Predicted Residual SS (PRESS) 3.25807


11:22 Monday, February 12, 2018
22
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M3
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:22 Monday, February 12, 2018
22
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M3
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=12 Param=lnAe
 Number of Observations Read 16
 Number of Observations Used 16
Analysis of Variance
Source
DF
Sum of
Squares
Mean
Square
F Value Pr > F
 Model 
1
9.25376 9.25376
29.92 <.0001
 Error 
14
4.32960 0.30926
 Corrected Total 15 13.58335
 Root MSE 
0.55611  R-Square 0.6813
 Dependent Mean 
-0.68007  Adj R-Sq 0.6585
 Coeff Var 
-81.77213    
Parameter Estimates
Variable
Label
DF Parameter
Estimate
Standard
Error
t Value Pr > |t|
95%
Confidence
Limits
 Intercept Intercept
1
-1.91428
0.26502
-7.22
<.0001 -2.48269 -1.34587
 CrLR 
CrLR
1
0.01444
0.00264
5.47
<.0001
0.00878
0.02010


11:22 Monday, February 12, 2018
23
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M3
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:22 Monday, February 12, 2018
23
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M3
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=12 Param=lnAe
Output Statistics
Obs
Dependent
Variable
Predicted
Value
Std Error
Mean Predict
Residual Std Error
Residual
Student
Residual
-2-1 0 1 2
Cook's
D
        1 
0.3001
0.4520
0.2493
-0.1519
0.497
-0.306  |      |      | 
0.012
        2 
-0.0313
0.2930
0.2258
-0.3244
0.508
-0.638  |     *|      | 
0.040
        3 
-0.3673
-0.4636
0.1446
0.0963
0.537
0.179  |      |      | 
0.001
        4 
0.0221
-0.1186
0.1728
0.1406
0.529
0.266  |      |      | 
0.004
        5 
0.9333
0.3268
0.2307
0.6065
0.506
1.199  |      |**    | 
0.149
        6 
-0.1374
-0.1786
0.1665
0.0412
0.531
0.0777  |      |      | 
0.000
        7 
0.0956
-0.2334
0.1612
0.3290
0.532
0.618  |      |*     | 
0.018
        8 
-0.1007
0.2139
0.2146
-0.3146
0.513
-0.613  |     *|      | 
0.033
        9 
-1.7432
-1.3353
0.1835
-0.4079
0.525
-0.777  |     *|      | 
0.037
       10 
-1.6382
-1.4881
0.2029
-0.1501
0.518
-0.290  |      |      | 
0.006
       11 
-0.8909
-1.2835
0.1775
0.3925
0.527
0.745  |      |*     | 
0.031
       12 
-0.5729
-1.4778
0.2015
0.9050
0.518
1.746  |      |***   | 
0.230
       13 
-1.1186
-1.5258
0.2079
0.4072
0.516
0.790  |      |*     | 
0.051
       14 
-2.5187
-1.6215
0.2212
-0.8972
0.510
-1.759  |   ***|      | 
0.291
       15 
-1.0260
-1.4763
0.2013
0.4503
0.518
0.869  |      |*     | 
0.057
       16 
-2.0870
-0.9644
0.1484
-1.1225
0.536
-2.095  |  ****|      | 
0.168
 Sum of Residuals 
0
 Sum of Squared Residuals 
4.32960
 Predicted Residual SS (PRESS) 5.63135


11:22 Monday, February 12, 2018
24
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M3
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:22 Monday, February 12, 2018
24
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M3
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=13 Param=lnLambda_z
 Number of Observations Read 16
 Number of Observations Used 16
Analysis of Variance
Source
DF Sum of
Squares
Mean
Square
F Value Pr > F
 Model 
1 0.83237 0.83237
9.98 0.0070
 Error 
14 1.16811 0.08344
 Corrected Total 15 2.00048
 Root MSE 
0.28885  R-Square 0.4161
 Dependent Mean 
-1.40673  Adj R-Sq 0.3744
 Coeff Var 
-20.53370    
Parameter Estimates
Variable
Label
DF Parameter
Estimate
Standard
Error
t Value Pr > |t|
95%
Confidence
Limits
 Intercept Intercept
1
-1.77689
0.13766
-12.91
<.0001 -2.07213 -1.48164
 CrLR 
CrLR
1
0.00433
0.00137
3.16
0.0070
0.00139
0.00727


