MEMORANDUM 

Date: August 30, 2012 

TXR No. 0056440 

SUBJECT: Propoxur: Review of Acute Comparative Cholinesterase Assay (CCA) Studies, 

Benchmark Dose Analysis and Derivation of Acute Point of Departure (POD) 

DP Barcode: D401491/ D404194 

Registration No.: NA 

PC Code: 047802 

Decision No.: 464412 

Petition No.: NA 

Risk Assessment Type: NA 

TXR No.: 0056440 

Regulatory Action: Generic Data Call In 

Case No.: NA 

MRID No.: 48784801,48784802,48784803, 

48784804 

CAS No.: NA 

40CFR:NA 

FROM: Deborah Smegal, MPH, Toxicologist C\ J.YI... J--(__ c:J(__ Registration Action Branch 6 (RAB6) (})' 

Health Effects Division (7509P) 

THROUGH: Felicia Fort, Branch Chief . f/1 (l --1_ _ 

Health 

Registration 

Effects 

Action 

Division 

Branch 

(7509P) 

6 (RAB~C1 ~­ TO: Kaitlin Keller, Chemical Review Manager (CRM) 

Risk Management and Implementation Branch 3 

Pesticide Reevaluation Division (PRD) (7508P) 

I. CONCLUSIONS 

The series of non-guideline cholinesterase (ChE) inhibition studies are acceptable and satisfy the 

generic data call-in (DCI) requirement for propoxur for a comparative cholinesterase assay 

(CCA) study in adult rats versus postnatal day (PND) 11 pups. 

Page 1 of2 \ 
y

p

p

and calculated a BMD10 (Benchmark Dose for 10% inhibition) as 0.0427 mg/kg/day and the 

BMDL10 (i.e. 95% Lower Bound Confidence Limits on the BMDlO) was estimated as 0.0285 

mg/kg/day. OPP has concluded that the use of a BMDL10 of 0.0285 mg/kg/day will provide a 

health-protective and scientifically supportable approach for an acute POD. 

Based on a comparison of BMD 1 Os, pups were approximately 11 fold more sensitive than the 

adult rats for brain and RBC cholinesterase inhibition (combined sex data). 

II. ACTION REQUESTED 

Review the series of non-guideline comparative cholinesterase (ChE) assay studies (MRID 

48784801-48784803) that were submitted as required by the registration review Data Call In 

(DC I). 

III. BACKGROUND 

A series of non-guideline cholinesterase (ChE) inhibition studies (MRID 48784801-48784803) 

were undertaken to evaluate any differences between postnatal day 11 (PND 11) pups and adult 

rats (approximately 7-8 weeks of age) with regard to cholinesterase inhibition for propoxur. 

These studies are acceptable and satisfy the generic DCI requirement for propoxur for a CCA 

study in adult rats versus postnatal day (PND) 11 pups. Consistent with then-methyl carbamates 

mode of action (MOA), these studies evaluated cholinesterase inhibition following a single dose 

at the time of peak effect. Both the range finding and definitive studies provide good doseresponse data. The definitive study used doses from 0.1 to 1 mg/kg, while the range finding 

study uses doses from 1 to 10 mg/kg in adults and 0.3 to 3 mg/kg in pups. 

IV. RESULTS/DISCUSSION (or MRID Summary Table, etc.) 

MRIDS ummary T a e bl E xamp1e I 

Study Type MRID Comments 

Non-Guideline Acute Time Course Study 48784801 NewDER 

Non-Guideline Acute Dose Range 48784802 NewDER 

Finding Study 

Non-Guideline Acute Dose-Response 48784803 NewDER 

Study 

Non-Guideline Study, Estimation of 48784804 Considered in EPA Benchmark 

Benchmark Dose for Propoxur Dose Analysis 

Page2 of2 
! DATAEVALUATIONRECORD ~ STUDY TYPE: ;Non-guideline; Effects on Brain and RBC Cholinesterase in Adult and Juvenile 

!Rats 

PC CODE: 047802 

I DP BARCODE: D401491 

TEST MATERIAL (PURITY): Propoxur (98.6% a.i.) 

SYNONYMS: 

CITATION: I • Tqot, J.D. (2012). A Dose-Response Study of Red Blood Cell and Bram 

Cl1.olinesterase in Juvenile Rats following Oral (Gavage) Administration of 

Prbpoxur WIL Research Laboratories, LLC, Ashland, OH. Laboratory Project 

ID: WIL-551 010, March 9, 2012. MRID 48784803. Unpublished. 

Toot, J.D. (2011). A Time Course Study ofthe Effects ofPropoxur on Red Blood 

Ceil and Brain Cholinesterase in Adult and Juvenile Rats Following Oral 

(G:~vage) Administration. WIL Research Laboratories, LLC, Ashland, OH. 

Laboratory Project ID: WIL-551008, November 21, 2011. MRID 48784801. 

un:published. 

Toot, J.D (2012). A Dose-Range Finding Study of the Effects ofPropoxur on Red 

Blood Cell and Brain Cholinesterase in Adult and Juvenile Rats Following Oral 

(Gavage) Administration. WIL Research Laboratories, LLC, Ashland, OH. I • Laboratory ProJect ID: WIL-551009, March 5, 2012. MRID 48784802. 

Unpublished. 

'I 

SPONSOR: Wellmark International, Schaumburg, IL and Bayer HealthCare, Shawnee 

~ission, KS 

. 

:i 

EXECUTIVE SUMMARY - This series of non-guideline cholinesterase (ChE) inhiqition studies (MRID 48784801-48784803) was undertaken to evaluate any differences between 

postnatal day 11 (PND 11) pups and adult rats (approximately 7-8 weeks of age) with rega,d to 

cholinesterase 

bition. 1 

I 

. 

Time-Course Stu~y (MRID 48784801): The study was divided into 3 phases (Phase I, Phase II 

and Phase III). Pmpoxur (98.6% a.i.; Lot#: 1104080407) in com oil was administered once via 

gavage (5 mL!kg) adult male or PND 11 male pups to determine the time of peak cholinesterase 

inhibition. Dos~g was as follows: (1) Phase I dosing was to 40 adult Crl: CD (SD) rats at a :~ J 

·I 
tremors were noted for 12/40 males receiving 3 mglkg, while no treatment-related clinical 

fmdings were noted in adult males in Phase I or PND 11 male pups in Phase II. Maximal RBC 

(63%) and brain (46%) inhibition was observed at 15 minutes at 5 mg/kg in males. In the 

PND 11 male pup, maximal RBC (74%) and brain (64%) inhibition was observed at 30 minutes 

at 3 mglkg. However, RBC and whole brain cholinesterase activity in 3.0 mglkg group 

increased from 0.5- to 4-hours post-dosing (106% and 83%, respectively, at 4 hours), providing 

evidence of partial recovery in brain. Overall results from the doses evaluated,in the time course 

study suggest that the time of peak inhibition occurred slightly faster in adults: (15 minutes) than 

in PND11 pups (30 minutes), but the PND11 pups took longer to recover. Based on the results 

of this time-course study, 15 minutes and 30 minutes were selected as the time of peak 

cholinesterase determination in the defmitive dose-response study for adults and PND 11 pups, 

respectively. Following acute oral exposure to propoxur, brain weights were comparable among 

the groups in both age groups. ' 

Dose Range-Finding Study (MRID 48784802): This study was performed to determine the dose 

levels for use in the definitive dose-response study (MRID 48784803). Adult

1 

Crl: CD (SD) rats 

8 weeks of age (1, 2, 3, 5, or 10 mglkg) and PND 11 pups (0.3, 0.5, 1, 2, 1or 3 mglkg) were 

administered single doses of propoxur in com oil 5 ml/kg via gavage (6/sexldose for both age 

groups). At 15 and 30 minutes post dose for adults and pups, respectively cholinesterase activity 

was assessed in the RBC and brain compartments. 

Results: No test substance-related clinical signs were observed in the adult rats at time of dosing 

(clinical signs were not recorded in pups due to technician error). A dose-related reduction in ChE activity (both compartments) was observed at all dose levels in both sexes and age groups. 

In adult rats, mean RBC cholinesterase inhibition (ChEI) ranged from 15% to 84%, while mean 

whole brain ChEI ranged from 3% to 53%. In PND 11 pups, mean RBC ChEI ranged from 36% 

to 82%, while mean whole brain ChEI ranged from 22% to 64%. At the common dose of 1.0 

mg/kg, RBC cholinesterase was reduced 15-16% in the adult rats compared to 57-58% in the 

PND 11 pups. Since significant ChE inhibition was observed at the lowest dose in PND11 pups, 

dosage levels of0.1, 0.3, and 1.0 mglkg were selected to further elucidate ChE inhibition at low 

doses for benchmark analyses in the definitive dose-response study. Brain weights were comparable among the groups in both age groups and sexes. 

Dose-Response Study in Pups (MRID48784803): In the defmitive dose response study, propoxur 

(98.6% a.i.; Lot#: 1104080407) was administered once via gavage in com oil (5 mllkg) to 11 

PND II pups/sex/dose at dose levels ofO, 0.1, 0.3, or 1.0 mg/kg. Adults were not evaluated 
RBC Cholinesterase Results. As suggested in the dose range-finding study, PND 11 pups were 

more sensitive than the adult rats based on a comparison of RBC cholinesterase inhibition. In 

the PND 11 pups, both sexes displayed a dose-related reduction in RBC cholinesterase activity, 

with females being more sensitive than males. The magnitude of RBC inhibition being 33-49% 

at 0.3 mg/kg and ~4-66% at the highest dose tested (1.0 mglkg) in both male and female PND11 

pups. At 0.1 mg/kg (lowest dose tested), 31% RBC cholinesterase inhibition was observed in the 

female and 12% in male PND 11 pups. 

Brain Cholinesterase. PND 11 pups were more sensitive than the adult rats, based on a 

comparison of brain ChE inhibition. Brain ChE activity was decreased at all doses in the PND 

11 pups (both sexes). The magnitude of the decrease was 7.7% (M) and 8% (F) at 0.1 mg/kg, 

23% (M) and-31% (F) at 0.3 mg/kg, and 55% (M) and 48%(F) at 1.0 mg/kg in the PND11 pups 

(both sexes). 

HED conducted BMD analyses on the propoxur comparative cholinesterase data (CCA) for both 

adults (MRID 48784802) and PND 11 pups (MRID 48784803) for both RBC and brain 

compartments. In additiofl, HED considered the registrant's submitted benchmark dose (BMD) 

analysis of the cholinesterase findings (Mihlan and Sheets (2012). Estimation of Benchmark 

Dose for Propoxur Based on RBC Cholinesterase Activity in Post-Natal Day 11 and Adult Rats; 

MRID 48784804). HED was able to reproduce most of the registrant's BMD analyses for the 

male and females. In addition, HED evaluated the male and female pup RBC data from the dose 

response study to see if it was appropriate to combine these data for BMD analysis. Although 

the statistical tests that show a borderline significant difference in these datasets (p=0.067), HED 

concluded that th~se datasets can be combined to provide more robust ChE measures as there is 

no biological basis to support sex-differences for PND 11 pups, and the observed difference is 

likely due to vari~bility in the RBC ChE measurements. Details of Agency's BMD analysis are 

presented in a separate BMD memo (D404194 memo from J. Liccione/ B.Sarkar August 2012 

TXR 0056440 ' 

These studies are classified as acceptable/non-guideline. These studies do not satisfy a 

guideline requirep1ent for propoxur. They satisfy the generic data call-in requirement for 

propoxur for a comparative cholinesterase study in adult rats versus postnatal day (PND) 11 

pups. 1 

COMPLIANCE i- Signed and dated Data Confidentiality, GLP Compliance, Flagging, and 

Quality Assuranc~ statements were provided. 

I 
Purity (w/w): 

Stability: 

CAS#: 

Structure: 

2. Vehicle - com oil 

3. Test animals 

Species: 

Strain: 

98.6-98.5% a.i. 

Expiration date: April26, 2012; WIL ID # 1100A4 

114-26-1 

Rat 

Crl:CD(SD) 

Adult age/weight at study 

initiation: 

adult rats 5-6 weeks at receipt; time-mated dams received on GD 10, 11 or 12 

(#551008: GD 10; #551009: GD 11 or 12); used to supply PND 11 pups; 

selected adults :::17-8 weeks old; body weights:#551008 Phase I 8 week males 

244-303g; #551009 7 week males: 206-267g and females: 151-195g. 

Pup Age/weight at dosing: 

Source: 

Housing: 

Diet: 

Water: 

Environmental conditions: 

Temperature: 

Humidity: 

Air changes: 

Photoperiod: 

Acclimation period: 

11 days old; males: 18.8-28.6g; #551009 Phase II 20.9-28.9g males and 19-

27.2g females; #551108 Phase II males 21-28 g; Phase III males 19-27 g 

Charles River Laboratories, Inc. (Raleigh, NC) 

Each dam was housed with her litter in a nesting box during the post-natal 

period. Adults were individually housed in stainless steel, wire bottomed 

cages. 

Certified Rodent Diet #5002 (PMI Nutrition International, LLC.), ad libitum 

Reverse osmosis treated (on-site) drinking water, ad libitum 

22±3°C 

50±20% 

10/hr 

12 hrs dark/12 hrs light 

Adults, 16-14 days; pups 0-1 days 
definitive dose response study in PND11 pups (MRID48784803) with regard to inhibition of red 

blood cell (RBC) and brain ChE. The adult ChE data in the range-fmding study (n=6/sex/dose) 

were determined to be adequate by EPA (email from M. Mizens to K. Keller summarizing 

conclusions of Dose-Response Conference call on 10.25.11), and thus only additional pup data 

were collected in the definitive dose-response study (MRID 48784803). 

2. In-life dates- MRID 48784801: WIL 551008: Phase 1 Start: May 10, 2011; End: May 24, 

2011; Phase II Start: May 24, 2011; End: June 16, 2011; Phase III Start: June 

7, 2011; End: June 30, 2011 

MRID 48784802: WIL 551009: Phase 1 Start: August 16, 2011 ; End: 

September 1-2, 2011; Phase II Start: August 30, 2011; End: September 21, 

2011 

MRID 48784803: WIL 551010: Start: December 12, 2011 End: December 14, 

2011 

3. Animal assignment and treatment -Dose Range Finding Study (MRID 48784802). 

Phase I (adult rats): There were 5 propoxur-treated groups and one control group, each 

consisting of 6 adult rats/sex/group (Table 1). After randomization (based on body weight 

stratification randomized in a block design), these rats were randomized into 2 study replicates to 

allow for the reasonable conduct of cholinesterase assessments. Each dose group and sex was 

~qually represented within each study replicate. Phase II (PND 11 pups): Pups were randomly 

assigned to one of 5 treatment groups and one control group; such that no more than 1 

pup/sex/litter was assigned to each treatment group; each group consisted of 11 pups/sex/dose. 

Each dose group and sex was equally represented within each study replicate for dose 

administration. Adults and pups (on PND 11) received a single gavage dose at a volume of 5 

mL/kg body weight. 

Study design: Table 1 shows the objectives and treatment groups allocated for the three studies. 
Time Course Phase III (PND 11 point toxicity in PND 11 pups; 

Study pups): 0, 3 Controls: 8 adult (Phase I) and 9 PND 11 pups (Phase III) terminated Phase II (PND at 0.25 and 4 hrs, 

11 ): 12 males 8 adults (Phase 1) and 8 PND 11 pups (Phase III) terminated at 0.25, 

treated and 3 0.5, 1, 2, and 4 hrs post dosing. 

control males 

Phase III 

(PND 11): 8 

males/ /time 

point and 17 

control males 

48784802 Phase I (adult): 0, 1, 6/sex Determine dose levels (dose-range fmding) for the inhibition ofRBC 

WIL-551009 2, 3, 5, 10 and brain cholinesterase following a single oral dose in adults (Phase Phase II (PND 11 I) and PND 11 (Phase II) rats. 

Toot2012 pups): 0, 0.3, 0.5, 1, 2 Single oral dose; clinical observations at approximately 15 and 30 

Dose Range and3 min post-dose for adults and PND 11 pups, respectively; 

Finding cholinesterase activity (brain and RBC) evaluated within 1 hour postStudy dose (termination) and sample collection. 

48784803 PND 11 pups: 0.1, Determine the dose-response for inhibition ofRBC and brain 

WIL 0.3, 1 11pupsl cholinesterase in PND 11 (Phase II) male and female rats. Single oral 

551010 sex/dose dose: PND 11 pups at 30 minutes post dose. 

