# Presentation: 632511

## Consideration of Investigational Pharmacokinetic Studies to Identify Patient Populations at Risk: Methods Used to Adjust Dose Given the Availability of Exposure-Response Information

**Case Studies and A Method for the Future**

**Consideration of Investigational Pharmacokinetic Studies to Identify Patient Populations at Risk: Methods Used to Adjust Dose Given the Availability of Exposure-Response Information**

- ACPS CPSC Meeting
- October 23, 2002
- Peter Lee, PhD
- Pharmacometrics, OCPB

## Clinical Pharmacology Studies: Input on Safety and Efficacy

- NDAs may contain up to 20 or more clinical pharmacology studies.
- Intrinsic/extrinsic factors result in increase or decrease in exposure due to change in pharmacokinetics.
- Need consistent approaches to determine dosing adjustment in special populations.

## Examples of Intrinsic/ Extrinsic Factors That Define Special Populations

- Drug-drug interactions
- Diseases: hepatic and renal impairments
- Age: elderly and pediatrics
- Sex and ethnicity
- Food: high fat and juice
- Formulation and regimen

**(ICH E5)**

## An Example of Changes in Exposure Due to In-/Ex-trinsic Factors:When Should Dose be Adjusted ?

- * no: no dosing adjustment recommended in the proposed label

**Change in AUC**

**no**

**no**

**no**

**no**

**no**

**not clin sig**

**caution**

**no **

**no **

**caution**

**not clin sig **

**Difference in AUC**

## Draft Regulatory Guidancefor Industry on Exposure-Response

- “*Exposure-response* information can sometimes be used to support use, without further clinical data, of a drug in a new target population by showing similar (or altered in a defined way) concentration-response relationships ...”
- How ? Standard ? Criteria ?

- Ref: www.fda.gov

## Evidence of Effectiveness Guidance For Industry 

- “ ... if there is a well-understood relationship between *blood concentration and response*, including an understanding of the time course of that relationship, it may be possible to conclude that a new dose, regimen, or dosage form is effective on the basis of PK data without an additional clinical efficacy trial.”
- How ? Standard ? Criteria ?

- Ref: www.fda.gov

## ICH Guidance on Dose Response

- “... *(**concentration response**)* may be useful for ascertaining the magnitude of the clinical consequences of PK differences, such as those due to drug-disease or drug-drug interactions, or assessing the effects of the altered PK of new dosage forms or new dosage regimens without need for additional clinical trial data ...“
- How ? Standard ? Criteria ?

- Ref: www.fda.gov

## Regulatory Guidance on Drug-Drug Interaction

- “Assuming unchanged PK/PD relationships, changes may be evaluated by comparing pharmacokinetic measures of systemic exposure that are most relevant to an understanding of relationship between *dose (exposure) and therapeutic outcome*“
- Similar statements in renal, general BA/BE, and hepatic guidances

- Ref: www.fda.gov

## Draft OCPB Good Review Practice (GRP) MaPP

- Question Based Review - Section IV. C. intrinsic factors
- Based upon what is known about *exposure-response* relationships and their variability, and the groups studied (volunteers vs. patients); what dosage regimen adjustments, if any, are recommended for each of these subgroups?  If dosage regimen adjustments are not based upon exposure-response relationships, describe the alternative basis for the recommendation.
- age, gender, race, weight, height, disease, genetic polymorphism, pregnancy, and organ dysfunction

## Draft OCPB Good Review Practice (GRP) MaPP (Cont.)

- Question Based Review - Section IV. D. extrinsic factors
- Based upon what is known about *exposure-response* relationships and their variability, what dosage regimen adjustments, if any, do you recommend for each of these factors?  If dosage regimen adjustments across factors are not based on the exposure-response relationships, describe the basis for the recommendation.
- drugs, herbal products, diet, smoking, and alcohol use

## An Example of Consistent Dosing Adjustment Based on In-/Ex-trinsic Factors

**Difference in AUC**

## An Example of Inconsistent Dosing Adjustment in Proposed Label

**Difference in AUC**

**Drug Y**

**Given before **
**meal**

**Sig. DDI**

**Dose adj.**

## Issues Related to Dosing Adjustment in Drug Labels of NDA Submissions

- Inconsistency in dosing adjustments is frequently seen in initial label language of NDA submissions.
- Exposure-response information needed for rational dosing adjustment is sometimes incomplete or unavailable in the NDAs.
- Additional exposure-response analyses are usually required and conducted by FDA reviewers to address questions of dosing adjustment.
- Standard for analyzing and interpreting exposure-response data for safety and effectiveness assessments of drugs would be beneficial to decision-making.