11:22 Monday, February 12, 2018
25
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M3
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:22 Monday, February 12, 2018
25
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M3
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=13 Param=lnLambda_z
Output Statistics
Obs
Dependent
Variable
Predicted
Value
Std Error
Mean Predict
Residual Std Error
Residual
Student
Residual
-2-1 0 1 2
Cook's
D
        1 
-0.9285
-1.0672
0.1295
0.1387
0.258
0.537  |      |*     | 
0.036
        2 
-1.4215
-1.1149
0.1173
-0.3066
0.264
-1.161  |    **|      | 
0.133
        3 
-0.7726
-1.3418
0.0751
0.5692
0.279
2.041  |      |****  | 
0.151
        4 
-1.5579
-1.2383
0.0898
-0.3195
0.275
-1.164  |    **|      | 
0.072
        5 
-1.0162
-1.1047
0.1198
0.0885
0.263
0.337  |      |      | 
0.012
        6 
-0.9613
-1.2563
0.0865
0.2950
0.276
1.070  |      |**    | 
0.056
        7 
-1.3693
-1.2728
0.0837
-0.0965
0.276
-0.349  |      |      | 
0.006
        8 
-1.3036
-1.1386
0.1114
-0.1650
0.266
-0.619  |     *|      | 
0.034
        9 
-1.9761
-1.6032
0.0953
-0.3728
0.273
-1.367  |    **|      | 
0.114
       10 
-1.4070
-1.6491
0.1054
0.2421
0.269
0.900  |      |*     | 
0.062
       11 
-2.0382
-1.5877
0.0922
-0.4505
0.274
-1.646  |   ***|      | 
0.154
       12 
-1.5887
-1.6460
0.1047
0.0573
0.269
0.213  |      |      | 
0.003
       13 
-1.7437
-1.6604
0.1080
-0.0833
0.268
-0.311  |      |      | 
0.008
       14 
-1.5917
-1.6891
0.1149
0.0974
0.265
0.367  |      |      | 
0.013
       15 
-1.6153
-1.6455
0.1045
0.0302
0.269
0.112  |      |      | 
0.001
       16 
-1.2161
-1.4920
0.0771
0.2759
0.278
0.991  |      |*     | 
0.038
 Sum of Residuals 
0
 Sum of Squared Residuals 
1.16811
 Predicted Residual SS (PRESS) 1.44904


11:22 Monday, February 12, 2018
26
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M3
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:22 Monday, February 12, 2018
26
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M3
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=14 Param=RkTmax
 Number of Observations Read 16
 Number of Observations Used 16
Analysis of Variance
Source
DF
Sum of
Squares
Mean
Square
F Value Pr > F
 Model 
1
6.13782
6.13782
0.26 0.6156
 Error 
14 325.86218 23.27587
 Corrected Total 15 332.00000
 Root MSE 
4.82451  R-Square 
0.0185
 Dependent Mean 
8.50000  Adj R-Sq -0.0516
 Coeff Var 
56.75891    
Parameter Estimates
Variable
Label
DF Parameter
Estimate
Standard
Error
t Value Pr > |t|
95%
Confidence
Limits
 Intercept Intercept
1
7.49484
2.29917
3.26
0.0057
2.56361 12.42607
 CrLR 
CrLR
1
0.01176
0.02290
0.51
0.6156 -0.03736
0.06089


11:22 Monday, February 12, 2018
27
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M3
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
11:22 Monday, February 12, 2018
27
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M3
(Healthy vs Severe)
ANOVA analysis
Regression Analysis of Cockcroft-Gault Estimate of the Creatinine Clearance at Baseline
--------------------- SUMMARY REPORT ---------------------
The REG Procedure
Model: MODEL1
Dependent Variable: Value
Order=14 Param=RkTmax
Output Statistics
Obs
Dependent
Variable
Predicted
Value
Std Error
Mean Predict
Residual Std Error
Residual
Student
Residual
-2-1 0 1 2
Cook's
D
        1 
8.5000
9.4220
2.1630
-0.9220
4.312
-0.214  |      |      | 
0.006
        2 
12.0000
9.2925
1.9587
2.7075
4.409
0.614  |      |*     | 
0.037
        3 
3.5000
8.6763
1.2540
-5.1763
4.659
-1.111  |    **|      | 
0.045
        4 
7.0000
8.9573
1.4993
-1.9573
4.586
-0.427  |      |      | 
0.010
        5 
3.5000
9.3200
2.0012
-5.8200
4.390
-1.326  |    **|      | 
0.183
        6 
12.0000
8.9084
1.4447
3.0916
4.603
0.672  |      |*     | 
0.022
        7 
14.5000
8.8638
1.3988
5.6362
4.617
1.221  |      |**    | 
0.068
        8 
8.5000
9.2281
1.8614
-0.7281
4.451
-0.164  |      |      | 
0.002
        9 
3.5000
7.9664
1.5920
-4.4664
4.554
-0.981  |     *|      | 
0.059
       10 
12.0000
7.8419
1.7598
4.1581
4.492
0.926  |      |*     | 
0.066
       11 
14.5000
8.0086
1.5396
6.4914
4.572
1.420  |      |**    | 
0.114
       12 
10.0000
7.8503
1.7480
2.1497
4.497
0.478  |      |      | 
0.017
       13 
6.0000
7.8112
1.8038
-1.8112
4.475
-0.405  |      |      | 
0.013
       14 
1.0000
7.7333
1.9194
-6.7333
4.426
-1.521  |   ***|      | 
0.218
       15 
3.5000
7.8516
1.7462
-4.3516
4.497
-0.968  |     *|      | 
0.071
       16 
16.0000
8.2684
1.2877
7.7316
4.649
1.663  |      |***   | 
0.106
 Sum of Residuals 
0
 Sum of Squared Residuals 
325.86218
 Predicted Residual SS (PRESS) 416.18300