Toot2012 

DoseResponse 

Study in 

Pups 

PND = postnatal day 

4. Dose selection and sampling time rationale; The dose levels and sampling times selected 

for the dose-response study in pups (MRID 48784803) were based on the results of the two 

studies, described below (a, b). Propoxur was administered once via gavage (5 mllkg) to 11 

PND 11 pups/sex/dose at dose levels of 0, 0.1, 0.3, 1.0 mg/kg in the definitive dose-response 

study (MRID 48784803). 
(Tables 2 and 3). All animals (both age groups) survived to scheduled sacrifice. In Phase III, 

tremors were noted in 12/40 males in the 3 mg/kg group. No substance-related clinical signs 

were noted in adults (Phase I) or the pups in Phase II. In the adult male rats, maximal RBC and 

brain inhibition was present at 15 minutes post dosing (63 and 46%, respectively) to 5 mg/kg. PND 11 male pups displayed a maximal RBC and brain inhibition response at 30 minutes at 3 

mg!kg (74% and 64%, respectively). Regarding the time to peak effect, time points of 30 

minutes and 15 minutes were selected for the PND 11 pups and adult rats, respectively, for the 

definitive dose-response study (MRID48784803; WIL 551010). 

a) Dose selection rationale for time to peak effect study - Dose levels were selected by the Sponsor based on the results of previous studies (Toot,2011, WLL-551008 MRID 48784801 and 

Toot, 2012, WIL-551009 MRlD 48784802). In the time course study (Toot, 2011, WLL551 008), inhibition of RBC and whole brain cholinesterase activity in PND 11 males was 

observed in the 3.0 mg!kg group, with peak inhibition noted at 0.5 hours following dose 

administration. However, RBC and whole brain cholinesterase activity in the 3.0 mg/kg group increased (106.0% and 83.0%, respectively) from 0.5- to 4-hours post-dosing, providing evidence 

of partial recovery. In the dose range-finding study (Toot, 2012, WIL-551009), administration of 

the test substance at doses of 0.3, 0.5, 1.0, 2.0, and 3.0 mg/kg to PND II pups resulted in a doserelated, statistically significant, reduction in ChE activity in both the brain and RBC 

compartments at all dose levels in both sexes and age groups (Tables 4 and 5). 

The PND 11 pups showed a greater reduction in RBC cholinesterase activity at 1 mg/kg 

(males/females 57% ChEI) than the adult rats (males 14% ChEI/females 16% ChEI) at the same 

dose level. Also at 1 mg!kg, PND 11 pups (both sexes) displayed a greater reduction in brain 

cholinesterase activity ( 42-4 7% ChEI) than the adult rats (3-1 0% ChEI). In pups, RBC 

inhibition ranged from 36% to 78% in males and from 38% to 82% in females, while whole 

brain cholinesterase ranged from 22% to 61% in males and from 25% to 64% in females at 0.5 

hours following dose administration. 
15 0 6327±920 (adjusted for - outlier) 

3 3288±2595 (a) 48* 

30 0 - -

3 1639±279 (a) . 74** 

60 01,; --

3 2527±1342 (a) 60** 

120 0 -

3 2251±1231 (adjusted) i(b) 64** 

240 0 4780±993 -

3 3375±1246 29.4* 

a Data were obtained from Table S 1 0 (pages 66-68) of the study report. 

n = 8, except where noted; (a) n=7, (b) n=5 

* p~0.05; ** p~0.01 

24230±1150 -

14345±5489 (a) 40.8** 

- -

8762±1424 63.8** 

-- -

9659±957 60** 

- -

13820±5098 43* 

24097±1039.6 -

16020±2426 33.8** 

Table 3. Time Course Study (MRID48784801; WIL551008). Mean (±SD) Cholinesterase Activity in Male Adult 

Rats Administered Propoxur via Gavage (acute). 

Time post-dose Dose Red Blood Cells Brain 

(minutes) (mg/kg) Cholinesterase (UIL) % inhibition Cholinesterase % inhibition 

(UIL) 

/' .... ~~ - .;: , .. .. -· Males ·~ .. , ~ .~.r .c. 

15 0 3150±530 49994±1008 

5 1175±471** 62.7** 27084±5859** 45.8** 

30 0 -

5 1901±419 40* 30966±2599 38* 

60 0 -

5 2572±403 18.3* 36666±2459 26.6* 

120 0 -

5 3093±635 2 43835±1989 12.3 

240 0 3482±379 50118±1782 

5 3467±332 0.4 47978±2392 4.3 

a Data were obtained from Table S5 (pages 58-60) of the study report. n = 8; * p~0.05; ** pS:O.Ol 
Table 4. Study_ Design and Results (RBC) of Range-Finding Study (MRID48784802; WIL 5 51009) 

Dose #of RBC Cholinesterase (U/L) Sample Time 

(mg/kg) rats/sex Males Females (minutes post- dosing) 

Adults 

0 6 2928±1187.6 3220±894 15 

1 6 2499±468!14.7% 2697±728 t 16% 15 

2 6 2061±792 !29.6% 2158±630* !33% 15 

3 6 1701±934* !41.9.7% 1515±645** !53% 15 

5 6 1453±408* !50.4% 1246±427** !61% 15 

10 6 1120±636** !61.7% 485±239** !85% 15 

PND 11 Pups 

0 6 7657±1187 7158±884 30 

0.3 5 4902±683** !36% 4444±879** !37.9% 30 

5 4459±1062** 4124±1001** 30 0.5 !41.8% !42.4% 

1 6 3259±573** !57.4% 3029±900** !57.7% 30 

2 4 2470±749** !67.7% 1302±294** !81.8% 30 

3 5 1726±328** !77.5% 1547±604** t 78.4% 30 

a Data obtained from Table S9 and S10 (pages 52-53) and Table S15 and S16 (pages 62-63) of the study report. 

* 

p~0.05; mean± s.d. 

** 

p~0.01; mean± s.d. 

Table 5. Study Design and Results (Brain) of Range-Finding Study (MRID48784802; WIL 551009) 

Brain Cholinesterase (UIL) Sample Time 

Dose #of Males Females (minutes post-

(mglkg) rats/sex dosing) 

Adults 

0 6 52184±1887.5 51558±1322 15 

1 6 50600±2619!3% 46481±2540 !9.8% 15 

6 43686±2300 42136±5139 U8.3% 15 2 * !16.3% 

6 41315±3712* 34790±2268** !32% 15 3 !20.8% \\ 
0 6 

0.3 

6 

0.5 

6 

1 

6 

2 

6 

3 

6 

PNDllPups 

23640±1983 24486±812 30 

18456±2756** 18378±2164** 30 

L21.9% L24.9% 

16627±2221** 15268±2395** 30 

L29.7% L37.6% 

13719±3004** 12856±1936** 30 

L42% L47.5% 

10073±1541 ** 10058±3756** 30 

L57.4% L58.9% 

9149±2023** 8683±1743** 30 

L61.3% t64.5% 

a Data obtained from Table S9 and S10 (pages 52-53) and Table SIS and S16 (pages 62-63) of the 

study report. 

* mean± s.d. 

** mean± s.d. 

5. Test substance preparation and analysis -The dose formulations were prepared once as 

single formulations for each dose divided into aliquots for dispensation, and stored 

refrigerated. The dose formulations were stirred continuously throughout use. 

Results: 

Homogeneity analysis: The dosing formulations were inspected visually and were found to be 

visibly homogeneous and acceptable for administration. Homogeneity analyses in MRID 

48784803 showed mean % of target to be 91.7%-99.4% for formulations of 0.02, and 0.2 

mg/mL. Homogeneity analyses in MRID 48784802 showed mean% of target to be 95.7%-

111% for formulations of 0.06, and 0.2 mg/mL. 

Stability analysis: In the dose-response study (MRID 48784803), formulations of 0.02, and 0.2 

mg/mL were 101%, and 97.1 %, respectively, of the mean % of time zero after storage 

(refrigeration) for 7 days. 

Concentration analysis: In the dose-response study (MRID 48784803), the dosing formulations 

were within the testing laboratories standard operating procedures range for suspensions (85% to 

115%) and were within the protocol requirement for concentration acceptability (90% to 110% 

of target) except for initial 0.02 mg/L formulation that was 157% of target concentration, and 

was not administered to animals. The 0.02 mg/L dose level was reformulated to be 95.6% of the 

target concentration. In the range fmding study (MRID 48784802) concentration analyses had 

mean % of target of 97.5%-107% and were within WIL Research Standard Operating Procedure 
Time to peak effect (MRID 48784801) Dose Range Finding Study (MRID 48784802): and dose response (MRID 48784803) studies - All statistical tests were performed using appropriate computing devices or programs. Analyses were conducted using two-tailed tests (except as noted otherwise) for minimum significance levels of 1% and 5%, comparing each test substancetreated group to the control group by sex. Each mean was presented with the standard deviation 

(S.D.), standard error (S.E.), and the number of animals (N) used to cal~ulate the mean. Due to 

the use of significant figures and the different rounding conventions inherent in the types of software used, the means, standard deviations, and/or standard errors on the summary and individual tables may differ slightly. RBC and whole-brain cholinesterase data were subjected to 

a parametric one-way ANOV A (Snedecor and Cochran, 1980) to determine intergroup differences between the control and test substance-treated groups. Ifthe ANOVA revealed 

significant (p<0.05) intergroup variance, Dunnett's test (Dunnett, 1964) was used to compare the 

test substance-treated groups to the control group. Intergroup comparative statistics were not conducted for body weight and brain weight data. 

C. METHODS 

1. Observations - Dose-Response Study (MRID 48784803) (Pup data) and Dose Range Finding Study (MRID 48784802) (Adult data) 

a. Adults - All adult rats, including dams of offspring, were observed at least twice daily for mortality and moribundity. Clinical examinations were performed prior to dosing, ::::20 minutes following dose administration, and immediately prior to sacrifice (::::5-10 and 20-25 minutes post dose for Phases I and II, respectively). 

b. Pups -Pups were sexed on PND 0, 4, 7, and 10. Pretest body weights and detailed physical examinations for each pup were recorded on PND 1, 4, 7, and 10. To reduce variability, litters 

were culled to 10 pups/litter, 5/sex when possible, on PND 4 using a computerized randomization procedure. 

2. Body weight - Body weights of all adult rats and PND 11 pups were recorded initially and used as the basis of randomization into dose groups. Additionally, all rats were weighed on the day of dose administration to determine individual doses. 

3. Cholinesterase activity determination - Blood samples and whole brains were collected 

from each pup at approximately 30 minutes (Dose-Response Study MRID 48784803), and each adult at approximately 15 minutes (Range-Finding Study MRID 48784802) following dose administration for determination of cholinesterase activities as follows. PND 11 pups in the dose ) ']__ 

response study were anesthetized with isoflurane and euthanized by exsanguination during the J 
diluted 1: 10 ( w:v) using 1% Triton X -100 solution (unbuffered) and homogenized. The 

homogenate was centrifuged for minutes 4°C, and the supernatant was analyzed. RBC 

and whole brain cholinesterase activities were determined using an assay based on a 

modification (Hunter et al., 1997) of the Ellman reaction (Ellman et al., 1961), which uses 

acetylthiocholine as a substrate to measure total cholinesterase (i.e., the assay is not specific to acetylcholinesterase) via a photometric period (WIL SOP No. T5-146-2, dated 9/12/2006). To 

prevent reactivation of the enzyme, all samples were maintained in an ice-water bath from the 

point of collection until analysis for cholinesterase activity. The time of each blood sample and 

brain collection was recorded and samples were analyzed within 1 hour of sample collection, 

based on the results of a previous validation study of carbamate inhibition of cholinesterase 

(Roegge, 2009, WIL-99420). 

II. RESULTS -Pups: Def"mitive Dose-Response Study (MRID 48784803) 

Adults: Dose Range- Finding Study (MRID 48784802) 

A. OBSERVATIONS 

1. Clinical signs of toxicity 

.!} Pups- No clinical signs were observed prior to dosing. No clinical observations were 

recorded post dosing due to technician error, as documented in the protocol deviations. 

b) Adults- No clinical signs of toxicity were noted in the adults prior to dosing, or just prior 

to euthanasia (approximately 5-10 minutes following dose administration) at any dose level. 

2. Mortality 

a) Pups - All pups survived to scheduled termination. 

b) Adults - All adult rats survived until scheduled termination. 

B. BODY WEIGHTS - Pups and Adults - Body weights of the treated PND 11 pups and adult 

rats were comparable to their respective controls on the day of dose administration. 

C. CHOLINESTERASE ACTIVITY-The cholinesterase data for both compartments and age 

groups are summarized and presented below in Tables 6 and 7. 

1. Red Blood Cell (RBC) Cholinesterase - Pups. RBC data in pups was evaluated in the 

definitive dose-response study. RBC cholinesterase activity was decreased (dose-related) in both 

sexes at 0.5 hour following acute exposure (males decreased 12-66%/females dec.reased 31-65%) ) 

to dose levels ranging from 0.1 to 1.0 mg/kg (Table 7). In males, the mean RBC cholinesterase 
e adult rats of both sexes at 15 minutes following acute exposure (males decreased 15-

62%/females decreased 16-85%) to dose levels ranging from 1.0 to 10 mg/kg (Table 8). With the 

sexes combined, the reductions were 15-74%. At lower doses, males and females had similar 

responses (1 and 2 mg/kg), but at higher doses females had a greater response than males (i.e., 

42% vs. 53% at 3 mg/kg, 50% vs. 61% at 5 mg/kg and 62 vs. 85% at 10 mg/kg for males and 

females, respectively). At the common dose of 1.0 mg/kg, RBC cholinesterase was reduced 15-

16% in the adult rats compared to 65% in the PND 11 pups. 

2. Brain Cholinesterase- Pups- Brain cholinesterase activity was decreased at all doses 

compared to the control values in the male (8-55%) and female (8-48%) PND 11 pups (Table 7). A BMD analysis will provide a level at which 10% inhibition was observed. In males, mean 

whole brain activity was statistically significantly (p<0.01 or p<O.OS) lower in all three dose groups relative to the control group. In females, whole brain cholinesterase activity was statistically significantly (p<0.01) lower than the control in the 0.3 and 1 mglkg/day groups. 

Adults- Brain cholinesterase activity was decreased at all doses in male (16-46%) and female 

(10-53%) adult rats except the lowest dose in the male rats (Table 8). At the common dose of 1.0 

mg/kg, brain cholinesterase was reduced 3-10% in the adult rats compared to 48-55% in the PND 

11 pups. 

Table 6. PND 11 pup cholinesterase results from definitive dose-response study (MRID 48784803) Sex omwk! 0.1 mwk! 0.3m2fk! t.omwk! 

RBC Cholinesterase (U/L_l 

PND 11 Males 6737±1121.1 

%! 5916±986.3 4532±1319.4 2323±591.8 

12.2 32.7 .. 65.5•• 

range 4796-7918 5416-8782 2182-6364 1474-3396 

PND 11 6994±2057.7 4856±489.9 3544±1166 2460±900.1 Females 

%! 30.6•• 49.3•• 64.8•• 

range 

4188-10758 4244-5530 2196-6124 1474-3848 

Brain Cholinesterase (UIL) 

PND 11 Males 21887±1315.5 

%! 18250±1.639.2 10594±1190 23708±1480.1 

7.7• 23•• 55.3•• 

range 21082-26230 19796-24692 14277-19866 9040-12595 

PND 11 24263±1220.8 22320±1610.7 16844±2432,9 12592±2300 Females 

8/o! 8 30.6•• 48.1 .. 

range 22959-27078 19117-24191 14305-21859 9641-17993 
Males 2928±1187.6 2499±468.4 2061±792 .5 1701±934.8 1453±408.5 1120±636.4 15 30 42* 50* 62** 

Range 1892-5020 1920-3196 1058-3168 520-2928 874-1980 794-2362 

Females 3220±894.9 2697±728.8 2158±630.1 1515±645.9 1246±427.5 485±239.5 16 33* 53** 61** 85** 

Range 1962-4270 1652-3532 1270-3220 606-2278 818-1764 252-902 

Brain Cholinesterase (U/L) 

Males 52184±1887.5 50600±2619.9 43686±2300.2 41315±3712.8 34964±4661 28107±8309.1 

3 16* 21** 33** 46** 

Ranee 50068-54796 47460-54647 41150-46719 34861-43627 30790-40971 19611-39910 

Females 51558±1322.9 46481±2540.1 42136±5139.1 34790±2268.7 26276±6965 24324±13626 

10 18 33** 49** 53** 

Range 49750-53396 42747-49686 36182-48124 32210-38267 17979-37048 16975-52060 

Data obtained from Table 4 (pages 48-49) and Tables A9/A10 (pages 215-270) of the study report; n = 6 rat/sex/group 

*statistically significant* Dunnett's p-value *p<0.05, or** p<0.01 

D. BRAIN WEIGHT - Following acute oral exposure to propoxur, brain weights were 

comparable among the groups in both age groups and sexes in all three studies (time course, dose 

response and dose range fmding). 

E. BENCHMARK DOSE CBMD) ANALYSIS: RED conducted BMD analyses on the 

propoxur comparative cholinesterase data (CCA) for both adults (MRID 48784803) and PND 11 

pups (MRID 48784802) for both RBC and brain compartments. The results are presented in 

Table 8. In addition, RED considered the registrant's submitted benchmark dose (BMD) 

analysis of the cholinesterase findings (Mihlan and Sheets (2012). Estimation of Benchmark 

Dose for Propoxur Based on RBC Cholinesterase Activity in Post-Natal Day 11 and Adult Rats; 

MRID 48784804). RED has reviewed the submission to verify the BMD analysis of the 

cholinesterase data presented in MRID 48784804. RED conducted a confirmatory analysis 

using EPA's Benchmark Dose Software (BMDS) 2.1.1, the same software used in MRID 

48,784804 and was able to reproduce the registrant's BMD analyses for the male and females. 

In addition, RED evaluated the male and female pup RBC data from the dose response study to 

see if it was appropriate to combine these data for BMD analysis. The registrant proposed that 

the Agency use the combined BMDLlO for regulatory purposes. To evaluate the merit of this 

approach, RED conducted a Likelihood ratio test (LRT) for RBC pup data based on the BMD 

output. The result of the LRT is not statistically significant because p value is greater than 

conventional alpha level of 0.05. Thus the likelihood-based evaluation suggests that the male l 

and female PNDll RBC data can be combined in the dose-response modeling. EPA also 

believes that there is no biological basis for gender-based differences in AChE inhibition in 
from J. Liccione/ B.Sarkar August 30, 2012 TXR 0056440). 