## Considerations in Using E-R for Dosing Adjustment  

- Limited availability of E-R data
- Selecting and combing E-R studies
- Quality and quantity (power) of the data
- Model building and verification
- Interpretation of the E-R model results
- Standard outputs
- Criteria for dosing adjustment

## To Improve the Current Status, We Propose To ...

- Develop and evaluate a standard approach for reviewers to quantitatively assess the impact of exposure change on either safety or efficacy that result from change in pharmacokinetics due to intrinsic or extrinsic factors.

## Flowchart of Using Exposure-Response Information for Dosing Adjustment Recommendations

**2.  Are the pooled studies  powered for determining E-R relationships ?  **

**3.  Define the goalpost based on the pivotal E-R relationships**

**Y**

**4.  Use the goalpost set in the respective guidance**

**N**

**Flowchart of Using Exposure-Response Information for Dosing Adjustment Recommendations**

**Q#1**

**Q#2**

**Q#3**

## Why Need A Standardized Output ?

- There are many exposure-response models with a range of complexity
- To establish standardized approach for interpreting the exposure-response data
- To communicate useful and understandable information to other disciplines
- To facilitate rational use of exposure-response information in regulatory decisions

## Proposed Standardized Outputs of E-R Results

- Present in term of probability

- Exposure

- Response Variable

- Frequency

- ref

- test

- E+

- Response

- Frequency

- ref

- test

**Probability**
**of clinical**
**significant**
**response **

**=**

- Exposure

## Interpreting The Significance of PK Change

- Usually limited to interpolation; ie, interpreting change in PK within the observed E-R data.
- Re-sampling of PK & E to determine the change in response with different covariates.
- Estimate the percentage (probability) in the patient population with the response > the clinically significant “critical value”.

## Example: Oncology Drug A

- Responses (clinical outcomes):
- Effectiveness: Time to death, hematologic / cytogenetic response
- Safety: Neutropenia (Grade 0, 1, 2, 3, 4)
- Intrinsic/extrinsic factors studied
- Drug-drug interaction
- Body weight
- Age

## Exposure-Safety Relationship

- (Nonlinear Mixed Effect Modeling)

- AE (Prob > Grade 2)

**Drug Conc.**

**Age**

**Critical value of AE = Grade 2**

## ‘Probability’ of AE: Related to PK Change due to Body Weight

- ‘Probability’ of AE: Related to PK Change due to Body Weight

- Probability of AE > Grade 2

## ‘Probability’ of AE: Effect of Ketoconazole on Drug A in Age Groups

- ‘Probability’ of AE: Effect of Ketoconazole on Drug A in Age Groups

- Probability of AE > Grade 2

**Age = 20 y**

**Age = 65 y**

## Example: Anti-infective Drug B

- Nonlinear kinetics in clearance
- Intrinsic factors
- Special populations
- 100% increase in elderly
- 40% increase in mild/severe renal impairment
- Extrinsic factors
- Drug-drug interactions
- Ketoconazole causes 95% increase in AUC

## Delta QTc vs Concentration by Linear and Linear Mixed-Effects Model

- QTc = -1.30 + 3.90*concentration

## ‘Probability’ of QTc Change in the Elderly due to Plasma Concentration of Drug B Alone at Clinical Dose

## ‘Probability’ of QTc Change in Elderly due to Drug B and Ketoconazole Interaction

## Summary of Above 2 Examples

- Safety assessment of intrinsic/extrinsic factors has become a routine part of pre-approval risk management.
- Exposure-response information provides rational basis for dosing adjustment.
- Estimating probability of adverse effect allows identification of populations at risk.
- Standardized approach for interpreting E-R data ensures the consistent assessment across review divisions and should improve the information in drug labels.

## Current Approaches for Dosing Adjustments in FDA Guidances

- Set the “no effect boundary”
- If exposure-response data are available
- adjust the no effect boundaries according to data
- If exposure-response data are not available
- default goalpost (eg, 80-125%)
- If there is significant change in PK beyond the no effect boundaries due to in-/ex-trinsic factors
- Apply concentration response information for determining dosing adjustment, precaution, warning, etc.

## Proposed Decision Tree for Dosing Adjustment Recommendations (TBD)

**Is PK/PD available ?**

**Default goal post **
**for AUC and Cmax**

**Can “no effect boundaries” be defined based on E-R ?**

**If the 90% CI of test/ref is within the boundaries**

**y**

**n**

**No dose adjustment**

**Dosing adjustment, precaution, or warning**

**y**

**n**

**y**

**n**

**?**

## Remaining Issues (Questions to the Committee)

- What are the acceptable study designs that provide reliable data to establish exposure-response relationship for dosing adjustment ?
- How to model incomplete E-R data ?
- How to assess the risk and benefit of drug exposures that are not contained within the known E-R relationship ?
- How to establish consistent criteria for determining the no effect boundaries for change in pharmacokinetics for dosing adjustment ?