11:22 Monday, February 12, 2018
28
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M3
(Healthy vs Severe)
ANOVA analysis
NON-PARAMETRIC TEST OF FIXED EFFECT for Tmax parameter
--------------------- SUMMARY REPORT ---------------------
The NPAR1WAY Procedure
11:22 Monday, February 12, 2018
28
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M3
(Healthy vs Severe)
ANOVA analysis
NON-PARAMETRIC TEST OF FIXED EFFECT for Tmax parameter
--------------------- SUMMARY REPORT ---------------------
The NPAR1WAY Procedure
Wilcoxon Scores (Rank Sums) for Variable Value
Classified by Variable Group
Group
N
Sum of
Scores
Expected
Under H0
Std Dev
Under H0
Mean
Score
 1 
8
69.50
68.0 9.409215 8.68750
 2 
8
66.50
68.0 9.409215 8.31250
Average scores were used for ties.
Wilcoxon Two-Sample Test
 Statistic 
69.5000
   
 Normal Approximation 
 Z 
0.1063
 One-Sided Pr >  Z 
0.4577
 Two-Sided Pr > |Z| 
0.9154
   
 t Approximation 
 One-Sided Pr >  Z 
0.4584
 Two-Sided Pr > |Z| 
0.9168
Z includes a continuity correction of 0.5.
Kruskal-Wallis Test
 Chi-Square 
0.0254
 DF 
1
 Pr > Chi-Square 
0.8733
Hodges-Lehmann Estimation
Location Shift (1 - 2)    0.0000
Type
90%
Confidence
Limits
Interval
Midpoint
Asymptotic
Standard Error
 Asymptotic (Moses) -0.5667 0.7500
0.0917
0.4002
 Exact 
-0.5000 0.7500
0.1250


10:08 Monday, January 22, 2018
1
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M3 - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
RAW DATA
--------------------- SUMMARY REPORT ---------------------
10:08 Monday, January 22, 2018
1
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M3 - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
RAW DATA
--------------------- SUMMARY REPORT ---------------------
Renal Function Group=Normal
Obs Subject
Cmax
Tmax
AUCT
Thalf
Ae
AUCinf
Res_Area Lambda_z lnCmax
lnAUCT
 1 101
14.00000 1.75000 45.30750 1.75421 1.34999 48.38157
6.35381
0.39513 2.63906 3.81347
 2 102
11.40000 2.00000 53.04500 2.87180 0.96915 57.14841
7.18026
0.24136 2.43361 3.97114
 3 103
14.70000 1.00000 33.71875 1.50087 0.69261 36.46914
7.54168
0.46183 2.68785 3.51805
 4 104
16.80000 1.58333 60.92925 3.29157 1.02231 66.09954
7.82198
0.21058 2.82138 4.10971
 5 105
24.30000 1.00000 71.99000 1.91495 2.54294 77.28180
6.84741
0.36197 3.19048 4.27653
 6 106
13.80000 2.00000 45.91250 1.81268 0.87162 49.50813
7.26270
0.38239 2.62467 3.82674
 7 107
11.90000 2.50000 62.35925 2.72587 1.10029 66.96819
6.88229
0.25428 2.47654 4.13291
 8 108
10.70000 1.75000 42.65250 2.55262 0.90420 50.04505 14.77180
0.27154 2.37024 3.75309
Obs lnAUCinf
lnAe
lnLambda_z RkTmax
eGFR
CrLR
 1 
3.87912
0.30010
-0.92853
8.5 115.00000 163.85000
 2 
4.04565 -0.03133
-1.42145
12.0 102.00000 152.84000
 3 
3.59647 -0.36729
-0.77256
3.5
94.00000 100.45000
 4 
4.19116
0.02206
-1.55788
7.0 109.00000 124.34000
 5 
4.34746
0.93332
-1.01621
3.5 102.00000 155.18000
 6 
3.90214 -0.13740
-0.96132
12.0 116.00000 120.18000
 7 
4.20422
0.09557
-1.36930
14.5
98.00000 116.39000
 8 
3.91292 -0.10071
-1.30363
8.5 118.00000 147.36000