Sex 

Male 

" 

Female 

I· 

Combined 

Sexes 

Table 8 

Summary of OPPs Benchmark Dose (BMD) Analyses for 

RBC and Brain ChE inhibition 

Adult" PND 11 PupsA PND 11 PupsA 

Target (MRID 48784802 (MRID 48784803 (MRID 48784802 Range Range Finding Study) Dose ReSj >Q_nse Study) Findinrz Study) Organ 

BMD1o BMDL1o BMD1o BMDL1o BMD1o BMDL1o 

Brain 1.26 1.09 0.13 0.12 0.14 0.11 

-

RBC 0.73 0.498 0.094 0.075 0.1 0.08 

Brain 0.88 0.76 0.08 0.06 0.1 o.os ; 

RBC 0.55 0.46 0.02 0.01 0.088 O.Q67 

Brain 1.29 1.04 0.122 0.0875 -- ---

RBC 0.474 0.339 0.042.7 0.0285 -- --

A Adult BMDs based on data m MRID 48784802; PNDII pup BMDs based on data m MRID 48784802, and MRID 48784803. 

Ill. DISCUSSION and CONCLUSIONS 

A.INVESTIGATORS' CONCLUSIONS (from Report Summary) - Based on the time to 

peak effect study (MRID 48784801) in adult rats and PND 11 pups, the investigators concluded 

that 15 minutes post-dosing was the appropriate time to sample blood and brain tissue for 

cholinesterase activity in the adult phase and 30 minutes post-dosing was appropriate in the PND 

11 pup phase of the comparative dose-response study. Recovery ofChE activity was observed at 

4 hours post dosing for adults administered 5 mglkg, while complete recovery time was not identified for pups given 3 mglkg. 

In the range finding study (MRID 48784802) a dose-related reduction in cholinesterase activity (both compartments) was observed at all dose levels in both sexes of adults and PND 11 pups (adults: 1, 2, 3, 5, or 10 mg/kg and PND 11 pups: 0.3, 0.5, 1, 2, or 3 mg/kg). In adult rats, mean 

RBC cholinesterase inhibition (ChEI) ranged from 15% to 85%, while mean whole brain ChEI 

ranged from 3% to 53%. In pups, the lowest dose tested of 0.3 mglkg resulted in 36-38% RBC 

ChE inhibition and 22-28% brain ChEI (both statistically significant). 

\l 
The investigators did not identify a no-observed-effect level (NOEL) for adults or pups, although 

at 2 mg!kg statistically significant RBC ChEI (33%) was noted in adult female rats, and 

statistically significant brain ChEI (16%) was noted in adult male rats. In pups, the lowest dose 

tested of 0.1 mg!kg in the definitive dose response study resulted in 31% and 12% RBC ChE 

inhibition in female pups (statistically significant) and male pups (not significant), respectively. 

B. REVIEWER COMMENTS - There were no treatment-related effects on mortality 

following acute oral exposure to propoxur in either adult rats or PND 11 pups. The time to peak 

effect is 15 minutes post-do.sing for adults and 30 minutes for PND 11 pups following propoxur 

doses of 5 mg!kg and 3 mg!kg, respectively. In the time course study, tremors were noted for 

12/40 PND 11 pups given 3 mg!kg propoxur between 0.25 and 1 hour post-dosing, while no 

treatment-related clinical findings were noted in adult males dosed with 5 mg!kg propoxur. 

PND 11 male pups with tremors displayed corresponding RBC and brain inhibition of 48-74% 

and 41-64%, respectively between 15 and 60 minutes post-dosing with 3 mg!kg. In adult males, 

RBC and whole-brain cholinesterase levels were similar to those in the control group at 

approximately 4-hours post-dosing, indicating complete recovery. For PND11 male pups, RBC and whole brain cholinesterase activity in the 3.0 mg!kg pup group increased from 0.5- to 4-

hours post-dosing (106% and 83%, respectively, at 4 hours), providing evidence of partial 

recovery in brain of pups. Overall results from the doses evaluated in the time course study 

suggest that the time of peak inhibition occurred slightly faster in adults (15 minutes) than in 

PND11 pups (30 minutes), but the PND11 pups took longer to recover. 

In the range finding study (MRID 48784802) there was a greater amount of inhibition in pups at 

a similar dose in adults and there was significant inhibition at a much lower dose than adults. 

Both sexes of PND 11 pups displayed significant brain cholinesterase inhibition (22% -64%) at 

dose levels of 0.3 mg!kg - 3 mg!kg for both sexes, whereas a similar but lower level of brain 

inhibition (3%-53%) occurred in both sexes of the adult rats at 1 mg!kg to 10 mg!kg. 

Significant RBC cholinesterase inhibition (>36%) was observed in the PND 11 pups at 0.3 

mg!kg and above, whereas the adult rat displayed this level of RBC cholinesterase inhibition at 2 

mg!kg and above. At the common dose of 1.0 mg!kg, RBC cholinesterase was reduced 15-16% 

in the adult rats compared to 57-58% in both sexes ofPND 11 pups. 

In the dose response study (MRID 48784803) with only PND 11 pups, both sexes displayed a 

dose-related reduction in RBC cholinesterase activity, with females being more sensitive than 

males. The magnitude of inhibition was 33% for males and 49% for females at 0.3 mg!kg and 

approximately 65% (both sexes) at the highest dose tested (1.0 mg!kg). At 0.1 mg!kg (lowest 

dose tested), 31% and 12% RBC cholinesterase inhibition was observed in the female and male 

PND 11 pups, respectively, which was statistically significant for female pups. -In PND pups, 

brain cholinesterase activity was decreased at all doses in both sexes. The magnitude of the 
D. STUDY DEFICIENCIES- None that would impact study interpretation. The description of the cholinesterase assay procedures lacks sufficient details. 
course) 

15 minutes 6327±920 

240 minutes 4780±993 

MRID 48784803A 6737±1121.1 

(dose-response) 

Females PNDll RBC UIL 

MRID 48784802A 7158±884 

MRID 48784801 Not tested 

MRID 48784803A 6994±2057.7 

Males PNDll Brain U/L 

MRID 48784802A 23940±1983 

MRID 48784801 

15 minutes 24230±1150 

240 minutes 24097+1039.6 

MRID 48784803A 23708±1480.1 

Females PNDll Brain U/L 

MRID 48784802A 24486±812 

MRID 48784801 Not tested 

MRID 48784803A 24263±1220.8 

30 mmutes post dose 

Summary Table 2. Adult Rat Control Values Across Studies 

Males- Adult RBC U/L 

MRID 48784802A 2928±1187.6 

MRID 48784801 

15 minutes 3150±530 

240 minutes 3482±379 

MRID 48784803A 2928±1187.6 

Females- Adult RBC U/L I 

MRID 48784802A 3220±894 

MRID 48784801 Not tested 

MRID 48784803 A 3220±894.9 

Males -Adult Brain U/L 

MRID 48784802A 52184±1887.5 

MRID 48784801 

15 minutes 49994±1008 

240 minutes 50118±1782 

MRID 48784803 A 52184±1887.5 

Females -Adult Brain U/L 

MRID 48784802A 51558±1322 

MRID 48784801 Not tested 

MRID 48784803 A 51558±1322.9 

A 15 mmutes post dose, NT females not tested 

~0 
48784803A -

(dose-response) 

Females 

MRID 7158±884 4444±879 (37.90/o)** 3029±900 U57.7%)** 

48784802A 

range imding 

study 

MRID 6994±2057.7 3544±1166 (49.3%)** 2460±900.1 U64.8%)** 

48784803A -

(dose-response) 

PND 11 Pup Brain Cholinesterase Values UIL 

Males 

MRID 23640±1983 18456±2756 (21.90/o) 13719±3004 U42%)** 

48784802A 

range fmding 

study 

MRID 23708±1480.1 18250±1639.2 (23%)** 10594±1190 U55.3%)** 

48784803A 

(dose-response) 

Females 

MRID 24486±812 18378±2164 U24.9%)** 12856±1936 U47.5%)** 

48784802A 

range finding 

study 

MRID 24263±1220.8 16844±2432.9 (J.30.6%)** 12592±2300 U48%)** 

48784803A 

(dose-response) 

(!%inhibition at 30 minutes;* p<0.05; ** p<O.Ol; mean± s.d. 
MEMORANDUM 

Date: August 30, 2012 

SUBJECT: Propoxur: Ben~hmark Dose Analysis of A~ute Oral Studies and Derivation 

of a Point of Departure. 

PC Code: 047802 

Decision No.: 464412 

Petition No.: NA 

Risk Assessment Type: NA 

TXR No.: 0056440 

MRIDNo.:NA 

FROM: John Liccione 

Toxicologist/Ris 

RABV 

DP 

Bar~ode: D404194 

Registration No.: NA 

Regulatory A~tion: NA 

Case No.: NA 

CASNo.:NA 

40CFR: NA 

Health Effects Division (7905P) r 

And C'L .. n ~ s~~~Nt)LJ.!L~ 

Bayazid Sarkar V.J~ilNt{ ..S: 

Mathematical Statisti~ 0. 

Chemistry and Exposure Branch (CEB) 

Health Effects Division (7905P) 

THROUGH: Anna Lowit, Ph.D. ~~ ' n 

Senior Scientist ~ ~ 

Health Effects Division 7905P) 

Acting 

~!hael 

Branch Metzger Chie ~ n n ~ K:· 

RABV 

Health Effects Division · 7905P) 

and 

Page 1 of84 
s

ssesso

RABVI Health Effects Division (7905P) 

I. CONCLUSIONS 

OPP performed benchmark dose (BMD) analyses of the comparative cholinesterase assay (CCA) 

on propoxur in order to establish a point of departure (POD) for the single-chemical risk 

assessment using the agency's Benchmark Dose Software (BMDS). OPP analyzed the 

registrant-supplied data of red blood cell (RBC) acetylcholinesterase inhibition (AChEI) in 

male and female PND11 pups (combined sex data) and calculated a BMD10 (Benchmark Dose 

for 10% inhibition) as 0.0427 mg/kg/day and the BMDL10 (i.e. 95% Lower Bound 

Confidence Limits on the BMD10) was estimated as 0.0285 mg/kg/day. OPP has concluded 

that the use of a BMDL10 of 0.0285 mg/kg/day will provide a health-protective and scientifically 

supportable approach for an acute POD. 

Based on a comparison ofBMD10s, pups were approximately 11 fold more sensitive than the 

adult rats for brain and RBC cholinesterase inhibition (combined sex data). However, male pups 

were between 7 and 10 fold more sensitive than male adults, while female pups were between 6 

and 28 fold more sensitive than female adults for brain and RBC cholinesterase inhibition. 

This memo summarizes the approach and presents the results of BMD analyses and POD 

derivation. 

II. BACKGROUND 

A series of non-guideline cholinesterase (ChE) inhibition studies (MRID 48784801-48784803) 

were undertaken to evaluate any differences between postnatal day 11 (PND 11) pups and adult 

rats (approximately 7-8 weeks of age) with regard to cholinesterase inhibition for propoxur. 

These CCA studies consist of a Time-Course Study (MRID 48784801 ), a Dose Range-Finding 

Study in both adults and pups (MRID 48784802) and a Dose-Response Study in Pups 

(MRID48784803). Consistent with then-methyl carbamates mode of action (MOA), these 

studies evaluated cholinesterase inhibition following a single dose at the time of peak effect. 

These studies are classified as acceptable/non-guideline and satisfy the generic data call-in 

requirement for propoxur for a comparative cholinesterase study in adult rats versus postnatal 

day (PND) 11 pups. Both the range finding and definitive studies provide good dose-response 

data. The definitive study used doses from 0.1 to 1 mg/kg, while the range fmding study uses 

doses from 1 to 10 mg/kg in adults and 0.3 to 3 mg/kg in pups. 

Page2 of84 
The Registrant conducted an analysis and submitted in findings (Mihlan and Sheets (2012). 

Estimation of Benchmark Dose for Propoxur Based on RBC Cholinesterase Activity in PostNatal Day 11 and Adult Rats; MRID 48784804). OPP has conducted an independent analysis. Both are discussed in this memo. 

III. METHODS 

OPP's BMD analyses were performed with EPA's Benchmark Dose Software (Version 2.1.1). 

The data selected for evaluation consisted of brain and red blood cell (RBC) acetylcholinesterase (AChE) activities from PND11 and adult rat OPP has previously used the exponential model for 

modeling ChE activity, except when the data fit another model better. In the case of the 

propoxur CCA study, OPP has used an exponential model, except for female and combined 

PND 11 pups where the Hill model provided a better fit of the RBC cholinesterase data. Model 

runs for ChE activity were conducted with the benchmark response level of 10% , and statistical 

(e.g., goodness of fit values, AIC criteria, scaled residual, etc.) and graphical results were used in 

model evaluation (USEP A 2000, 2002). 

The registrant proposed that the Agency use the combined BMDL10 for regulatory purposes. To evaluate the merit of this approach, HED conducted a Likelihood ratio test (LRT) for RBC pup data based on the BMD output. This analysis is provided in Appendix A. The result of the 

LRT is not statistically significant because p value is greater than conventional alpha level of 

0.05. Thus the likelihood-based evaluation suggests that the male and female PND11 RBC data 

can be combined in the dose-response modeling. EPA also believes that there is no biological basis for gender-based differences in AChE inhibition in PND11 rats with N-methyl 

carbamates, like propoxur. Given the lack of statistical significance, and lack of biological basis for gender based difference in RBC at PND 11 HED has concluded that male and female data for 

PND 11 pups can be combined for deriving more robust POD for AChE inhibition at this age. 

IV. Comparison to Registrant BMD analysis 

The registrant used a slightly different version of BMD (although there is no important 

difference between the versions), and only conducted BMDs for RBC ChE. In addition, the 

registrant utilized a heterogeneous variance model for both male and female RBC datasets; 

however, HED applied a homogeneous variance model to the male RBC dataset since it provided 

a better fit. Also, for adult RBC ChE, the registrant dropped the high dose in their analyses for both males and females. HED only dropped the high dose for the males because HED could not 

obtain an adequate fit for male data. However, the female adult data analyses resulted in an 

adequate fit (without dropping the high dose group). It is HED policy to utilize the entire dose 

Page 3 of84 
with the registrant that the Hill model is the best fit for the female and combined pup RBC ChE 

data. In addition, HED calculated BMDs using the exponential model for comparison purposes, 

although the Hill model provides a better fit of the data (as shown in Table 2). 

The registrant also included Likelihood Ratio Test (LRn to evaluate the appropriateness of 

combining sexes statistically. HED reviewed the analysis ofLRT test and was able to replicate 

the result (i.e. p value) ofLRT test for PNDll RBC. See Appendix A. 

V. RESULTS 

The results of the BMD analyses are summarized in Table 1 below. Details are included in 

Appendix A. HED was able to reproduce most of the registrant's BMD analyses for the male 

and females (Mihlan and Sheets 2012). In addition, HED evaluated the male and female pup 

RBC data from the dose response study to see if it was appropriate to combine these data for 

BMD analysis. 

HED concluded that these datasets can be combined to provide more robust ChE measures as there is no 

biological basis to support sex-differences for PND 11 pups. In addition, the statistical test also did not 

fmd significant difference in these datasets (p=0.067) at conventional alpha level 0.05. 

HED also conducted BMD analysis of the PND 11 pup data from the range fmding study that 

used a smaller sample size (n=6 sex/dose) for comparison with the BMD estimates from the dose 

response study (n= 11/sex/dose) and these BMDs are shown in Table 1. 

Details of Agency's BMD analysis are presented in Appendix B. 

Page4 of84 
Male 

Female 

Combined 

Sexes 

Organ 

BMDto BMDLto BMDto BMDLto BMDto BMDLto 

Brain 1.26 1.09 0.13 0.12 0.14 0.11 

RBC 0.73 0.498 0.094 0.075 0.1 0.08 

Brain 0.88 0.76 0.08 0.06 0.1 0.08 

RBC 0.55 0.46 0.02 0.01 0.088 0.067 

Brain 1.29 1.04 0.12Q 0.0875 - -

RBC 0.474 0.339 0.0427 0.0285 -- ---

A Adult BMDs based on data m MRID 48784802; PNDll pup BMDs based on data m MRID 48784802, and MRID 48784803. 

Table 2 

Summary Statistics of PND 11 Pup Cholinesterase Data as 

Reported by the Registrant (MRID 48784803) (a) 

Time Mean 

post Time ChE ChE 

sex age dosing unit dose Activity unit sd n 

AcuteRBC 

PND11 0.5 hr 0 6737 UIL 1121.1 9 

PND11 0.5 hr 0.1 5916 UIL 986.3 9 

Males PND11 0.5 hr 0.3 4532 UIL 1319.4 9 

PND11 0.5 hr 1 2323 UIL 591.8 8 

PND11 0.5 hr 0 6994 UIL 2057.7 9 

PND11 0.5 hr 0.1 4856 UIL 489.9 8 

PND11 0.5 hr 0.3 3544 UIL 1166 10 

Females PND11 0.5 hr 1 2460 UIL 900.1 10 

PND11 0.5 hr 0 6865.67 UIL 1612.92 18 

PND11 0.5 hr 0.1 5416.94 UIL 942.63 17 

PND11 0.5 hr 0.3 4012.21 UIL 1307.87 19 

M+F PND11 0.5 hr 1 2398.9 UIL 760.28 18 

Acute Brain 

Males PND11 0.5 hr 0 23708 UIL 1480.1 11 

PND11 0.5 hr 0.1 21887 UIL 1315.5 11 ~ Page 5 of84 
Females 

M+F 

Sex 

AcuteRBC 

M M 

M M 

M M 

F 

F 

F 

F 

F 

F 

M+F M+F M+F 

M+F M+F 

PND11 0.5 hr 0.3 16844 UIL 2432.9 11 PND11 0.5 hr 1 12592 UIL 2300 11 

PND11 0.5 hr 0 23985.82 UIL 1354.13 22 

PND11 0.5 hr 0.1 22103.86 UIL 1452.14 22 PND11 0.5 hr 0.3 17547.18 UIL 2148.51 22 

PND11 0.5 hr 1 11593.18 UIL 2058.85 22 

(a) Combined male and female statistics calculated by EPA. 