## Remaining Issues (Questions to the Committee)

- What are the acceptable study designs that provide reliable data to establish exposure-response relationship for dosing adjustment ?
- How to model incomplete E-R data ?
- How to assess the risk and benefit of drug exposures that are not contained within the known E-R relationship ?
- How to establish consistent criteria for determining the no effect boundaries for change in pharmacokinetics for dosing adjustment ?

## Q1: Study Design

- Two approaches recommended (in the draft Exposure-Response Guidance)
- observing the plasma concentrations attained in patients who have been given various doses of drug, and relating the plasma concentrations to observed response;
- assigning patients randomly to desired plasma concentrations, titrating dose to achieve them, and relating the concentration to observed response.

## Q1: Considerations in Exposure-Response Study Design

## Remaining Issues (Questions to the Committee)

- What are the acceptable study designs that provide reliable data to establish exposure-response relationship for dosing adjustment ?
- _How to model incomplete E-R data ?_
- How to assess the risk and benefit of drug concentrations that are not contained within the known E-R relationship ?
- How to establish consistent criteria for determining the no effect boundaries for change in pharmacokinetics for dosing adjustment ?

## Q2: Incomplete E-R DataExample: A CNS Drug

## Example: Another CNS Drug

**?**

## Issues Related to the Previous Two Examples

- Shape of the exposure-response curve: monotonous vs U-shape, linear vs nonlinear.
- What is the model describing the data ?
- Emax, linear, sigmoid, polynomial, exponential, segmentation

## Remaining Issues (Questions to the Committee)

- What are the acceptable study designs that provide reliable data to establish exposure-response relationship for dosing adjustment ?
- How to model incomplete E-R data ?
- _How to assess the risk and benefit of drug concentrations that are not contained within the known E-R relationship ?_
- How to establish consistent criteria for determining the no effect boundaries for change in pharmacokinetics for dosing adjustment ?

## Q3 Example: A Cardio-Vascular Drug

## Safety D-R (20-160 mg)

**Ref dose**

## Issues Related to the CV Drug

- What can be concluded for dosing adjustment if we don’t have a complete E-R curve ?
- PK range of the E-R curve < PK due to in-/ex-trinsic factors.
- The “critical AE” is not within the range of known E-R curve.
- The direction of E-R trend beyond the observed concentration range cannot be determined.
- Use the default goalpost in the respective guidance ?

## Proposed Decision Tree for dosing adjustment Recommendations (TBD)

**Is PK/PD available ?**

**Default goal post **
**for AUC and Cmax**

**Can “no effect boundaries” be defined based on E-R ?**

**If the 90% CI of test/ref is within the boundaries**

**y**

**n**

**No dose adjustment**

**Dosing adjustment, precaution, or warning**

**y**

**n**

**y**

**n**

**?**

## Remaining Issues (Questions to the Committee)

- What are the acceptable study designs that provide reliable data to establish exposure-response relationship for dosing adjustment ?
- How to model incomplete E-R data ?
- How to assess the risk and benefit of drug concentrations that are not contained within the known E-R relationship ?
- _How to establish consistent criteria for determining the no effect boundaries for change in pharmacokinetics for dosing adjustment ?_

## Q4: Establishing “No Effect Boundary”

- Interpret the clinical significance of change in response, and establish the “critical value”.
- Estimate the probability of adverse event and therapeutic response related to a change in exposure.

## Q4: What Is the Minimum Clinical Significant Change in PD ?

**?**

## Decision on Dosing Adjustment

- Selection of “critical” concentration or PD endpoint
- Severity of AE
- Other drugs of the same class
- Other drugs with similar AE
- Patient populations
- Utility function
- How to adjust ?
- Dose amount, Dose interval, Titration

## Acknowledgement

- Jenny J. Zheng, He Sun, Gene Williams, Sam Haidar, Joga Gobburu, Raman Baweja, Jim Wei, Jurgen Venitz, Shiew-Mei Huang, Arzu Selen, Larry Lesko

## Remaining Issues (Questions to the Committee)

- What are the acceptable study designs that provide reliable data to establish exposure-response relationship for dosing adjustment ?
- How to model incomplete E-R data ?
- How to assess the risk and benefit of drug exposures that are not contained within the known E-R relationship ?
- How to establish consistent criteria for determining the no effect boundaries for change in pharmacokinetics for dosing adjustment ?