10:08 Monday, January 22, 2018
2
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M3 - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
RAW DATA
--------------------- SUMMARY REPORT ---------------------
10:08 Monday, January 22, 2018
2
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M3 - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
RAW DATA
--------------------- SUMMARY REPORT ---------------------
Renal Function Group=Severe
Obs Subject
Cmax
Tmax
AUCT
Thalf
Ae
AUCinf
Res_Area Lambda_z lnCmax
lnAUCT
 9 013-01
17.30000 2.00000
71.44500 2.83059 0.19433
76.21265
6.25572
0.24488 2.85071 4.26893
 10 013-02
28.60000 1.50000 120.06250 3.96358 0.32675 126.79522
5.30992
0.17488 3.35341 4.78801
 11 013-03
15.90000 2.50000 105.23750 5.32130 0.41027 121.19195 13.16462
0.13026 2.76632 4.65622
 12 013-04
5.57000 2.56667
23.83792 2.33870 0.12406
27.53273 13.41972
0.29638 1.71740 3.17128
 13 013-05
19.50000 0.75000
70.00292 3.40484 0.08056
75.62775
7.43752
0.20358 2.97041 4.24854
 14 013-06
13.80000 1.00000
82.06500 5.00063 0.17496
91.27968 10.09500
0.13861 2.62467 4.40751
 15 013-07
40.00000 1.81667 195.71667 3.39472 0.56391 203.01562
3.59527
0.20418 3.68888 5.27667
 16 013-08
21.20000 1.00000 102.14750 3.48605 0.35844 107.28247
4.78640
0.19883 3.05400 4.62642
Obs lnAUCinf
lnAe
lnLambda_z RkTmax
eGFR
CrLR
 9 
4.33353 -1.63820
-1.40700
12.0 23.00000 29.51000
 10 
4.84257 -1.11858
-1.74366
6.0 27.00000 26.90000
 11 
4.79738 -0.89094
-2.03823
14.5 26.00000 43.68000
 12 
3.31538 -2.08697
-1.21611
16.0 28.00000 65.77000
 13 
4.32582 -2.51873
-1.59171
1.0 16.00000 20.27000
 14 
4.51393 -1.74318
-1.97608
3.5 26.00000 40.09000
 15 
5.31328 -0.57287
-1.58873
10.0 19.00000 30.22000
 16 
4.67547 -1.02600
-1.61528
3.5 21.00000 30.33000


10:08 Monday, January 22, 2018
3
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M3 - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
DESCRIPTIVE RESULTS (OVERALL)
--------------------- SUMMARY REPORT ---------------------
10:08 Monday, January 22, 2018
3
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M3 - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
DESCRIPTIVE RESULTS (OVERALL)
--------------------- SUMMARY REPORT ---------------------
Parameter
Renal
Function
Group
n
Min
Mean
Geometric
Mean
Median
Max
Standard
Deviation
Coefficient
of
Variation
Cmax
Normal
8 10.70000
14.70000
14.23179 13.90000
24.30000
4.35234
29.608
Cmax
Severe
8
5.57000
20.23375
17.78266 18.40000
40.00000
10.32319
51.020
Tmax
Normal
8
1.00000
1.69792
1.62445
1.75000
2.50000
0.50970
30.019
Tmax
Severe
8
0.75000
1.64167
1.50434
1.65833
2.56667
0.69591
42.390
AUCT
Normal
8 33.71875
51.98934
50.66348 49.47875
71.99000
12.48521
24.015
AUCT
Severe
8 23.83792
96.31438
83.96890 92.10625 195.71667
49.74951
51.653
Thalf
Normal
8
1.50087
2.30307
2.22520
2.23379
3.29157
0.64115
27.839
Thalf
Severe
8
2.33870
3.71755
3.59875
3.44544
5.32130
1.01576
27.323
Ae
Normal
8
0.69261
1.18164
1.09340
0.99573
2.54294
0.58197
49.252
Ae
Severe
8
0.08056
0.27916
0.23470
0.26054
0.56391
0.16404
58.763
AUCinf
Normal
8 36.46914
56.48773
55.14091 53.59673
77.28180
13.04790
23.099
AUCinf
Severe
8 27.53273 103.61726
91.34732 99.28108 203.01562
51.01128
49.230
Res_Area
Normal
8
6.35381
8.08274
7.79325
7.22148
14.77180
2.73985
33.898
Res_Area
Severe
8
3.59527
8.00802
7.24393
6.84662
13.41972
3.79397
47.377
Lambda_z
Normal
8
0.21058
0.32239
0.31150
0.31675
0.46183
0.08959
27.791
Lambda_z
Severe
8
0.13026
0.19895
0.19261
0.20121
0.29638
0.05423
27.260
lnCmax
Normal
8
2.37024
2.65548
2.63186
3.19048
0.26148
9.847
lnCmax
Severe
8
1.71740
2.87822
2.91056
3.68888
0.57909
20.120
lnAUCT
Normal
8
3.51805
3.92521
3.89894
4.27653
0.24504
6.243
lnAUCT
Severe
8
3.17128
4.43045
4.51696
5.27667
0.60693
13.699
lnAUCinf
Normal
8
3.59647
4.00989
3.97929
4.34746
0.23751
5.923
lnAUCinf
Severe
8
3.31538
4.51467
4.59470
5.31328
0.58038
12.855
lnAe
Normal
8 -0.36729
0.08929
-0.00464
0.93332
0.39131
438.252
lnAe
Severe
8 -2.51873
-1.44943
-1.37839
-0.57287
0.65909
-45.472
lnLambda_z Normal
8 -1.55788
-1.16636
-1.15992
-0.77256
0.28148
-24.133
lnLambda_z Severe
8 -2.03823
-1.64710
-1.60350
-1.21611
0.27293
-16.570
RkTmax
Normal
8
3.50000
8.68750
7.74418
8.50000
14.50000
4.00836
46.139
RkTmax
Severe
8
1.00000
8.31250
6.14992
8.00000
16.00000
5.59296
67.284