Table3 

Summary Statistics of Acute Adult Cholinesterase Data in 

Range Finding Study (MRID 48784802) 

Time 

post Time Dose ChE ChE 

dosin2 unit m2/k2 Activity unit sd n 

-

. 

0.25 hr 0 2928 UIL 1187.6 6 

0.25 hr 1 2499 UIL 468.4 6 

0.25 hr 2 2061 UIL 792.5 6 

0.25 hr 3 1701 UIL 934.8 6 

0.25 hr 5 1453 UIL 408.5 6 

0.25 hr 10 1120 UIL 636.4 6 

0.25 hr 0 3220 UIL 894.9 6 

0.25 hr 1 2697 UIL 728.8 6 

0.25 hr 2 2158 UIL 630.1 6 

0.25 hr 3 1515 UIL 645.9 6 0.25 hr 5 1246 UIL 427.5 6 

0.25 hr 10 485 UIL 239.5 6 

0.25 hr 0 3074 UIL 1014 12 

0.25 hr 1 2598 UIL 593 12 0.25 hr 2 2109.5 UIL 684 12 

0.25 hr 3 1607 UIL 772 12 

0.25 hr 5 1349 UIL 413 12 

Page 6 of84 
M 0.25 hr 2 43686 UIL 2300.2 6 

M 0.25 hr 3 41315 UIL 3712.8 6 

M 0.25 hr 5 34964 UIL 4661.7 6 

M 0.25 hr 10 28107 UIL 8309.1 6 

F 0.25 hr 0 51558 UIL 1322.9 6 

F 0.25 hr 1 46481 UIL 2540.1 6 

F 0.25 hr 2 42136 UIL 5139.1 6 

F 0.25 hr 3 34790 UIL 2268.7 6 

F 0.25 hr 5 26276 UIL 6965.7 6 

F 0.25 hr 10 24324 UIL 13626.8 6 

M+F 0.25 hr 0 51870 UIL 1587.9 12 

M+F 0.25 hr 1 48540 UIL 3268 12 

M+F 0.25 hr 2 42911 UIL 3881 12 

M+F 0.25 hr 3 37755 UIL 4438 12 

M+F 0.25 hr 5 30620 UIL 7247 12 

M+F 0.25 hr 10 26215 UIL 10940 12 

VI. Recommendation for POD for Single Chemical Risk Assessment. 

Based on the analyses, it is concluded that the use of a BMDL10 of 0.0285 mg/kg/day for red 

blood cell (RBC) cholinesterase inhibition (ChEI) in male and female PND11 pups (combined 

sex data) will provide a health-protective and scientifically supportable approach for an acute 

POD. 

VII. References 

U.S. EPA 2000. Benchmark Dose Guidance Document. October 2000. 

U.S EPA 2002. "Organophosphate pesticides: revised cumulative risk assessment." June 2002. 

Page 7 of84 
, 

p

g

(male, female and combined sexes) to conduct a likelihood ratio test (LRT). The Exponential 

model 4 meets this criterion. 

The Likelihood Ratio test can be conducted using the following asymptotic result: 

Chi-Square(''Number of Parameters") = -2 x {Logarithm Likelihood Model Fit to Combined 

Males & Females - (Logarithm Likelihood Model Fit to Males+ Logarithm Likelihood Model 

Fit to Females)}; Where 

''Number of Parameters" is the degrees of freedom and is equal to the number of 

parameters in the model. The distribution of test statistic follows a Chi-Square 

distribution with ''Number of Parameters" degrees of freedom. 

The Log- Likelihood value for PND11 male for exponential model(4) with heterogeneous 

variance= -257.6347-32.16 = -289.7947 

The Log- Likelihood value for PND11 female for exponential model(4) with heterogeneous 

variance= -278.8974-34 =-312.8974 

The Log-Likelihood for PND11 combined dataset for exponential model (4) with heterogeneous 

variance= -541.693-66.16= -607.853 

The chi-square test statistic= -2*(-607.853-(-289.7947-312.8974))=-2*(-5.1609)=10.3218 

DF=5 

p value= 0.067. 

Note registrant also derived the same p value. 

The result ofthe LRT is not statistically significant at conventional alpha=0.05level. Thus the 

likelihood-based evaluation suggests that the male and female PND11 RBC data can be 

combined in the dose-response modeling 

Page 8 of84 
Sex Compartment BMD Results8 

(mg/kg/day) 

BMDto BMDLto 

Dose Response Study (48784802 (n=11 sex/dose) (b) 

0.13 0.12 

Male Exponential 2 Exponential 2 

0.08 0.06 

Female Exponential 4 

Brain Exponential 4 

Combined 0.122 0.0875 

Male and 

Female Exponential 5 Exponential 5 

Male 0.094 0.075 

Exponential 2 Exponential 2 

0.021 0.010 

Female Hill Model Hill model 

(Best Fit of data) (Best Fit of data) 

RBC 0.032 0.019 

Exponential 2 Exponential 2 

Combined 0.0427 0.0285 

Male and Hill Model Hill Model 

Female 

Range Finding Study_(48784802 (n=4-6 sex/dose}_ 

Male Brain 0.145 0.1095 

Female 0.1 0.082 

Male RBC 0.1 0.080 

Female 0.088 0.067 

8Exponential Model with BMR = 10%, unless noted. EPA BMDS Software 

(b) source: MRID 48784803 

Page9 of84 
1.26

 1.09

 

Male Exponential 2 Exponential 2 

0.88 0.76 

Female Brain Exponential 2 Exponential 2 

Combined 1.29 1.04 

Male and 

Female Exponential 5 Exponential 5 

Male 0.7309° 0.4982° 

Exponential 2 Exponential 2 

Female 0.55 0.46 

RBC Exponential 2 Exponential 2 

Combined 0.474 0.339 

Male and 

Female Exponential 4 Exponential 4 

Source: MRID 48784802 

8Exponential Model with BMR = 10%. EPA BMDS Software 

bHigh dose dropped. 

Page 10 of84 
0.5 hr 0 6994 UIL 2057.7 9 

0.5 hr 0.1 4856 UIL 489.9 8 

0.5 hr 0.3 3544 UIL 1166 10 

0.5 hr 2460 UIL 900.1 10 

==================================================================== Hill Model. {Version: 2.15; Date: 10/28/2009) Input Data File: C:/Usepa/BMDS212/Data/hil Testrunscontinuous Opt. {d) Gnuplot Plotting File: C:/Usepa/BMDS212/Data/hil_Testrunscontinuous_Opt.plt 

Men Jun 18 11:24:15 2012 

==================================================================== 

BMDS Model Run 

The form of the response function is: 

Dependent variable = Mean 

Independent variable = Dose 

Power parameter restricted to be greater than 1 The variance is to be modeled as Var{i) = exp{lalpha +rho* ln{mean{i))) 

Total number of dose groups = 4 

Total number of records with missing values = 0 Maximum number of iterations = 250 

Relative Function Convergence has been set to: 1e-008 

Parameter Convergence has been set to: 1e-008 

Default Initial Parameter Values 

lalpha 14.3278 

rho 0 

intercept 

v 

n 

k 

6994 

-4534 

0.94713 

0.119665 

Asymptotic Correlation Matrix of Parameter Estimates 

Page 11 of84 
rho -1 1 -0.11 

intercept 0.1 -0.11 1 

v -0.23 0 . 23 -0 . 71 

k 0.086 -0.086 -0.51 

Parameter Estimates 

Interval 

Variable Estimate Std. Err. 

Limit 

lalpha 2.76865 4.68109 

11.9434 

rho 1. 35729 0.562229 

2.45924 

intercept 7056.86 534.476 

8104.41 

v -5125 . 22 640 . 528 

3869.81 

n 1 NA 

k 0.128476 0.0582209 

0.242587 

NA - Indicates that this parameter has hit a bound 

implied by some inequality constraint and thus 

has no standard error. 

Table of Data and Estimated Values of Interest 

Dose N Obs Mean Est Mean Obs Std Dev 

-------- -------- -----------

0 9 6 . 99e+003 7 . 06e+003 2 . 06e+003 

0 . 1 8 4.86e+003 4.81e+003 490 

0.3 10 3.54e+003 3.47e+003 1.17e+003 

1 10 2.46e+003 2.52e+003 900 

Model Descriptions for likelihoods calculated 

Model A1: Yij 

Var{e(ijl} 

Model A2: Yij 

Mu(i) + e(ij) 

Sigma ... 2 

Mu(i) + e(ij) 

Page 12 of 84 

0.23 -0.086 

-0.71 -0.51 

1 -0.16 

-0.16 1 

95.0% Wald Confidence 

Lower Conf. Limit Upper 

-6.40613 

0.255342 

6009.3 

-6380 . 63 

0.0143652 

Est Std Dev Scaled Res . 

----------- ----------

1 . 63e+003 -0 . 115 

1.26e+003 0 . 0951 

1.01e+003 0.237 

811 -0.215 

Conf. 
Test 1: 

Test 2: 

Test 3: 

Test 4: 

(Note: 

Test 

Test 

Test 

Test 

Test 

1 

2 

3 

4 

Likelihoods of Interest 

Model 

A1 

A2 

A3 

Log (likelihood) # Param•s AIC 

fitted 

R 

-281.447743 

-273.238355 

-278.207838 

-278.338748 

-301.433091 

Explanation of Tests 

5 572.895487 

8 562.476711 

6 568.415675 

5 566.677496 

2 606.866183 

Do responses and/or variances differ among Dose levels? (A2 vs. R) 

Are Variances Homogeneous? (A1 vs. A2) 

Are variances adequately modeled? (A2 vs. A3) 

Does the Model for the Mean Fit? (A3 vs. fitted) 

When rho=O the results of Test 3 and Test 2 will be the same.) 

Tests of Interest 

-2*log(Likelihood Ratio) Test df p-value 

56.3895 6 <.0001 

16.4188 3 0.0009304 

9.93896 2 0.006947 

0.261821 1 0.6089 

The p-value for Test 1 is less than .OS. There appears to be a difference between response and/or variances among the dose levels It seems appropriate to model the data 

The p-value for Test 2 is less than .1. A non-homogeneous variance model appears to be appropriate 

The p-value for Test 3 is less than .1. You may want to consider a different variance model 

The p-value for Test 4 is greater than .1. The model chosen seems 

to adequately describe the data 

Benchmark Dose Computation 

Specified effect 0.1 

Risk Type Relative risk 

Confidence level 0.95 

BMD 0.0205143 

Page 13 of84 
8000 

7000 

Q) 6000 Ul 

c: 

0 

c. 

Ul 

Q) 

0::: 5000 

c: 

I'll 

Q) 

::!: 

4000 

3000 

2000 

MD 

0 0.2 0.4 0.6 0.8 1 

dose 

11:24 06/18 2012 

Page 14 of84 
0.5 hr 0 24263 U/L 1220.8 11 

0.5 hr 0.1 22320 U/L 1610.7 11 

0.5 hr 0.3 16844 U/L 2432.9 11 

0.5 hr 12592 U/L 2300 11 

==================================-========-======================== Exponential Model. (Version: 1.7; Date: 12/10/2009) 

Input Data File: C:/Usepa/BMDS212/Data/exp_Testrunscontinuous_Setting. (d) Gnuplot Plotting File: 

Man May 07 14:14:11 2012 

BMDS Model Run 

The the response function by Model: form of 

Model 2: Y[dose] a * exp{sign * b * dose} 

Model 3: 

Model 4: 

Model 5: 

Y[dose] a* exp{sign * (b * dose)Ad} 

Y[dose] a* [c-(c-1) * exp{-b *dose}] 

Y[dose] a* [c-(c-1) * exp{-(b * dose)Ad}] 

Note: Y[dose] is the median response for e~osure = dose; 

sign +1 for increasing trend in data; 

sign = -1 for decreasing trend. 

Model 2 is nested within Models 3 and 4. 

Model 3 is nested within Model 5. 

Model 4 is nested within Model 5. 

Dependent variable = Mean 

Independent variable = Dose 

Data are assumed to be distributed: normally Variance Model: exp(lnalpha +rho *ln(Y[dose])) 

rho is set to o. 

A constant variance model is fit. 

Total number of dose groups = 4 

Total number of records with missing values = 0 

Maximum number of iterations = 250 

Relative Function Convergence has been set to: 1e-008 

Parameter Convergence has been set to: 1e-008 

MLE solution provided: Exact 

Initial Parameter values 

Page 15 of84 
(S) Specified 

Parameter Estimates by Model 

Variable 

lnalpha 

rho 

a 

b 

c 

d 

Table 

Dose N 

0 11 

0.1 11 

0.3 11 

1 11 

Model 

2 

3 

4 

5 

of 

Model 2 

15.4424 

0 

23437.7 

0.700996 

Stats From Input 

Obs Mean 

----------

2.426e+004 

2.232e+004 

1.684e+004 

1.259e+004 

Model 3 

15.4424 

0 

23437.7 

0.700996 

1 

Data 

Obs Std Dev 

-------------

1221 

1611 

2433 

2300 

Estimated Values of Interest 

Dose Est Mean Est Std 

---------- ---------

0 2.344e+004 2256 

0.1 2.185e+004 2256 

0.3 1.899e+004 2256 

1 1.163e+004 2256 

0 2.344e+004 2256 

0.1 2.185e+004 2256 

0 . 3 1.899e+004 2256 

1 1.163e+004 2256 

0 2.465e+004 1933 

0.1 2.153e+004 1933 

0.3 1.735e+004 1933 

1 1. 249e+004 1933 

0 2.426e+004 1864 

0.1 2.232e+004 1864 

0.3 1.684e+004 1864 

1 1. 259e+004 1864 

Other models for which likelihoods are calculated: 

Model A1: Yij 

Var{e(ij)} 

Mu(i) + e(ij) 

Sigma ... 2 

Page 16 of84 

Model 4 

15.134 

0 

24649.9 

2. 75113 

0.473097 

Scaled Residual 

----------------

1.213 

0.6896 

-3.159 

1.419 

1.213 

0.6896 

-3.159 

1.419 

-0.6638 

1. 362 

-0.871 

0.1729 

-8.431e-008 

2.676e-008 

-1.391e-007 

1.543e-008 

Model 5 

15.0613 

0 

24263 

3.34891 

0.518308 

1.55833 

~l 
Likelihoods of Interest 

Model Log (likelihood) 

-------

-----------------

A1 -3S3.3496 

A2 -3S0.2243 

A3 -3S3.3496 

R -396.3873 

2 -361.7322 

3 -361.7322 

4 -3S4.9483 

s -3S3.3496 

Additive constant for all log-likelihoods = 

above values gives the log-likelihood including 

depend on the model parameters. 

DF 

s 

8 

s 

2 

3 

3 

4 

s 

-40.43. 

the term 

Explanation of Tests 

AIC 

------------

716.6993 

716.448S 

716.6993 

796.774S 

729.4644 

729.4644 

717.8966 

716.6993 

This constant 

that does not 

added to the 

Test 1: Does response and/or variances differ among Dose levels? (A2 vs. R) 

Test 2: Are variances Homogeneous? (A2 vs. A1) 

Test 3: Are variances adequately modeled? (A2 vs. A3) 

Test 4: Does Model 2 fit the data? (A3 vs. 2) 

Test Sa: Does Model 3 fit the data·? (A3 vs. 3) 

Test Sb: Is Model 3 better than Model 2? (3 vs. 2) 

Test 6a: Does Model 4 fit the data? {A3 vs. 4) 

Test 6b: Is Model 4 better than Model 2? (4 vs. 2) 

Test 7a: Does Model s fit the data? {A3 VB. S) 

Test 7b: Is Model s better than Model 3? (S VB. 3) 

Test 7c: Is Model s better than Model 4? (S vs. 4) 

Tests of Interest 

Test -2*log(Likelihood Ratio) D. F. 

--------

------------------------ ------

Test 1 92.33 6 

Test 2 6.2S1 3 

Test 3 6.2S1 3 

Test 4 16.77 2 

Test Sa 16.77 2 

Test Sb 0 0 

Test 6a 3.197 1 

Test 6b 13.S7 1 

Test 7a 0 0 

Test 7b 16.77 2 

Test 7C 3.197 1 

Page 17 of84 

p-value 

< 0.0001 

0.1 

0.1 

0.0002288 

0.0002288 

N/A 

0.07376 

0.0002301 

N/A 

0.0002288 

0.07376 
variance appears to be appropriate here. 

The p-value for Test 4 is less than .1. Model 2 may not adequately 

describe the data; you may want to consider another model. 

The p-value for Test Sa is less than .1. Model 3 may not adequately 

describe the data; you may want to consider another model. 

Degrees of freedom for Test Sb are less than or equal to 0. 

The Chi-Square test for fit is not valid. The p-value for Test 6a is less than .1. Model 4 may not adequately 

describe the data; you may want to consider another model. 

The p-value for Test 6b is less than .05. Model 4 appears 

to fit the data better than Model 2. 

Degrees of freedom for Test 7a are less than or equal to 0. 

The Chi-Square test for fit is not valid. The p-value for Test 7b is less than .05. Model 5 appears 

to fit the data better than Model 3. 

The p-value for Test 7c is greater than .05. Model 5 does 

not seem to fit the data better than Model 4. 

Benchmark Dose Computations: 

Specified Effect 0.100000 

Risk Type Relative deviation 

Confidence Level 0.950000 

Model 

2 

3 

4 

5 

BMD and BMDL by Model 

BMD 

0.150301 

0.150301 

0.0764995 

0.117152 

BMDL 

0.129508 0.129508 

0.0600184 0.0753261 

Page 18 of84 

• i7. 
G) 20000 

Ill 

c 

0 

Q. 

Ill 

G) 18000 0:: 

c 

cu 

G) 

::::! 16000 l 

14000 

12000 

10000 BMD BMD 

0 0.2 0.4 0.6 0.8 1 

dose 

14:14 05/07 2012 

0 

Page 19 of84 
Q) 20000 

Ill 

c:: 0 

a. 

Ill 

Q) 18000 a:: 

c:: ca Q) 

:!!: 16000 I 

14000 

12000 

10000 BMD BMD 

0 0.2 0.4 0.6 0.8 1 

dose 

14:14 05/07 2012 

Page20 of84 
Q) 20000 

II) 

c: 

0 

c. 

II) 

Q) 18000 0:: 

c: 

I'll 

Q) ~ 16000 

14000 

12000 

10000 BMD BMD 

0 0.2 0.4 0.6 0.8 

dose 

14:14 05/07 2012 

Page 21 of84 
CD 20000 til 

c: 

0 

a. 

til CD 18000 0::: 

c: 

Ill 

CD 

:::! 16000 

14000 

12000 

10000 BMD MD 

0 0.2 0.4 0.6 0.8 

dose 

14:14 05/07 2012 

Page22 of84 
studytype 

acute time 

acute 

acute 

4 acute 

timeunit dose chei chunit sd n 

0.5 hr 0 6737 UIL 1121.1 9 

0.5 hr 0.1 5916 UIL 986.3 9 

0.5 hr 0.3 4532 UIL 1319.4 9 

0.5 hr 2323 UIL 591.8 8 

========================z=========================================== 

Exponential Model. (Version: 1.7; Date: 12/10/2009) 

Input Data File: C:/Usepa/BMDS212/Data/exp_Testrunscontinuous_Setting. (d) Gnuplot Plotting File: 

Mon May 07 11:58:51 2012 

==================================================================== 

BMDS Model Run 

The form of the 

Model 2: 

Model 3: 

Model 4: 

Model 5: 

response function by Model: 

Y[dose] a * exp{sign * b * dose} 

Y[dose] a * exp{sign * (b * dose)Ad} 

Y[dose] a * [c- (c-1) * exp{ -b * dose}] 

Y[dosel a* [c-(c-1) * exp{-(b * dose)Ad}l 

Note: Y[dose) is the median response for exposure = dose; 

sign +1 for increasing trend in data; 

sign = -1 for decreasing trend. 

I Model 2 is' nested within Models 3 and 4. 

Model 3 is nested within Model 5. 

Model 4 is nested within Model 5. 

Dependent variable = Mean 

Independent variable = Dose 

Data are assumed to be distributed: normally 

Variance Mode'l: exp(lnalpha +rho *ln(Y[dose])) 

rho is set to· o. 

A constant variance model is fit. 

Total number of dose groups = 4 

Total number of records with missing values = 0 

Maximum number of iterations = 250 

Relative Function Convergence has been set to: 1e-008 

Parameter Convergence has been set to: 1e-008 

MLE solution provided: Exact 

Page23 of84 
d 

(S) Specified 

1 

Parameter Estimates by Model 

Variable Model 2 Model 3 Model 4 

-------- ------- ------- -------

lnalpha 13.8128 13.8128 13.7932 

rho 0 0 0 

a 6625.92 6625.92 6753.37 

b 1.11739 1.11739 1.77608 

c 0.209792 

d 1 

Table of Stats From Input Data 

Dose N Obs Mean Obs Std Dev 

---------- -------------

0 9 6737 1121 

0.1 9 5916 986.3 

0.3 9 4532 1319 

1 8 2323 591.8 

Estimated Values of Interest 

Model Dose Est Mean Est Std Scaled Residual 

------- ------ ---------- --------- ----------------

2 0 6626 998.6 0.3337 

0.1 5925 998.6 -0.02828 

0.3 4739 998.6 -0.6211 

1 2168 998.6 0.4403 

3 0 6626 998.6 0.3337 

0.1 5925 998.6 -0.02828 

0.3 4739 998.6 -0.6211 

1 2168 998.6 0.4403 

4 0 6753 988.9 -0.04967 

0.1 5885 988.9 0.09417 

0.3 4549 988.9 -0.05181 

1 2320 988.9 0.007758 

5 0 6737 988.7 1. 987e-007 

0.1 5916 988.7 -4.962e-007 

0.3 4532 988.7 2.309e-007 

1 2323 988.7 9.523e-007 

Other models for which likelihoods are calculated: 

Page24 of84 

1 

Model 5 

-------

13.7928 

0 

6737 

1. 98588 

0.251467 

1.06876 
Likelihoods of Interest 

Model Log (likelihood) 

-------

-----------------

A1 -2S8.8746 

A2 -2S6.3498 

A3 -2S8.8746 

R -281.9819 

2 -2S9.224 

3 -2S9.224 

4 - 2S8 . 8817 

s -2S8.8746 

Additive constant for all log- likelihoods = 

above values gives the log-likelihood including 

depend on the' model parameters. 

DF 

s 

8 

s 

2 

3 

3 

4 

s 

-32 . 16. 

the term 

Explanation of Tests 

AIC 

------------

S27.7493 

S28.6996 

S27.7493 

S67.9638 

S24.4479 

S24.4479 

S2S.7634 

S27.7493 

This constant 

that does not 

added to the 

Test 1: Does response and/or variances differ among Dose levels? (A2 vs. R) 

Test 2 : Are variances Homogeneous? (A2 vs. A1) 

Test 3: Are variances adequately modeled? (A2 vs . A3) 

Test 4: Does Model 2 fit the data? (A3 vs. 2) 

Test Sa: Does Model 3 fit the data? (A3 vs. 3) 

Test Sb: Is Model 3 better than Model 2? (3 vs. 2) 

Test 6a: Does Model 4 fit the data? (A3 vs. 4) 

Test 6b: Is Model 4 better than Model 2? (4 vs. 2) 

Test 7a: Does Model s fit the data? (A3 vs. S) 

Test 7b: Is Model s better than Model 3? (S vs. 3) 

Test 7c : Is Model s better than Model 4? (S vs. 4) 

Tests of Interest 

Test -2*log(Likelihood Ratio) D. 

--------

------------------------

Test 1 S1.26 6 

Test 2 s.os 3 

Test 3 s.os 3 

Test 4 0.6986 2 

Test Sa 0.6986 2 

Test Sb 0 0 

Test 6a 0.01408 1 

Test 6b 0.6846 1 

Test 7a 1. 364e-012 0 

Page25 of84 

F. p-value 

--------------

< 0.0001 

0.1682 

0.1682 

0.70S2 

0.70S2 

N/A 

0.90SS 

0 . 408 

N/A 
The p-value for Test 3 is greater than .1. The modeled 

variance appears to be appropriate here. 

The p-value for Test 4 is greater than .1. Model 2 seems 

to adequately describe the data. 

The p-value for Test Sa is greater than .1. Model 3 seems 

to adequately describe the data. 

Degrees of freedom for Test Sb are less than or equal to 0. 

The Chi-Square test for fit is not valid. The p-value for Test 6a is greater than .1. Model 4 seems 

to adequately describe the data. 

The p-value for Test 6b is greater than .OS. Model 4 does 

not seem to fit the data better than Model 2. 

Degrees of freedom for Test 7a are less than or equal to 0. 

The Chi-Square test for fit is not valid. The p-value for Test 7b is greater than .OS. Model S does 

not seem to fit the data better than Model 3. 

The p-value for Test 7c is greater than .OS. Model S does 

not seem to fit the data better than Model 4. 

Benchmark Dose Computations: 

Specified Effect 0.100000 

Risk Type Relative deviation 

Confidence Level 0.9SOOOO 

Model 

2 

3 

4 

s 

BMD and BMDL by Model 

BMD 

0.0942918 0.0942918 0.0761809 

0.0818214 

BMDL 

0.0748161 0.0748161 

O.OS06134 O.OS06648 

Page 26 of84 
0.5 hr 0 23708 UIL 1480.1 11 

0.5 hr 0.1 21887 UIL 1315.5 11 

0.5 hr 0.3 18250 UIL 1639.2 11 

0.5 hr 10594 UIL 1190 11 

==================================================================== 

Exponential Model. (Version: 1.7; Date: 12/10/2009) 

Input Data File: C:/Usepa/BMDS212/Data/exp_Testrunscontinuous_Setting. (d) Gnuplot Plotting File: 

Mon May 07 12:25:36 2012 

==================================================================== 

BMDS Model Run 

The form of the response function by Model: 

Model 2: Y [dose] a * exp{sign * b * dose} 

Model 3: Y[dose] a * exp{sign * (b * dose)"d} 

Model 4: Y [dose] a * [c- (c-1) * exp{-b * dose}l 

Model 5: Y [dose] a * [c- (c-1) * exp{-(b * dose)"d}l 

Note: Y[dose] is the median response for exposure = dose; 

sign +1 for increasing trend in data; 

sign = -1 for decreasing trend. 

Model 2 is nested within Models 3 and 4. 

Model 3 is nested within Model 5. 

Model 4 is nested within Model 5. 

Dependent variable = Mean 

Independent variable = Dose 

Data are assumed to be distributed: normally 

Variance Model: exp(lnalpha +rho *ln(Y[dose])) 

rho is set to 0. 

A constant variance model is fit. 

Total number of dose groups = 4 

Total number of records with missing values = 0 

Maximum number of iterations = 250 

Relative Function Convergence has been set to: 1e-008 

Parameter Convergence has been set to: 1e-008 

MLE solution provided: Exact 

Initial Parameter Values 

Page27 of84 
(S) Specified 

Parameter Estimates by Model 

Variable 

lnalpha 

rho 

a 

b 

c 

d 

Model 2 

14.43 

0 

23640.5 

0.814242 

Model 3 

-------

14.43 

0 

23640.5 

0.814242 

1 

Table of Stats From Input Data 

Dose N Obs Mean Obs Std Dev 

---------- -------------

0 11 2.371e+004 1480 

0.1 11 2.189e+004 1316 

0.3 11 1.825e+004 1639 

1 11 1.059e+004 1190 

Estimated Values of Interest 

Model Dose Est Mean Est Std 

------

---------- ---------

2 0 2.364e+004 1360 

0.1 2.179e+004 1360 

0.3 1. 852e+004 1360 

1 1.047e+004 1360 

3 0 2.364e+004 1360 

0.1 2.179e+004 1360 

0.3 1.852e+004 1360 

1 1. 047e+004 1360 

4 0 2.378e+004 1353 

0.1 2.176e+004 1353 

0.3 1.831e+004 1353 

1 1.059e+004 1353 

5 0 2.371e+004 1350 

0.1 2.189e+004 1350 

0.3 1.825e+004 1350 

1 1.059e+004 1350 

Other models for which likelihoods are calculated: 

Model A1: Yij = Mu(i) + e(ij) 

Page 28 of84 

Model 4 

-------

14.4197 

0 

23777.2 

1.03883 

0.14148 

Scaled Residual 

----------------

0.1646 

0.232 

-0.6513 

0.2972 0.1646 

0.232 

-0.6513 

0.2972 

-0.1696 

0.304 

-0.1503 

0.01585 

-9.875e-008 

1. 349e-007 

1. 266e-007 

-1.187e-007 

Model 5 

-------

14.4164 

0 

23708 

1. 44418 

0.289878 

1.12009 
Likelihoods of Interest 

Model Log (likelihood) 

-------

-----------------

A1 -339.1604 

A2 -338.S238 

A3 -339.1604 

R -398.S328 

2 -339.4S92 

3 -339.4S92 

4 -339.232S 

s -339.1604 

Additive constant for all log-likelihoods = 

above values gives the log-likelihood including 

depend on the model parameters. 

DF 

s 

8 

s 

2 

3 

3 

4 

s 

-40.43. 

the term 

Explanation of Tests 

AIC 

------------

688.3208 

693.0476 

688.3208 

801.06S6 

684.9183 

684.9183 

686.46S1 

688.3208 

This constant 

that does not 

added to the 

Test 1: Does response and/or variances differ among Dose levels? (A2 vs. R) 

Test 2: Are Variances Homogeneous? (A2 vs. A1) 

Test 3: Are variances adequately modeled? (A2 vs. A3) 

Test 4: Does Model 2 fit the data? (A3 vs. 2) 

Test Sa: Does Model 3 fit the data? (A3 vs. 3) 

Test Sb: Is Model 3 better than Model 2? (3 vs. 2) 

Test 6a: Does Model 4 fit the data? (A3 vs. 4) 

Test 6b: Is Model 4 better than Model 2? (4 vs. 2) 

Test 7a: Does Model s fit the data? (A3 vs. S) 

Test 7b: Is Model s better than Model 3? (S vs. 3) 

Test 7c: Is Model s better than Model 4? (S vs. 4) 

Tests of Interest 

Test -2*log(Likelihood Ratio) D. F. 

--------

------------------------

Test 1 120 6 

Test 2 1. 273 3 

Test 3 1.273 3 

Test 4 O.S97S 2 

Test sa O.S97S 2 

Test Sb 1.137e-013 0 

Test 6a 0.1443 1 

Test 6b 0.4S32 1 

Test 7a 0 0 

Test 7b O.S97S 2 

Page29 of84 

p-value 

--------------

< 0.0001 

0.73SS 

0.73SS 

0.7417 

0.7417 

N/A 

0.7041 

O.S008 

N/A 

0.7417 
The p

value for Test 3 is greater than .1. The modeled 

variance appears to be appropriate here. 

The p-value for Test 4 is greater than .1. Model 2 seems 

to adequately describe the data. 

The p-value for Test Sa is greater than .1. Model 3 seems 

to adequately describe the data. 

Degrees of freedom for Test Sb are less than or equal to 0. 

The Chi-Square test for fit is not valid. The p-value for Test 6a is greater than .1. Model 4 seems 

to adequately describe the data. 

The p-value for Test 6b is greater than .05. Model 4 does 

not seem to fit the data better than Model 2. 

Degrees of freedom for Test 7a are less than or equal to 0. 

The Chi-Square test for fit is not valid. The p-value for Test 7b is greater than .05. Model 5 does 

not seem to fit the data better than Model 3. 

The p-value for Test 7c is greater than .05. Model 5 does 

not seem to fit the data better than Model 4. 

Benchmark Dose Computations: 

Specified Effect 0.100000 

Risk Type Relative deviation 

Confidence Level 0.950000 

BMD and BMDL by Model 

Model 

2 

3 

4 

5 

BMD 

0.129397 

0.129397 

0.119211 

0.128639 

BMDL 

0.119112 0.119112 

0.0974144 0.0979343 

Page 30 of84 

51 
20000 

5l 

c: 

0 

a. 18000 

II) 

CD 

a:: 

c: 

111 

CD 16000 

::!: 

14000 

12000 

10000 

BMD BMD 

0 0.2 0.4 0.6 0.8 1 

dose 

12:25 05/07 2012 

Page 31 of84 
20000 

Gl 

Ill 

r:::: 

0 

c. 18000 

Ill 

Gl 

0::: 

r:::: 

Ill 16000 Gl 

::! 

14000 12000 

10000 

BMD MD 

0 0.2 0.4 0.6 0.8 

dose 

12:25 05/07 2012 

Page 32 of84 
20000 

CD 

VI 

1: 

0 

c. 18000 

VI 

CD 

0::: 

1: 

cu 

CD 16000 ~ 14000 

12000 

10000 

BMD BMD 

0 0.2 0.4 0.6 0.8 1 

dose 

12:25 05/07 2012 

Page 33 of84 
20000 

Q) 

II) 

c: 

0 

c. 18000 

II) 

Q) 

0::: 

c: 

Cll 

Q) 16000 

:::!: 

14000 12000 

10000 

BMD MD 

0 0.2 0.4 0.6 0.8 1 

dose 

12:25 05/07 2012 

Page 34 of84 
0 3220 UIL 894.9 6 

I 2697 UIL 728.8 6 

2 2158 UIL 630.1 6 

3 1515 UIL 645.9 6 

15 1246 U/L 427.5 6 

10 485 UIL 239.5 6 

Exponential Model. (Version: 1.7; Date: 12/10/2009) 

Input Data File: C:/Usepa/BMDS212/Data/exp_Testrunscontinuous_Setting. (d) 

Gnuplot Plotting File: 

Thu Jun 07 09:03:13 2012 

==================================================================== 

BMDS Mode 1 Run 

The form of the 

Model 2: 

Model 3: 

Model 4: 

Model 5: 

response function by Model: 

Y[dose] a * exp{sign * b * dose} 

Y[dose] a* exp{sign * (b * dose)Ad} 

Y[dose] a* [c-(c-1) * exp{-b *dose}] 

Y[dose] a* [c-(c-1) * exp{-(b * dose)Ad}l 

Note: Y[dose] is the median response for exposure = dose; 

sign = +1 for increasing trend in data; 

sign = -1 for decreasing trend. 