10:08 Monday, January 22, 2018
4
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M3 - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
--------------------- SUMMARY REPORT ---------------------
The Mixed Procedure
10:08 Monday, January 22, 2018
4
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M3 - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
--------------------- SUMMARY REPORT ---------------------
The Mixed Procedure
Order=1 Param=Cmax
Model Information
 Data Set 
WORK.KINDATA
 Dependent Variable 
Value
 Covariance Structure 
Variance Components
 Group Effect 
FunctionGroup
 Estimation Method 
REML
 Residual Variance Method 
None
 Fixed Effects SE Method 
Model-Based
 Degrees of Freedom Method Between-Within
Class Level Information
Class
Levels
Values
 FunctionGroup 
2 Severe Normal
Dimensions
 Covariance Parameters 
2
 Columns in X 
3
 Columns in Z 
0
 Subjects 
16
 Max Obs per Subject 
1
Number of Observations
 Number of Observations Read 
16
 Number of Observations Used 
16
 Number of Observations Not Used 
0
Iteration History
Iteration Evaluations -2 Res Log Like Criterion
      0 
1
101.83862169
      1 
1
97.16065024 0.00000000
Convergence criteria met.
Covariance Parameter Estimates
Cov Parm
Group
Estimate
 Residual FunctionGroup Severe
106.57
 Residual FunctionGroup Normal
18.9429
Fit Statistics
 -2 Res Log Likelihood 
97.2
 AIC (Smaller is Better) 
101.2
 AICC (Smaller is Better) 102.3
 BIC (Smaller is Better) 
102.7
Null Model Likelihood
Ratio Test
DF
Chi-Square Pr > ChiSq
1
4.68
0.0306
Type 3 Tests of Fixed Effects
Effect
Num
DF
Den
DF
F Value Pr > F
 FunctionGroup 
1
14
1.95 0.1841
Least Squares Means
Effect
Renal
Function
Group
Estimate Standard
Error
DF t Value Pr > |t| Alpha
Lower
Upper
 FunctionGroup Severe
20.2338
3.6498 14
5.54
<.0001
0.1 13.8053 26.6622
 FunctionGroup Normal
14.7000
1.5388 14
9.55
<.0001
0.1 11.9897 17.4103
Differences of Least Squares Means
Effect
Renal
Function
Group
Renal
Function
Group
Estimate Standard
Error
DF t Value Pr > |t| Alpha
Lower
Upper
 FunctionGroup Severe
Normal
5.5338
3.9609 14
1.40
0.1841
0.1 -1.4427 12.5102


10:08 Monday, January 22, 2018
5
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M3 - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
--------------------- SUMMARY REPORT ---------------------
The Mixed Procedure
10:08 Monday, January 22, 2018
5
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M3 - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
--------------------- SUMMARY REPORT ---------------------
The Mixed Procedure
Order=3 Param=AUCT
Model Information
 Data Set 
WORK.KINDATA
 Dependent Variable 
Value
 Covariance Structure 
Variance Components
 Group Effect 
FunctionGroup
 Estimation Method 
REML
 Residual Variance Method 
None
 Fixed Effects SE Method 
Model-Based
 Degrees of Freedom Method Between-Within
Class Level Information
Class
Levels
Values
 FunctionGroup 
2 Severe Normal
Dimensions
 Covariance Parameters 
2
 Columns in X 
3
 Columns in Z 
0
 Subjects 
16
 Max Obs per Subject 
1
Number of Observations
 Number of Observations Read 
16
 Number of Observations Used 
16
 Number of Observations Not Used 
0
Iteration History
Iteration Evaluations -2 Res Log Like Criterion
      0 
1
144.43620945
      1 
1
133.93080097 0.00000000
Convergence criteria met.
Covariance Parameter Estimates
Cov Parm
Group
Estimate
 Residual FunctionGroup Severe
2475.01
 Residual FunctionGroup Normal
155.88
Fit Statistics
 -2 Res Log Likelihood 
133.9
 AIC (Smaller is Better) 
137.9
 AICC (Smaller is Better) 139.0
 BIC (Smaller is Better) 
139.5
Null Model Likelihood
Ratio Test
DF
Chi-Square Pr > ChiSq
1
10.51
0.0012
Type 3 Tests of Fixed Effects
Effect
Num
DF
Den
DF
F Value Pr > F
 FunctionGroup 
1
14
5.97 0.0284
Least Squares Means
Effect
Renal
Function
Group
Estimate Standard
Error
DF t Value Pr > |t| Alpha
Lower
Upper
 FunctionGroup Severe
96.3144
17.5891 14
5.48
<.0001
0.1 65.3345
127.29
 FunctionGroup Normal
51.9893
4.4142 14
11.78
<.0001
0.1 44.2146 59.7641
Differences of Least Squares Means
Effect
Renal
Function
Group
Renal
Function
Group
Estimate Standard
Error
DF t Value Pr > |t| Alpha
Lower
Upper
 FunctionGroup Severe
Normal
44.3250
18.1345 14
2.44
0.0284
0.1 12.3845 76.2656