Model 2 is nested within Models 3 and 4. 

Model 3 is nested within Model 5. 

Model 4 is nested within Model 5. 

Dependent variable = Mean 

Independent v.ariable = Dose 

Data are assumed to be distributed: normally 

Variance Mode~: exp(lnalpha +rho *ln(Y[dose])) 

The variance 1is to be modeled as Var (i) = exp (lalpha + log (mean {i)) * rho) 

Total number of dose groups = 6 

Total number of records with missing values = 0 

Maximum numbe~ of iterations = 250 

Relative Function Convergence has been set to: 1e-008 

Parameter Convergence has been set to: 1e-008 

MLE solution provided: Exact 

Page 35 of84 
d 1 1 

Parameter Estimates by Model 

Variable Model 2 Model 3 Model 4 Model 5 

-------- ------- ------- ------- -------

lnalpha 2.47268 2.47268 2.32367 2.32367 

rho 1.35616 1.35616 1. 37493 1.37493 

a 3145.43 3145.43 3224.88 3224.88 

b 0.192137 0.192137 0.224761 0.224761 

c 0.0507246 0.0507246 

d 1 1 

Table of Stats From Input Data 

Dose N Obs Mean Obs Std Dev 

---------- -------------

0 6 3220 894.9 

1 6 2697 728.8 2 6 2158 630.1 

3 6 1515 645.9 

5 6 1246 427.5 

10 6 485 239.5 

Estimated Values of Interest 

Model Dose Est Mean Est Std Scaled Residual 

---------- --------- ----------------

2 0 3145 810.3 0.2254 

1 2596 711.3 0.3492 

2 2142 624.4 0.06329 

3 1767 548.2 -1.128 

5 1204 422.4 0.2462 

10 460.5 220.2 0.2724 

3 0 3145 810.3 0.2254 

1 2596 711.3 0.3492 

2 2142 624.4 0.06329 

3 1767 548.2 -1.128 

5 1204 422.4 0.2462 

10 460.5 220.2 0.2724 

4 0 3225 825.2 -0.01447 

1 2609 713.3 0.3034 

2 2116 617.8 0.1646 

3 1723 536.4 -0.9516 

5 1159 408.3 0.5242 

10 487 225 -0.0219 

5 0 3225 825.2 -0.01447 

1 2609 713.3 0.3034 

Page 36 of84 
var{e(ij)} Sigma

2 

Model A2: Yij Mu(i) + e(ij) 

Var{e(ij)} Sigma(i)"'2 

Model A3: Yij Mu(i) + e(ij) 

Var{e(ij)} exp(lalpha + log(mean(i)) * 

Model R: Yij Mu + e(i) 

Var{e(ij)} Sigma"'2 

Likelihoods of Interest 

Model Log (likelihood) DF 

-------

-----------------

A1 -246.8013 7 

A2 -241.7651 12 

A3 -242.095 8 

R -269.4793 2 

2 -242.6912 4 

3 -242.6912 4 

4 -242.5467 5 

5 -242.5467 5 

rho) 

AIC 

------------

507.6026 

507.5301 

500.1899 

542.9587 

493.3823 

493.3823 

495.0933 

495.0933 

Additive constant for all log-likelihoods = 

above values gives the log-likelihood including 

depend on the model parameters. 

-33.08. This constant 

the term that does not 

Explanation of Tests 

added to the 

Test 1: Does response and/or variances differ among Dose levels? (A2 vs. R) 

Test 2: Are variances Homogeneous? (A2 vs. A1) 

Test 3: Are variances adequately modeled? (A2 vs. A3) 

Test 4: Does Model 2 fit the data? (A3 vs . 2) 

Test Sa: Does Model 3 fit the data? (A3 vs. 3) 

Test Sb: Is Model 3 better than Model 2? (3 vs. 2) 

Test 6a: Does Model 4 fit the data? (A3 vs. 4) 

Test 6b: Is Model 4 better than Model 2? (4 vs. 2) 

Test 7a: Does Model 5 fit the data? (A3 vs. 5) 

Test 7b: Is Model 5 better than Model 3? (5 vs. 3) 

Test 7c: Is Model 5 better than Model 4? (5 vs. 4) 

Tests of Interest 

Test -2*log(Likelihood Ratio) D. F. 

Page 37 of84 

p-value 
The p-value for Test 1 is less than .OS. There appears to be a 

difference between response and/or variances among the dose 

levels, it seems appropriate to model the data. 

The p-value for Test 2 is less than .1. A non-homogeneous 

variance model appears to be appropriate. 

The p-value for Test 3 is greater than .1. The modeled 

variance appears to be appropriate here. 

The p-value for Test 4 is greater than .1. Model 2 seems 

to adequately describe the data. 

The p-value for Test Sa is greater than .1. Model 3 seems 

to adequately describe the data. 

Degrees of freedom for Test Sb are less than or equal to 0. 

The Chi-Square test for fit is not valid. 

The p-value for Test 6a is greater than .1. Model 4 seems 

to adequately describe the data. 

The p-value for Test 6b is greater than .OS. Model 4 does 

not seem to fit the data better than Model 2. 

The p-value for Test 7a is greater than .1. Model s seems 

to adequately describe the data. 

The p-value for Test 7b is greater than .OS. Model s does 

not seem to fit the data better than Model 3. 

Degrees of freedom for Test 7c are less than or equal to 0. 

The Chi-Square test for fit is not valid. 

Benchmark Dose Computations: 

Specified Effect 0.100000 

Risk Type Relative deviation 

Confidence Level 0.9SOOOO 

BMD and BMDL by Model 

Model 

2 

3 

BMD 

O.S48362 

O.S48362 

BMDL 

0.4SS429 0.4SS429 

Page 38 of84 
Q) 

Ul 

c: 

0 

a. 

Ul 

Q) 

0:: 

c: 

IU 

Q) ~ 

3500 3000 2500 2000 

1500 

1000 

500 

0 BMD BMD 

0 2 4 6 

dose 

09:03 06/07 2012 

Page 39 of84 

8 10 

{) 
3000 

Cl) 

Ill 

c: 2500 0 

Q. 

Ill 

Cl) 

0::: 

c: 2000 Ill 

Cl) 

:E 

1500 1000 

500 

0 BMD MD 

0 2 4 6 8 10 

dose 

09:03 06/07 2012 

Page40 of84 
3000 

CD 

II) 

2500 c: 0 

a. 

II) 

CD ~ c: 2000 co 

CD 

:::::!: 

1500 

1000 

500 

0 BMD BMD 

0 2 4 6 8 10 

dose 

09:03 06/07 2012 

Page 41 of84 
3000 

CD 

1/) 

2500 c: 0 

a. 

1/) 

CD 

0::: 

c: 2000 tU 

CD 

::::! 

1500 1000 

500 

0 BMD MD 

0 2 4 6 8 10 

dose 

09:03 06/07 2012 

Page42 of84 
2 42136 U/L 5139.1 6 

3 34790 U/L 2268.7 6 

5 26276 U/L 6965.7 6 

10 24324 U/L 13626.8 6 

Exponential Model. (Version: 1.7; Date: 12/10/2009) 

Input Data File: C:/Usepa/BMDS212/Data/exp_Testrunscontinuous_Setting. (d) 

Gnuplot Plotting File: 

Thu Jun 07 12:33:27 2012 

BMDS Mode 1 Run 

The form of the 

Model 2: 

response function by Model: 

Y[dose] a * exp{sign * b * dose} 

Model 3: 

Model 4: 

Model 5: 

Y[dose] a* exp{sign * (b * dose)Ad} 

Y[dose] a* [c-(c-1) * exp{-b *dose}] 

Y[dose] a* [c-(c-1) * exp{-(b * dose)Ad}l 

Note: Y[dose] is the median response for exposure = dose; 

sign +1 for increasing trend in data; 

sign = -1 for decreasing trend. 

Model 2 is nested within Models 3 and 4. 

Model 3 is. nested within Model 5. 

Model 4 is nested within Model 5. 

Dependent variable = Mean 

Independent variable = Dose 

Data are assumed to be distributed: normally 

variance Model: exp(lnalpha +rho *ln(Y[dose])) 

The variance is to be modeled as Var(i) = exp(lalpha + log(mean(i)) *rho) 

Total number of dose groups = 6 

Total number of records with missing values = 0 

Maximum number of iterations = 250 

Relative Function Convergence has been set to: 1e-008 

Parameter Convergence has been set to: 1e-008 

MLE solution provided: Exact 

Initial Parameter Values 

variable Model 2 Model 3 

Page43 of84 

Model 4 Model 5 
Parameter Estimates by Model 

Variable Model 2 Model 3 Model 4 Model 5 

-------- ------- ------- ------- -------

lnalpha 53.1801 51.8956 63.3822 64.1543 

rho -3.48949 -3.36982 -4.44667 -4.52536 

a 51893.7 51832.1 51979.7 51579.9 

b 0.120147 0.124256 0.184354 0.273658 

c 0.288445 0.421209 

d 1. 03317 1.34443 

Table of Stats From Input Data 

Dose N Obs Mean Obs Std Dev 

---------- -------------

0 6 5.156e+004 1323 

1 6 4.648e+004 2540 

2 6 4.214e+004 5139 

3 6 3.479e+004 2269 

5 6 2.628e+004 6966 

10 6 2.432e+004 1.363e+004 

Estimated Values of Interest 

Model Dose Est Mean Est Std Scaled Residual 

---------- --------- ----------------

2 0 5.189e+004 2095 -0.3925 

1 4.602e+004 2584 0.4381 

2 4.081e+004 3187 1. 02 

3 3.619e+004 3930 -0.8721 

5 2.846e+004 5976 -0.8947 

10 1.561e+004 1.705e+004 1.253 

3 0 5.183e+004 2115 -0.3174 

1 4.616e+004 2571 0.3083 

2 4.088e+004 3155 0.973 

3 3.613e+004 3884 -0.8478 

5 2.812e+004 5927 -0.7619 

10 1. 483e+004 1.742e+004 1.335 

4 0 5.198e+004 1898 -0.5441 

1 4.575e+004 2521 0.7076 

2 4.057e+004 3293 1.162 

3 3.627e+004 4226 -0.8563 

5 2.971e+004 6586 -1.276 

10 2.085e+004 1.447e+004 0.5885 

5 0 5.158e+004 1854 -0.02887 

1 4.678e+004 2312 -0.3207 

2 4.086e+004 3140 0.9933 

3 3.559e+004 4293 -0.4562 

5 2.823e+004 7253 -0.6589 

10 2.235e+004 1.23e+004 0.3934 

Page44 of84 
Model A3: Yij 

Mu(i) + e(ij) 

Var{e(ij)} exp(lalpha + log(mean(i)) *rho) 

· Model R: Yij 

var{e(ij)} 

Mu + e(i) 

SigmaA2 

Likelihoods of Interest 

Model Log(likelihood) 

-------

-----------------

A1 -332.1801 

A2 -312.7243 

A3 -317.7667 

R -3SS.S20S 

2 -319. 7208 

3 -319.6983 

4 -319.2167 

s -317.9674 

Additive constant for all log-likelihoods = 

above values gives the log-likelihood including 

depend on the model parameters. 

DF 

7 

12 

8 

2 

4 

s 

s 

6 

-33.08. 

the term 

Explanation of Tests 

AIC 

------------

678.3602 

649.4486 

6S1.S333 

71S.041 

647.4416 

649.3966 

648.4333 

647.9348 

This constant 

that does not 

added to the 

Test 1: Does response and/or variances differ among Dose levels? (A2 vs. R) Test 2: Are Variances Homogeneous? (A2 vs. A1) 

Test 3: Are variances adequately modeled? (A2 vs. A3) 

Test 4: Does Model 2 fit the data? (A3 vs. 2) 

Test Sa: Does Model 3 fit the data? (A3 vs. 3) 

Test Sb: Is Model 3 better than Model 2? (3 vs. 2) 

Test 6a: Does Model 4 fit the data? (A3 vs. 4) 

Test 6b: Is Model 4 better than Model 2? (4 vs. 2) 

Test 7a: Does Model s fit the data? (A3 vs. S) 

Test 7b: Is Model S better than Model 3? (S vs. 3) 

Test 7C: Is Model s better than Model 4? (S vs. 4) 

Tests of Interest 

I 

Test -2*log(Likelihood Ratio) D. 

--------

------------------------

Test 1 8S.S9 10 

Test 2 38.91 s 

Test 3 10.08 4 

Test 4 3.908 4 

Test sa 3.863 3 

Page45 of84 

F. p-value 

< 0.0001 

< 0.0001 

0.03902 

0.4186 

0.2766 
levels, it seems appropriate to model the data. 

The p-value for Test 2 is less than .1. A non-homogeneous 

variance model appears to be appropriate. 

The p-value for Test 3 is less than .1. You may want to 

consider a different variance model. 

The p-value for Test 4 is greater than .1. Model 2 seems 

to adequately describe the data. 

The p-value for Test Sa is greater than .1. Model 3 seems 

to adequately describe the data. 

The p-value for Test Sb is greater than .05. Model 3 does 

not seem to fit the data better than Model 2. 

The p-value for Test 6a is greater than .1. Model 4 seems 

to adequately describe the data. 

The p-value for Test 6b is greater than .05. Model 4 does 

not seem to fit the data better than Model 2. 

The p-value for Test 7a is greater than .1. Model 5 seems 

to adequately describe the data. 

The p-value for Test 7b is greater than .05. Model 5 does 

not seem to fit the data better than Model 3. 

The p-value for Test 7c is greater than .05. Model 5 does 

not seem to fit the data better than Model 4. 

Benchmark Dose Computations: 

Specified Effect 0.100000 

Risk Type Relative deviation 

Confidence Level 0.950000 

BMD and BMDL by Model 

Model 

2 

3 

4 

5 

BMD 

0.876932 

0. 911454 0.821507 

1.06114 

BMDL 

0.76335 

0.764225 

0.681906 0.774727 

Page 46 of84 

01 
40000 

Q) 

tn 

c 

0 

c. 

tn 

Q) 

0:: 30000 c 

1'0 

Q) 

:E 

20000 

10000 

BMD BMD 

0 2 4 6 8 10 

dose 

12:33 06/07 2012 

Page47 of84 
40000 

Cl) 

1/) 

c: 

0 

c. 

1/) 

Cl) 

0::: 30000 c: 

<U 

Cl) 

:2 

20000 

10000 

BMD MD 

0 2 4 6 8 10 

dose 

12:33 06/07 2012 

Page48 of84 
40000 

Q) 

U) 

r:::: 

0 

c. 

U) 

Q) 

0::: 30000 r:::: 

«< 

Q) 

:::2!: 

20000 

10000 

BMD BMD 

0 2 4 6 8 10 

dose 

12:33 06/07 2012 

Page49 of84 0 
40000 

Q) 

t/) 

c: 

0 

c.. 

t/) 

Q) 

0:::: 30000 c: 

as 

Q) 

::lE 

20000 

10000 

BMD MD 

0 2 4 6 8 10 

dose 

12:33 06/07 2012 

Page 50 of84 
1 2499 U/L 

2 2061 U/L 

3 1701 

5 1453 

468.4 6 

792.5 6 

U/L 934.8 

U/L 408.5 

==================================================================== Exponential Model. (Version: 1.7; Date: 12/10/2009) 

6 

6 

Input Data File: C:/Usepa/BMDS212/Data/exp_Testrunscontinuous_setting. (d) Gnuplot Plotting File : 

Mon Jun 11 12 : 38:17 2012 

==================================================================== 

BMDS Model Run 

The form of the response function by Model: Model 2: Y[dose] a * exp{sign * b * dose} Model 3: Y [dose] a * exp{sign * (b * dose)"d} Model 4: Y[dose] a * [c- (c-1) * exp{-b * dose}] Model 5: Y[dose] a * [c- (c-1) * exp{-(b * dose)"d}J 

Note: Y[dose] is the median response for exposure = dose; sign +1 for increasing trend in data; sign = -1 for decreasing trend . 

Model 2 is nested within Models 3 and 4. 

Model 3 is nested within Model 5. 

Model 4 is nested within Model 5. 

Dependent variable = Mean 

Independent variable = Dose 

Data are assumed to be distributed: normally Variance Model: exp(lnalpha +rho *ln(Y[dose])) The variance is to be modeled as Var(i) = exp(lalpha + log(mean(i)) *rho) 

Total number of dose groups = 5 Total number of records with missing values = 0 Maximum number of iterations = 250 

Relative Function Convergence has been set to: 1e-008 Parameter Convergence has been set to: 1e-008 

MLE solution provided: Exact 

Initial Parameter Values 

Variable Model 2 Model 3 

Page 51 of84 

Model 4 Model 5 
Parameter Estimates by Model 

variable Model 2 Model 3 Model 4 Model 5 

-------- ------- ------- ------- -------

lnalpha -1.94991 117.185 -0.925051 -0.925052 

rho 1. 97589 -13.5129 1.8413 1.8413 

a 2834.45 2128.4 2913.48 2913.48 

b 0.144133 0.0603954 0. 251355 0.251355 

c 0.275837 0.275837 

d 17.4896 1 

Table of Stats From Input Data 

Dose N Obs Mean Obs Std Dev 

---------- -------------

0 6 2928 1188 

1 6 2499 468.4 

2 6 2061 792.5 

3 6 1701 934.8 

5 6 1453 408.5 

Estimated Values of Interest 

Model Dose Est Mean Est Std Scaled Residual 

------- ---------- --------- ----------------

2 0 2834 971.5 0.2359 

1 2454 842.5 0.1308 

2 2125 730.7 -0.2132 

3 1839 633.7 -0.535 

5 1379 476.7 0.3815 

3 0 2128 913.1 2.145 

1 2128 913.1 0.9942 

2 2128 913.1 -0.1808 

3 2128 913.1 -1.147 

5 2128 913.1 -1.812 

4 0 2913 974.2 0.0365 

1 2445 828.9 0.1609 

2 2080 714.3 -0.06469 

3 1796 624.1 -0.3737 

5 1404 497.5 0. 2411 

5 0 2913 974.2 0.0365 

1 2445 828.9 0.1609 

2 2080 714.3 -0.06469 

3 1796 624.1 -0.3737 

5 1404 497.5 0. 2411 

Other models for which likelihoods are calculated: 

Model A1: Yij = Mu(i) + e(ij) 

Page 52 of84 
Likelihoods of Interest 

Model Log(likelihood) 

-------

-----------------

A1 -213.2S86 

A2 -208.8074 

A3 -211.7294 

R -219.SOS8 

2 -211.9663 

3 -219.SOS8 

4 -211.9129 

s -211.9129 

Additive constant for all log-likelihoods = above values gives the log-likelihood including depend on the model parameters. 

DF 

6 

10 

7 

2 

4 

s 

s 

s 

- 27.S7. 

the term 

Explanation of Tests 

AIC 

------------

438.S172 

437.6147 

437.4S88 

443.0117 

431.9327 

449.0117 

433.82S9 

433.82S9 

This constant 

that does not 

added to the 

Test 1: Does response and/or variances differ among Dose levels? (A2 vs. R) Test 2: Are variances Homogeneous? (A2 vs. A1) Test 3: Are variances adequately modeled? (A2 vs. A3) Test 4: Does Model 2 fit the data? (A3 vs. 2) 

Test Sa: Does Model 3 fit the data? (A3 vs. 3) Test Sb : Is Model 3 better than Model 2? (3 vs. 2) 

Test 6a : Does Model 4 fit the data? (A3 vs. 4) Test 6b: Is Model 4 better than Model 2? (4 vs. 2) 

Test 7a: Does Model s fit the data? (A3 vs. S) Test 7b : Is Model s better than Model 3? (S vs. 3) Test 7c : Is Model s better than Model 4? (S vs. 4) 

Tests of Interest 

Test - 2*log(Likelihood Ratio) D. 

--------

------------------------

Test 1 21.4 8 

Test 2 8.903 4 

Test 3 S.844 3 

Test 4 0.4739 3 

Test sa 1S.SS 2 

Test Sb -1S.08 1 

Test 6a 0.367 2 

Test 6b 0.1068 1 

Test 7a 0.367 2 

Test 7b 1S . 19 0 

Page 53 of84 

F. p-value 

0.006164 

0.063S8 

0.1194 

0.9246 

0.000419S 

N/A 

0 . 8323 

0 . 7438 

0.8323 

N/A 
The p-value for Test 3 is greater than .1. The modeled 

variance appears to be appropriate here. 

The p-value for Test 4 is greater than .1. Model 2 seems 

to adequately describe the data. 

The p-value for Test sa is less than .1. Model 3 may not adequately 

describe the data; you may want to consider another model. 

The p-value for Test Sb is less than .OS. Model 3 appears 

to fit the data better than Model 2. 

The p-value for Test 6a is greater than .1. Model 4 seems 

to adequately describe the data. 

The p-value for Test 6b is greater than .OS. Model 4 does 

not seem to fit the data better than Model 2. 

The p-value for Test 7a is greater than .1. 

to adequately describe the data. 

Degrees of freedom for Test 7b are less than 

The Chi-Square test for fit is not valid. 

Degrees of freedom for Test 7c are less than 

The Chi-Square test for fit is not valid. 

Benchmark Dose Computations: 

Specified Effect 0.100000 

Risk Type Relative deviation 

Confidence Level 0.9SOOOO 

BMD and BMDL by Model 

Model 

2 

3 

4 

s 

BMD 

0.73099S 

14 . SS8S 

O.S9121S 

O.S9121S 

BMDL 

0.498177 

0.27478S 

0.2263S 

0.2263S 

Page 54 of84 

Model s seems 

or equal to 0 . 

or equal to 0. 
3500 

3000 

Q) 

fl) 

c: 

0 

c.. 

fl) 

Q) 2500 

0::: 

c: 

Ill 

Q) 

:::!: 2000 

1500 

1000 

500 BMD MD 

0 2 3 4 5 

dose 

12:38 06111 2012 

Page 55 of84 
3500 

3000 

Cl) 

--

U) 

r:::: 

0 -rc. 

U) 

Cl) 2500 

0::: 

r:::: 

111 

Cl) 

::!: 2000 _._ 

-r-

~ 

-

1500 

1000 _._ 

500 BMqL ~Mi 0 2 4 6 8 10 12 14 

dose 

12:38 06/11 2012 

11 

Page 56 of84 
3000 

(J) 

"' c:: 0 

Q. 

"' (J) 2500 a::: 

c:: 

1'0 

(J) ~ 2000 

1500 

1000 

500 BMD 

0 2 3 4 5 

dose 

12:3806/112012 

Page 57 of84 
3500 3000 

Q) 

t/) 

c: 

0 

Q. 

t/) 

Q) 2500 

0:: 

c: 

co Q) 

:!E 2000 

1500 

1000 

500 BMD MD 

0 2 3 4 5 

dose 

12:3806/112012 

Page 58 of84 
2 

3 

5 

887.5 6 

50600 U/L 2619.9 6 

43686 U/L 2300.2 6 

41315 U/L 3712.8 6 

34964 U/L 4661.7 6 

Exponential Model. (Version: 1.7; Date: 12/10/2009) Input Data File: C:/Usepa/BMDS212/Data/exp_Testrunscontinuous_Setting. (d) Gnuplot Plotting File: 

Mon Jun 11 13:01:24 2012 

BMDS Model Run 

The form of the response function by Model: Model 2: Y [dose] a * exp{sign * b * dose} Model 3: Y [dose] a * exp{sign * (b * dose) ... d} Model 4: Y[dose] a * [c- (c-1) * exp{-b * dose}] Model 5: Y[dose] a * [c- (c-1) * exp{-(b * dose) ... d}l 

Note: Y[dose] is the median response for exposure = dose; sign +1 for increasing trend in data; 

sign = -1 for decreasing trend . . 

Model 2 is nested within Models 3 and 4. 

Model 3 is nested within Model 5. 

Model 4 is nested within Model 5. 

Dependent variable = Mean 

Independent variable = Dose 

Data are assumed to be distributed: normally variance Model: exp(lnalpha +rho *ln(Y[dose])) rho is set to 0. 

A constant variance model is fit. 

Total number of dose groups = 5 

Total number of records with missing values = 0 Maximum number o~ iterations = 250 

Relative Function Convergence has been set to: 1e-008 

Parameter Convergence has been set to: 1e-008 

MLE solution provided: Exact 

Initial Parameter Values 

Page 59 of84 
(S) Specified 

Parameter Estimates by Model 

Variable Model 2 Model 3 

-------- ------- -------

lnalpha 16.0798 16.072 

rho 0 0 

a 52979 52657.9 

b 0.0833343 0.0897811 

c d 1. 08599 

Table of Stats From Input Data 

Dose N Obs Mean Obs Std Dev 

---------- -------------

0 6 5.218e+004 1888 

1 6 5.06e+004 2620 

2 6 4.369e+004 2300 

3 6 4.132e+004 3713 

5 6 3.496e+004 4661 

Estimated Values of Interest 

Model Dose Est Mean Est Std 

------

---------- ---------

2 0 5.298e+004 3102 

1 4.874e+004 3102 

2 4.485e+004 3102 

3 4.126e+004 3102 

5 3.493e+004 3102 

3 0 5.266e+004 3090 

1 4.895e+004 3090 

2 4.51e+004 3090 

3 4.14e+004 3090 

5 3.463e+004 3090 

4 0 5.298e+004 3102 

1 4.874e+004 3102 

2 4.485e+004 3102 

3 4.126e+004 3102 

5 3.493e+004 3102 

5 0 5.249e+004 3031 

1 4.967e+004 3031 

2 4.496e+004 3031 

3 4.052e+004 3031 

5 3.511e+004 3031 

Page 60 of 84 · 

Model 4 

16.0798 

0 

52979 

0.0833343 

0 

Scaled Residual 

----------------

-0.6277 

1.466 

-0.9157 

0.04346 

0.03021 

-0.3757 

1. 306 

-1.122 

-0.06482 

0.2629 

-0.6277 

1.466 

-0.9157 

0.04346 0.03021 

-0.2462 

0.7494 

-1.028 

0.6459 

-0.1209 

Model 5 

16.033 

0 

52488.6 

0.322679 0. 627572 

1.64519 
Model A3: Yij Mu(i) + e(ij) 

var{e(ijl} exp(lalpha + log(mean(i)) * rho) 

Model R: Yij Mu + e(i) 

var{e(ij)} Sigma"2 

Likelihoods of Interest 

Model Log (likelihood) DF AIC 

-------

----------------- ------------

A1 -2S4.4003 6 S20.8007 

A2 -2S1.1922 10 S22.384S 

A3 -2S4.4003 6 S20.8007 

R -280.3427 2 S64.68S3 

2 -2S6.1963 3 S18.3926 

3 -2S6.0803 4 S20.1606 

4 -2S6.1963 3 S18.3926 

s -2SS.4949 s S20.9898 

I Additive constant for all log-likelihoods = -27.S7. This constant added to the above values giv~s the log-likelihood including the term that does not depend on the model parameters. 

Explanation of Tests 

Test 1: Does response and/or variances differ among Dose levels? (A2 vs. R) Test 2: Are vartances Homogeneous? (A2 vs. A1) 

Test 3: Are varfances adequately modeled? (A2 vs. A3) Test 4: Does Model 2 fit the data? (A3 vs. 2) 

Test Sa: Does Model 3 fit the data? (A3 vs. 3) I Test Sb: Is Model 3 better than Model 2? (3 vs. 2) 

Test ' 6a: Does Model 4 fit the data? (A3 vs. 4) 

Test 6b: Is Model 4 better than Model 2? (4 vs. 2) 

Test 7a: Does Model s fit the data? (A3 vs. S) 

Test 7b: Is Modet s better than Model 3? (S vs. 3) 

Test 7c: Is Model s better than Model 4? (S vs. 4) 

Tests of Interest 

Test -2*log(Likelihood Ratio) D. F. 

--------

------------------------

Test 1 S8.3 8 

Test 2 6.416 4 

Test 3 6.416 4 

Test 4 3.S92 3 

Test sa 3.36 2 

Page 61 of84 

p-value 

< 0.0001 

0.1701 

0.1701 

0.309 

0.1864

~ 
levels, it seems appropriate to model the data. 

The p-value for Test 2 is greater than .1. A homogeneous 

variance model appears to be appropriate here. 

The p-value for Test 3 is greater than .1. The modeled 

variance appears to be appropriate here. 

The p-value for Test 4 is greater than .1. Model 2 seems 

to adequately describe the data. 

The p-value for Test Sa is greater than . 1. Model 3 seems 

to adequately describe the data. 

The p-value for Test Sb is greater than .OS. Model 3 does 

not seem to fit the data better than Model 2. 

The p-value for Test 6a is greater than .1. Model 4 seems 

to adequately describe the data. 

Degrees of freedom for Test 6b are less than or equal to o. 

The Chi-Square test for fit is not valid. The p-value for Test 7a is greater than .1. Model S seems 

to adequately describe the data. 

The p-value for Test 7b is greater than .OS. Model S does 

not seem to fit the data better than Model 3. 

The p-value for Test 7c is greater than .OS. Model S does 

not seem to fit the data better than Model 4. 

Benchmark Dose computations: 

Specified Effect 0.100000 

Risk Type Relative deviation 

Confidence Level 0.9SOOOO 

BMD and BMDL by Model 

Model 

2 

3 

4 

s 

BMD 

1. 26431 

1.40241 

1. 26431 

1. S2871 

BMDL 

1.08907 

1. 09607 

0.9294S8 

1. 02944 

Page 62 of84 
Q) 45000 Ill 

c: 

0 

c.. 

Ill 

Q) 

0::: 

c: 

(U 40000 Q) 

:::::!!: 

35000 

30000 

BMD BMD 

0 1 2 3 4 5 

dose 13:01 06/11 2012 

Page 63 of84 
50000 

Q) 45000 

1/) 

c: 

0 

c.. 

1/) 

Q) 

a: 

c: 

«< 40000 Q) :::!: 

35000 

30000 

0 2 3 4 5 

dose 

13:01 06/11 2012 

Page 64 of84 
CD 45000 

U) 

c: 

0 

c.. 

U) 

CD 

0::: 

c: 

IV 

CD 40000 :E 

35000 

30000 

0 2 3 4 5 

dose 13:01 06111 2012 

Page 65 of84 
Cl) 45000 rn 

c::: 

0 

0.. 

rn 

Cl) 

a::: 

c::: 

CQ 

Cl) 40000 ~ 35000 

30000 

0 2 3 4 5 

dose 

13:01 06/11 2012 

Selected BMDS output for Likelihood Ratio Test: 

Exponential model (heterogeneous variance) Female PNDll RBC: 

Likelihoods of Interest 

Model Log (likelihood) DF AIC 

------- ----------------- ------------

A1 -281.4468 5 572.8935 

A2 -273.2373 8 562.4745 

A3 -278.2065 6 568.4131 

R -301.4351 2 606.8702 

2 -284.6608 4 577.3215 

3 -284.6608 4 577.3215 

4 -278.8974 5 567.7947 

5 -278.8974 5 567.7947 

Additive constant for all log-likelihoods = -34. This constant added to the 

above values gives the log-likelihood including the term that does not 

depend on the model parameters. 

Page 66 of84 
9 6 527.2678 

R -281.9828 2 567.9655 2 -257.8321 4 523.6641 

3 -499.1267 4 1006 . 253 

4 -257.6347 5 525.2694 

5 -257.6347 5 525.2694 

Additive constant for all log-likelihoods = -32.16. This constant added to the above values gives the log-likelihood including the term that does not depend on the model parameters . 

Exponential Model (heterogeneous variance ) combined PND 11 RBC : 

Likelihoods of Interest 

Model Log (likelihood) 

-------

-----------------

A1 -544.8439 

A2 -539.0674 

A3 -541.3211 

R -584.2958 

2 -545.789 

3 -890.5382 

4 -541.693 

5 -541.693 

Additive constant for all log-likelihoods = above values gives the log-likelihood including depend on the model parameters. 

Page 67 of84 

DF 

5 

8 

6 

2 

4 

4 

5 

5 

-66.16. 

the term 

AIC 

------------

1099.688 

1094.135 

1094.642 

1172.592 

1099.578 

1789.076 

1093.386 

1093.386 

This constant 

that does not 

added to the 
=============================================================

 

BMDS Model Run 

The form of the response function is: 

Dependent variable = mean 

Independent variable = dose 

Power parameter restricted to be greater than 1 

The variance is to be modeled as Var(i) = exp(lalpha +rho* ln(mean(i))) 

Total number of dose groups = 4 

Total number of records with missing values = 0 

Maximum number of iterations = 250 

Relative Function Convergence has been set to: 1e-008 

Parameter Convergence has been set to: 1e-008 

Default Initial Parameter Values 

lalpha 14.1917 

rho 0 

intercept 

v 

n 

k 

6865.67 

-4466.78 

8.77777 

0.211717 

Asymptotic Correlation Matrix of Parameter Estimates 

( *** The model parameter(s) -n 

have been estimated at a boundary point, or have been specified by 

the user, 

and do not appear in the correlation matrix 

lalpha rho intercept v k 

lalpha 1 -1 0.14 -0.13 -0.056 

rho -1 1 -0.15 0.13 0.056 

intercept 0.14 -0.15 1 -0.2 -0.61 

v -0.13 0.13 -0.2 1 -0.59 

k -0.056 0.056 -0.61 -0.59 1 

Page 68 of84 
tercept 6839.55 330.275 

7486.87 

v -5892.8 572.828 4770.08 

n 1 NA 

k 0.325016 0.115836 0.552051 

NA - Indicates that this parameter has hit a bound implied by some inequality constraint and thus has no standard error. 

Table of Data and Estimated Values of Interest 

6192.22 

-7015.53 

0.0979805 

Dose N Obs Mean Est Mean Obs Std Dev Est Std Dev Scaled Res. 