10:08 Monday, January 22, 2018
6
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M3 - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
--------------------- SUMMARY REPORT ---------------------
The Mixed Procedure
10:08 Monday, January 22, 2018
6
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M3 - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
--------------------- SUMMARY REPORT ---------------------
The Mixed Procedure
Order=6 Param=AUCinf
Model Information
 Data Set 
WORK.KINDATA
 Dependent Variable 
Value
 Covariance Structure 
Variance Components
 Group Effect 
FunctionGroup
 Estimation Method 
REML
 Residual Variance Method 
None
 Fixed Effects SE Method 
Model-Based
 Degrees of Freedom Method Between-Within
Class Level Information
Class
Levels
Values
 FunctionGroup 
2 Severe Normal
Dimensions
 Covariance Parameters 
2
 Columns in X 
3
 Columns in Z 
0
 Subjects 
16
 Max Obs per Subject 
1
Number of Observations
 Number of Observations Read 
16
 Number of Observations Used 
16
 Number of Observations Not Used 
0
Iteration History
Iteration Evaluations -2 Res Log Like Criterion
      0 
1
145.16965227
      1 
1
134.89859671 0.00000000
Convergence criteria met.
Covariance Parameter Estimates
Cov Parm
Group
Estimate
 Residual FunctionGroup Severe
2602.15
 Residual FunctionGroup Normal
170.25
Fit Statistics
 -2 Res Log Likelihood 
134.9
 AIC (Smaller is Better) 
138.9
 AICC (Smaller is Better) 140.0
 BIC (Smaller is Better) 
140.4
Null Model Likelihood
Ratio Test
DF
Chi-Square Pr > ChiSq
1
10.27
0.0014
Type 3 Tests of Fixed Effects
Effect
Num
DF
Den
DF
F Value Pr > F
 FunctionGroup 
1
14
6.41 0.0240
Least Squares Means
Effect
Renal
Function
Group
Estimate Standard
Error
DF t Value Pr > |t| Alpha
Lower
Upper
 FunctionGroup Severe
103.62
18.0352 14
5.75
<.0001
0.1 71.8517
135.38
 FunctionGroup Normal
56.4877
4.6131 14
12.24
<.0001
0.1 48.3626 64.6129
Differences of Least Squares Means
Effect
Renal
Function
Group
Renal
Function
Group
Estimate Standard
Error
DF t Value Pr > |t| Alpha
Lower
Upper
 FunctionGroup Severe
Normal
47.1295
18.6158 14
2.53
0.0240
0.1 14.3413 79.9178


10:08 Monday, January 22, 2018
7
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M3 - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
--------------------- SUMMARY REPORT ---------------------
The Mixed Procedure
10:08 Monday, January 22, 2018
7
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M3 - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
--------------------- SUMMARY REPORT ---------------------
The Mixed Procedure
Order=9 Param=lnCmax
Model Information
 Data Set 
WORK.KINDATA
 Dependent Variable 
Value
 Covariance Structure 
Variance Components
 Group Effect 
FunctionGroup
 Estimation Method 
REML
 Residual Variance Method 
None
 Fixed Effects SE Method 
Model-Based
 Degrees of Freedom Method Between-Within
Class Level Information
Class
Levels
Values
 FunctionGroup 
2 Severe Normal
Dimensions
 Covariance Parameters 
2
 Columns in X 
3
 Columns in Z 
0
 Subjects 
16
 Max Obs per Subject 
1
Number of Observations
 Number of Observations Read 
16
 Number of Observations Used 
16
 Number of Observations Not Used 
0
Iteration History
Iteration Evaluations -2 Res Log Like Criterion
      0 
1
21.48676106
      1 
1
17.46171905 0.00000000
Convergence criteria met.
Covariance Parameter Estimates
Cov Parm
Group
Estimate
 Residual FunctionGroup Severe
0.3354
 Residual FunctionGroup Normal
0.06837
Fit Statistics
 -2 Res Log Likelihood 
17.5
 AIC (Smaller is Better) 
21.5
 AICC (Smaller is Better) 
22.6
 BIC (Smaller is Better) 
23.0
Null Model Likelihood
Ratio Test
DF
Chi-Square Pr > ChiSq
1
4.03
0.0448
Type 3 Tests of Fixed Effects
Effect
Num
DF
Den
DF
F Value Pr > F
 FunctionGroup 
1
14
0.98 0.3382
Least Squares Means
Effect
Renal
Function
Group
Estimate Standard
Error
DF t Value Pr > |t| Alpha
Lower
Upper
 FunctionGroup Severe
2.8782
0.2047 14
14.06
<.0001
0.1 2.5176 3.2388
 FunctionGroup Normal
2.6555
0.09245 14
28.72
<.0001
0.1 2.4926 2.8183
Differences of Least Squares Means
Effect
Renal
Function
Group
Renal
Function
Group
Estimate Standard
Error
DF t Value Pr > |t| Alpha
Lower
Upper
 FunctionGroup Severe
Normal
0.2227
0.2246 14
0.99
0.3382
0.1 -0.1729 0.6184