-------- --------

-----------

0 18 6.87e+003 6.84e+003 1.61e+003 

0.1 17 5.42e+003 5.45e+003 943 

0.3 19 4.01e+003 4.01e+003 1.31e+003 

1 18 2.4e+003 2.39e+003 760 

Model Descriptipns for likelihoods calculated 

Model A1: Yij 

Var{e·(ij}} I 

Model A2: Yij 

Var{eJ(ij}} 

Mu(i} + e(ij} 

Sigma"2 

Mu(i} + e(ij} 

Sigma(i}"2 

Model A3: Yij Mu(i} + e(ij} 

-----------

1.46e+003 

1. 28e+003 

1.07e+003 

789 

Var{e(ij}} exp(lalpha + rho*ln(Mu(i}}} Model A3 uses any fixed variance parameters that 

were specified by the user 

Model R: Yi 

var{e(i}} 

Model 

A1 

A2 

A3 

fitted 

R 

Mu + e(i} 

Sigma"2 

Likelihoods of Interest 

Log (likelihood} # Param•s 

-544.843935 5 

-539.067392 8 

-541.321057 6 

-541.453167 5 

-584.295799 2 

Page 69 of84 

AIC 

1099.687870 

1094.134785 

1094.642113 

1092.906334 

1172.591599 

----------

0.0757 

-0.116 

0.00464 

0.036 

qo I 
Test 

Test 

Test 

Test 

Test 

1 

2 

3 

4 

Tests of Interest 

-2*log(Likelihood Ratio) Test df p -value 

90.4568 6 <.0001 

11.5531 3 0 . 009082 

4.50733 2 0.105 

0.264221 1 0. 6072 

The p-value for Test 1 is less than .05. There appears to be a 

difference between response and/or variances among the dose levels 

It seems appropriate to model the data 

The p-value for Test 2 is less than .1. A non-homogeneous variance 

model appears to be appropriate 

The p-value for Test 3 is greater than .1. The modeled variance appears 

to be appropriate here 

The p-value for Test 4 is greater than .1. The model chosen seems 

to adequately describe the data 

Benchmark Dose Computation 

Specified effect 0.1 

Risk Type Relative risk 

Confidence level 0 . 95 

BMD 0.0426766 

BMDL 0.0285396 

Page 70 of84 
6000 

Q) 

Ul 

r::: 

0 

Q. 

Ul 5000 Q) 

0::: 

r::: 

IV 

Q) 

::::! 

4000 

3000 

2000 

BMD BMD 

0 0.2 0.4 0.6 0.8 

dose 11:07 08/14 2012 

Page 71 of84 
Gnuplot Plotting File: 

Thu Aug 16 11:12:56 2012 

BMDS Model Run 

The form of the response function by Model: 

Model 2: Y [dose] a * exp{sign * b * dose} 

Model 3: Y [dose] a * exp{sign * (b * dose)Ad} 

Model 4: Y[dose] a * [c- (c-1) * exp{-b * dose}] 

Model 5: Y[dose] a * [c- (c-1) * exp{-(b * dose)Ad}l 

Note: Y[dose] is the median response for exposure = dose; 

sign +1 for increasing trend in data; 

sign = -1 for decreasing trend. 

Model 2 is nested within Models 3 and 4. 

Model 3 is nested within Model 5. 

Model 4 is nested within Model 5. 

Dependent variable = mean 

Independent variable = Dose 

Data are assumed to be distributed: normally 

Variance Model: exp(lnalpha +rho *ln(Y[dose])) 

The variance is to be modeled as Var(i) = exp(lalpha + log(mean(i)) *rho) 

Total number of dose groups = 6 

Total number of records with missing values = 0 

Maximum number of iterations = 250 

Relative Function Convergence has been set to: 1e-008 

Parameter Convergence has been set to: 1e-008 

MLE solution provided: Exact 

Initial Parameter Values 

Variable Model 2 Model 3 

-------- ------- -------

lnalpha 7.48339 7.48339 

rho 0.731572 0. 731572 

a 1106.16 1106.16 

b 0.132095 0.132095 

c 

0.236888 

d 1 

Parameter Estimates by Model 

Page 72 of84 

Model 4 

-------

7.48339 

0.731572 

3227.7 

0.385352 

0.236888 

Model 5 

-------

7.48339 

0.731572 

3227.7 

0.385352 

1 
p

ata 

Dose N Obs Mean Obs Std Dev 

---------- -------------

0 12 3074 1014 

1 12 2598 593.1 

2 12 2110 684.4 

3 12 1608 772.2 

5 12 1350 413.1 

10 12 802.8 565.8 

Estimated Values of Interest 

Model Dose Est Mean Est Std 

-------

---------- ---------

2 p 2929 783.1 

1 2522 748.3 

2 2171 715.1 

B 1869 683.4 

5 1385 624.1 

10 654.4 497.4 

3 0 2929 783.1 

1 2522 748.3 

2 2171 715.1 

3 1869 683.4 

5 1385 624.1 

10 654.4 497.4 

4 0 3134 824.7 

1 2520 753.9 

2 2061 694.1 

3 1719 644 

5 1271 568.8 

10 836.8 478.9 

5 0 3119 822.7 

1 2537 755.8 

2 2070 695.1 

3 1716 643.6 

5 1258 566.4 

10 841.4 480.1 

Other models for which likelihoods are calculated: 

Model A1: Yij = Mu(i) + e(ij) 

Var{e(ij)} = SigmaA2 

Model A2: Yij 

Var{e(ij)} 

Mu(i) + e(ij) 

Sigma(i)A2 

Model A3: Yij = Mu(i) + e(ij) 

scaled Residual 

----------------

0.6392 

0.3538 

-0.2965 

-1.322 

-0.1938 

1.034 

0.6392 

0.3538 

-0.2965 

-1.322 

-0.1938 

1.034 

-0.2525 

0.3582 

0.2398 

-0.596 

0.479 

-0.2459 

-0.19 

0.2788 

0.1962 

-0.5837 

0.5599 

-0.278 

Var{e(ij)} = exp(lalpha + log(mean(i)) *rho) 

Page 73 of84 
A2 

A3 

R 

2 

3 

4 

s 

-499.0298 12 

-S02.2S09 8 

-S34.4764 2 

-S04.3179 4 

-S04.3179 4 

-S02.3881 s 

-S02.3774 6 

1022.06 

1020.S02 

1072.9S3 

1016.636 

1016.636 

1014.776 

1016.7SS 

Additive constant for all log-likelihoods = -66.16. This constant added to the 

above values gives the log-likelihood including the term that does not 

depend on the model parameters. 

Explanation of Tests 

Test 1: Does response and/or variances differ among Dose levels? (A2 vs. R) 

Test 2: Are Variances Homogeneous? (A2 vs. A1) 

Test 3: Are variances adequately modeled? (A2 vs. A3) 

Test 4: Does Model 2 fit the data? (A3 vs. 2) 

Test Sa: Does Model 3 fit the data? (A3 vs 3) 

Test Sb: Is Model 3 better than Model 2? (3 vs. 2) 

Test 6a: Does Model 4 fit the data? (A3 vs 4) 

Test 6b: Is Model 4 better than Model 2? (4 vs. 2) 

Test 7a: Does Model s fit the data? (A3 vs S) 

Test 7b: Is Model s better than Model 3? (S vs. 3) 

Test 7c: Is Model s better than Model 4? (S vs. 4) 

Tests of Interest 

Test -2*log(Likelihood Ratio) D. F . 

-------- ------------------------

Test 1 70.89 10 

Test 2 10.92 s 

Test 3 6.442 4 

Test 4 4.134 4 

Test Sa 4.134 4 

Test Sb -9.3e-011 0 

Test 6a 0.2744 3 

Test 6b 3.86 1 

Test 7a 0.2S31 2 

Test 7b 3.881 2 

Test 7c 0.02129 1 

p-value 

--------------

< 0.0001 

O.OS29 

0.168S 

0.3882 

0.3882 

N/A 

0.9648 

0.04946 

0.8811 

0.1436 

0 . 884 

The p-value for Test 1 is less than .OS. There appears to be a 

difference between response and/or variances among the dose 

levels, it seems appropriate to model the data. 

Page 74 of84 
q

y 

data. 

Degrees of freedom for Test Sb are less than or equal to 0. The 

Chi~square test for fit is not valid. 

The p-value for Test 6a is greater than .1. Model 4 seems to adequately describe the data. 

The p-value for Test 6b is less than .05. Model 4 appears to fit the data better than Model 2. 

The p-value for Test ?a is greater than .1. Model 5 seems to adequately describe the data. 

The p-value for' Test 7b is greater than .05. Model 5 does not seem to fit 1 the data better than Model 3. 

The p-value for Test 7c is greater than .05. Model 5 does not seem to fit the data better than Model 4. 

Benchmark Dose Computations: 

Specified Effect 0.100000 

Risk Type Relative deviation 

Confidence Level 0.950000 

Model 

2 

3 

4 

5 

BMD and BMDL by Model 

BMD 

I 

------------

0.702937 

0.702937 

. 0. 474181 

0.51859 

BMDL 

0.557075 

0.557075 

0.339178 

0.339621 

Page 75 of84 
5l 2500 

c: 

&. 

.., ~ 2000 

c: 

Ill 

CD 

::!: 

1500 

1000 

500 

BMD MD 

0 2 4 6 8 10 

dose 

11 :12 08116 2012 

Page 76 of84 
3! 

c: 

0 

D. 

& 

c: 

:l ~ 

2500 2000 1500 1000 500 11:12 08116 2012 4000 3500 3000 2500 2000 

1500 

1000 

500 

11 :12 08/16 2012 

BMD MD 

0 

BMD MD 

0 

2 4 6 8 10 

dose 

Exponential Model 4 with 0.95 Confidence Level 

Exponential 

2 4 6 8 10 

dose 

Page 77 of84 
5l 2500 

c 

0 

a. 

XI 

a: 2000 

c 

al 

Q) 

::::!! 

1500 

1000 

500 

BMD MD 

0 2 4 6 8 10 

dose 

11:12 08/16 2012 

Page 78 of84 
Thu Aug 16 12:06:49 2012 

==================================================================== 

BMDS Model Run 

The form of the 

Model 2: 

Model 3: 

Model 4: 

response function by Model: 

Y[dose] a * exp{sign * b * dose} Y[dose] a * exp{sign * (b * dose)Ad} Y[dose] a* [c-(c-1) * exp{-b *dose}] Model 5: Y [dose] a * [c- (c-1) * exp{- (b * dose) Ad}] 

Note: Y[dose] is the median response for exposure = dose; sign +1 for increasing trend in data; sign = -1 for decreasing trend. 

Model 2 is nested within Models 3 and 4. 

Model 3 is nested within Model 5. 

Model 4 is nested within Model 5. 

Dependent variable = mean 

Independent variable = Dose 

Data are assumed to be distributed: normally Variance Model: exp(lnalpha +rho *ln(Y[dose])) The variance is to be modeled as Var(i) = exp(lalpha + log(mean(i)) *rho) 

Total number of dose groups = 6 

Total number of records with missing values = 0 Maximum number of iterations = 250 

Relative Function Convergence has been set to: 1e-008 Parameter Convergence has been set to: 1e-008 

MLE solution provided: Exact 

Variable 

lnalpha 

0.458415 

rho 

a 

b 

c 

d 

Variable 

Model 2 

67.4078 

-4.79547 

30110 

0.0704899 

Model 2 

Initial Parameter Values 

Model 3 

67 . 4078 

-4.79547 

30110 

0.0704899 

1 

Parameter Estimates by Model 

Model 3 

Page 79 of84 

Model 4 

67.4078 

-4.79547 

54464.4 

0.313747 

0.458415 

Model 4 

Model 5 

67.4078 

-4.79547 

54464.4 

0.313747 

1 

Model 5 

}00 
Dose N Obs Mean Obs Std Dev 

---------- -------------

0 12 5.187e+004 1588 

1 12 4.854e+004 3268 

2 12 4.291e+004 3881 

3 12 3.776e+004 4438 

5 12 3.062e+004 7247 

10 12 2.622e+004 1.094e+004 

Estimated Values of Interest 

Model Dose Est Mean Est Std 

------- ---------- ---------

2 0 5.229e+004 2473 

1 4.736e+004 2953 

2 4.289e+004 3526 

3 3.885e+004 421.0 

5 3.187e+004 6003 

10 1.943e+004 1.457e+004 

3 0 5.229e+004 2473 

1 4.736e+004 2953 

2 4.289e+004 3526 

3 3.885e+004 4210 

5 3.187e+004 6003 

10 1.943e+004 1.457e+004 

4 0 5.25e+004 2280 

1 4.706e+004 2901 

2 4.25e+004 3631 

3 3.868e+004 4469 

5 3.279e+004 6430 

10 2.464e+004 1.207e+004 

5 0 5.199e+004 2171 

1 4.831e+004 2571 

2 4.291e+004 3379 

3 3.783e+004 4518 

5 3.083e+004 7241 

10 2.629e+004 1.045e+004 

Other models for which likelihoods are calculated: 

Model A1: Yij 

Var{e(ij)} 

Model A2: Yij 

Var{e(ij)} 

Model A3: Yij 

Mu(i) + e(ij) 

Sigma ... 2 

Mu(i) + e(ij) 

Sigma(i)"2 

Mu(i) + e(ij) 

Scaled Residual 

----------------

-0.5866 

1. 385 

0.01581 

-0.9012 

-0.7219 

1.614 

-0.5866 

1. 385 

0.01581 

-0.9012 

-0.7219 

1. 614 

-0.9555 

1. 768 

0. 3913 

-0.7163 

-1.171 

0.4512 

-0.1973 

0.3049 

-0.002005 

-0.05872 

-0.1 

-0.02404 

var{e(ij)} exp(lalpha + log(mean(i)) *rho) 

Page 80 of84 
R -70S . 0244 

2 -643.2422 

3 -643.2422 

4 -641.6889 

s -638.619S 

Additive constant for all log-likelihoods = above vall es gives the log-likelihood including depend on the model parameters. 

8 

2 

4 

4 

s 

6 

-66.16. 

the term 

Explanation of Tests 

I 

1293.208 

1414.049 

1294.484 

1294.484 

1293.378 

1289.239 

This constant 

adde~ 

that does not 

Test I 1: Does response and/or variances differ among Dose levels? (A2 vs. R)' Test 2 : Are Variances Homogeneous? I (A2 vs. A1) Test 3 : Are variances adequately modeled? (A2 vs. A3) Test 4: Does 

I 

Model 2 fit the data? (A3 vs. 2) 

I 

Test Sa: koes Model 3 fit the data? (A3 VS 3) Test Sb: s Model 3 better than Model 2? (3 vs. 2) I 

I 

fit the data? (A3 VS 4) Test 6a: poes Model 4 Test 6b: Is Model 4 better than Model 2? (4 vs. 2) i 

I 

Test 7a: boes Model s fit the data? (A3 VS S) Test 7b: Is Model s better than Model 3? (S vs. 3) Test 7c: Is Model s better than Model 4? (S vs. 4) 

Tests of Interest 

Test -2*log(Likelihood Ratio) D. F. p-value --------

------------------------

--------------

Test 1 136.8 10 < 0.0001 Test 2 46.6 s < 0.0001 Test 3 3.969 4 0.4103 Test 4 9.277 4 O.OS4S4 Test Sa 9 . 277 4 O.OS4S4 Test Sb I 2.274e-013 0 N/A Test 6a 6.17 3 0.1036 Test 6b 3 . 107 1 0.07798 Test 7a 0.03139 2 0.9844 Test 7b 9.24S 2 0.009826 Test 7c 6 . 139 1 0.01322 

The p-value for Test 1 is less than .OS. There appears to be a differeh ce between response and/or variances among the dose levels, J, it seems appropriate to model the data. 

I' The p-value for Test 2 is less than .1 . A non-homogeneous 

Page 81 of84 

to the 
I 

f 

' I 

{ 

I 

I 

I 

i 

I 

! 

i 

.I 

I 

! 

I 

Degrees of freedom for Test Sb are less than or equal to 0. 

The Chi-Square test for fit is not valid. 

The p-value for Test 6a is greater than .1. Model 4 seems 

to adequately describe the data. 

The p-value for Test 6b is greater than .OS. Model 4 does 

not seem to fit the data better than Model 2. 

The p-value for Test 7a is greater than .1. Model S seems 

to adequately describe the data. 

The p-value for Test 7b is less than .OS. Model S appears 

to fit the data better than Model 3. 

The p-value for Test 7c is less than .OS . Model s appears 

to fit the data better than Model 4. 

Benchmark Dose Computations: 

Specif"ied Effect 0.100000 

Risk Type Relative deviation 

Confidence Level 0.9SOOOO 

BMD and BMDL by Model 

Model 

2 

3 

4 

s 

BMD 

1.06402 

1.06402 

0 . 961987 

1. 28942 

BMDL 

0.944464 

0.944464 

0.822887 

1. 03778 

Page 82 of84 
CD 

.., 40000 

r:: 

0 

c. 

.., 

CD 

a:: 35000 r:: 

Ill 

Q) 

:::.! 

30000 

25000 

20000 

BMD MD 

0 2 4 6 8 10 

dose 

12:06 08/16 2012 

Exponential Model 3 with 0.95 Confidence Level 

55000 Exponential 

50000 

45000 

Q) 

.., 4oobo 

r:: 

0 

c. 

.., 

Q) 

a:: 35000 r:: 

Ill 

CD 

:::.! 

30000 

25000 

20000 

BMD BMD 

0 2 4 6 8 10 

dose 

12:06 08/16 2012 

Page 83 of84 )0 
CD 40000 Ill 

c: 

0 

c. 

Ill 

(!}_ 35000 c: 

Ill 

CD 

::!! 

30000 

25000 

20000 

BMD MD 

0 2 4 6 8 10 

dose 

12:06 08/16 2012 

Exponential Model 5 with 0.95 Confidence Level 

55000 Exponential 50000 

45000 

CD 40000 Ill 

c: 

0 

c. 

Ill 

(!}_ 35000 c: 

Ill 

CD 

::!! 

30000 

25000 

20000 

BMD MD 

0 2 4 6 8 10 

s dose t -12:06 08/16 2012 0 Page 84 of84