10:08 Monday, January 22, 2018
8
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M3 - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
--------------------- SUMMARY REPORT ---------------------
The Mixed Procedure
10:08 Monday, January 22, 2018
8
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M3 - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
--------------------- SUMMARY REPORT ---------------------
The Mixed Procedure
Order=10 Param=lnAUCT
Model Information
 Data Set 
WORK.KINDATA
 Dependent Variable 
Value
 Covariance Structure 
Variance Components
 Group Effect 
FunctionGroup
 Estimation Method 
REML
 Residual Variance Method 
None
 Fixed Effects SE Method 
Model-Based
 Degrees of Freedom Method Between-Within
Class Level Information
Class
Levels
Values
 FunctionGroup 
2 Severe Normal
Dimensions
 Covariance Parameters 
2
 Columns in X 
3
 Columns in Z 
0
 Subjects 
16
 Max Obs per Subject 
1
Number of Observations
 Number of Observations Read 
16
 Number of Observations Used 
16
 Number of Observations Not Used 
0
Iteration History
Iteration Evaluations -2 Res Log Like Criterion
      0 
1
22.31749113
      1 
1
17.20945966 0.00000000
Convergence criteria met.
Covariance Parameter Estimates
Cov Parm
Group
Estimate
 Residual FunctionGroup Severe
0.3684
 Residual FunctionGroup Normal
0.06004
Fit Statistics
 -2 Res Log Likelihood 
17.2
 AIC (Smaller is Better) 
21.2
 AICC (Smaller is Better) 
22.3
 BIC (Smaller is Better) 
22.8
Null Model Likelihood
Ratio Test
DF
Chi-Square Pr > ChiSq
1
5.11
0.0238
Type 3 Tests of Fixed Effects
Effect
Num
DF
Den
DF
F Value Pr > F
 FunctionGroup 
1
14
4.77 0.0465
Least Squares Means
Effect
Renal
Function
Group
Estimate Standard
Error
DF t Value Pr > |t| Alpha
Lower
Upper
 FunctionGroup Severe
4.4304
0.2146 14
20.65
<.0001
0.1 4.0525 4.8084
 FunctionGroup Normal
3.9252
0.08663 14
45.31
<.0001
0.1 3.7726 4.0778
Differences of Least Squares Means
Effect
Renal
Function
Group
Renal
Function
Group
Estimate Standard
Error
DF t Value Pr > |t| Alpha
Lower
Upper
 FunctionGroup Severe
Normal
0.5052
0.2314 14
2.18
0.0465
0.1 0.09766 0.9128


10:08 Monday, January 22, 2018
9
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M3 - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
--------------------- SUMMARY REPORT ---------------------
The Mixed Procedure
10:08 Monday, January 22, 2018
9
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M3 - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
--------------------- SUMMARY REPORT ---------------------
The Mixed Procedure
Order=11 Param=lnAUCinf
Model Information
 Data Set 
WORK.KINDATA
 Dependent Variable 
Value
 Covariance Structure 
Variance Components
 Group Effect 
FunctionGroup
 Estimation Method 
REML
 Residual Variance Method 
None
 Fixed Effects SE Method 
Model-Based
 Degrees of Freedom Method Between-Within
Class Level Information
Class
Levels
Values
 FunctionGroup 
2 Severe Normal
Dimensions
 Covariance Parameters 
2
 Columns in X 
3
 Columns in Z 
0
 Subjects 
16
 Max Obs per Subject 
1
Number of Observations
 Number of Observations Read 
16
 Number of Observations Used 
16
 Number of Observations Not Used 
0
Iteration History
Iteration Evaluations -2 Res Log Like Criterion
      0 
1
21.11877396
      1 
1
16.14663386 0.00000000
Convergence criteria met.
Covariance Parameter Estimates
Cov Parm
Group
Estimate
 Residual FunctionGroup Severe
0.3368
 Residual FunctionGroup Normal
0.05641
Fit Statistics
 -2 Res Log Likelihood 
16.1
 AIC (Smaller is Better) 
20.1
 AICC (Smaller is Better) 
21.2
 BIC (Smaller is Better) 
21.7
Null Model Likelihood
Ratio Test
DF
Chi-Square Pr > ChiSq
1
4.97
0.0258
Type 3 Tests of Fixed Effects
Effect
Num
DF
Den
DF
F Value Pr > F
 FunctionGroup 
1
14
5.18 0.0390
Least Squares Means
Effect
Renal
Function
Group
Estimate Standard
Error
DF t Value Pr > |t| Alpha
Lower
Upper
 FunctionGroup Severe
4.5147
0.2052 14
22.00
<.0001
0.1 4.1533 4.8761
 FunctionGroup Normal
4.0099
0.08397 14
47.75
<.0001
0.1 3.8620 4.1578
Differences of Least Squares Means
Effect
Renal
Function
Group
Renal
Function
Group
Estimate Standard
Error
DF t Value Pr > |t| Alpha
Lower
Upper
 FunctionGroup Severe
Normal
0.5048
0.2217 14
2.28
0.0390
0.1 0.1143 0.8953


10:08 Monday, January 22, 2018
10
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M3 - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
--------------------- SUMMARY REPORT ---------------------
The Mixed Procedure
10:08 Monday, January 22, 2018
10
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M3 - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
--------------------- SUMMARY REPORT ---------------------
The Mixed Procedure
Order=14 Param=RkTmax
Model Information
 Data Set 
WORK.KINDATA
 Dependent Variable 
Value
 Covariance Structure 
Variance Components
 Group Effect 
FunctionGroup
 Estimation Method 
REML
 Residual Variance Method 
None
 Fixed Effects SE Method 
Model-Based
 Degrees of Freedom Method Between-Within
Class Level Information
Class
Levels
Values
 FunctionGroup 
2 Severe Normal
Dimensions
 Covariance Parameters 
2
 Columns in X 
3
 Columns in Z 
0
 Subjects 
16
 Max Obs per Subject 
1
Number of Observations
 Number of Observations Read 
16
 Number of Observations Used 
16
 Number of Observations Not Used 
0
Iteration History
Iteration Evaluations -2 Res Log Like Criterion
      0 
1
88.19050897
      1 
1
87.42765094 0.00000000
Convergence criteria met.
Covariance Parameter Estimates
Cov Parm
Group
Estimate
 Residual FunctionGroup Severe
31.2813
 Residual FunctionGroup Normal
16.0670
Fit Statistics
 -2 Res Log Likelihood 
87.4
 AIC (Smaller is Better) 
91.4
 AICC (Smaller is Better) 
92.5
 BIC (Smaller is Better) 
93.0
Null Model Likelihood
Ratio Test
DF
Chi-Square Pr > ChiSq
1
0.76
0.3824
Type 3 Tests of Fixed Effects
Effect
Num
DF
Den
DF
F Value Pr > F
 FunctionGroup 
1
14
0.02 0.8797
Least Squares Means
Effect
Renal
Function
Group
Estimate Standard
Error
DF t Value Pr > |t| Alpha
Lower
Upper
 FunctionGroup Severe
8.3125
1.9774 14
4.20
0.0009
0.1 4.8297 11.7953
 FunctionGroup Normal
8.6875
1.4172 14
6.13
<.0001
0.1 6.1914 11.1836
Differences of Least Squares Means
Effect
Renal
Function
Group
Renal
Function
Group
Estimate Standard
Error
DF t Value Pr > |t| Alpha
Lower
Upper
 FunctionGroup Severe
Normal
-0.3750
2.4328 14
-0.15
0.8797
0.1 -4.6599 3.9099


10:08 Monday, January 22, 2018
11
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M3 - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
Geometric LSmeans
--------------------- SUMMARY REPORT ---------------------
10:08 Monday, January 22, 2018
11
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M3 - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
Geometric LSmeans
--------------------- SUMMARY REPORT ---------------------
Obs Parameters Group GeoLSmeans
 1 lnCmax
Severe
17.7827
 2 lnCmax
Normal
14.2318
 3 lnAUCT
Severe
83.9689
 4 lnAUCT
Normal
50.6635
 5 lnAUCinf
Severe
91.3473
 6 lnAUCinf
Normal
55.1409


10:08 Monday, January 22, 2018
12
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M3 - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
RATIO ESTIMATE BASED ON ln-TRANSFORMED PARAMETERS
--------------------- SUMMARY REPORT ---------------------
10:08 Monday, January 22, 2018
12
--------------------- SUMMARY REPORT ---------------------
Algorithme Pharma
CUD-P4-001: Effect of Renal Impairment on Pharmacokinetics of Lasmiditan - M3 - Additional Analysis
(Healthy vs Severe)
ANOVA analysis
RATIO ESTIMATE BASED ON ln-TRANSFORMED PARAMETERS
--------------------- SUMMARY REPORT ---------------------
Obs Parameters Group
vs
Group
Ratio
(%)
L90
U90
 1 lnCmax
Severe Normal 124.950
84.120 185.599
 2 lnAUCT
Severe Normal 165.739 110.258 249.135
 3 lnAUCinf
Severe Normal 165.662 112.106 244.802