Guidance for Industry Exposure-Response Relationships — Study Design, Data Analysis, and Regulatory Applications

B. Modeling Strategy

In the process of PK-PD modeling, it is important to describe the following prospectively:

1. Statement of the Problem

The objectives of the modeling, the study design, and the available PK and PD data;

2. Statement of Assumptions

The assumptions of the model that can be related to dose-response, PK, PD, and/or one or more of the following:

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  The mechanism of the drug actions for efficacy and adverse effects
  
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  Immediate or cumulative clinical effects
  
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  Development of tolerance or absence of tolerance
  
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  Drug-induced inhibition or induction of PK processes
  
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  Disease state progression
  
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  Response in a placebo group
  
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  Circadian variations in basal conditions
  
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  Influential covariates
  
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  Absence or presence of an effect compartment
  
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  Presence or absence of active metabolites and their contribution to clinical effects
  
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  The PK model of absorption and disposition and the parameters to be estimated
  
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  The PD model of effect and the parameters to be estimated
  
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  Distribution of PK and PD measures and parameters
  
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  Distributions of intra- and inter-individual variability in parameters
  
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  Inclusion and/or exclusion of specific patient data
  
  
  

The assumptions can be justified based on previous data or from the results of the current analysis.

3. Selection of the Model

The answer to the question of what constitutes an appropriate model is complex. In general, the model selected will be based on the mechanism of action of the drug, the assumptions made, and the intended use of the model in decision making. If the assumptions do not lead to a mechanistic model, an empirical model can be selected. In this case, the validation of the model predictability becomes especially important. The available data can also govern the types of models that can be used. The model selection process can be a series of trial and error steps. Different model structures or newly added or dropped components to an existing model can be assessed by visual inspection and tested using one of several objective criteria. New assumptions can be added when emerging data indicates that this is appropriate. The final selection of the model will usually be based on the simplest model possible that has reasonable goodness of fit, and that provides a level of predictability appropriate for its use in decision making.

4. Validation of the Model

The issue of model validation is not totally resolved. Generally, we recommend that the predictive power of a model be dealt with during the study design as well as in the data analysis stages and that the study be designed to yield a predictive model. When plausible exposure-response models are identified based on prior knowledge of the drug before conducting an exposure-response study, the predictive power of the final models derived from the study results becomes a function of study design factors, such as number of subjects and sampling plan. The predictive power can be estimated through simulation, by considering distributions of pharmacokinetic, pharmacodynamic, and study design variables. A robust study design will provide accurate and precise model parameter estimations that are insensitive to model assumptions.

During the analysis stage of a study, models can be validated based on internal and/or external data. The ultimate test of a model is its predictive power and the data used to estimate predictability could come from exposure-response studies designed for such a purpose. A common method for estimating predictability is to split the data set into two parts, build the model based on one set of data, and test the predictability of the resulting model on the second set of data. The predictability is especially important when the model is intended to (1) provide supportive evidence for primary efficacy studies, (2) address safety issues, or (3) support new doses and dosing regimens in new target populations or subpopulations defined by intrinsic and extrinsic factors or when there is a change in dosage form and/or route of administration.

VII. SUBMISSION INFORMATION: EXPOSURE-RESPONSE STUDY REPORT

It is advisable for the general format and content of a clinical study report to be based on that presented in the ICH E3 guidance on the Structure and Content of Clinical Study Reports, modified to include measurements of exposure and response and planned or actual modeling and simulation. It is helpful to include a description of the assay methods used in quantifying drug concentrations (if they are components of the exposure measure) as well as assay performance (quality control samples), sample chromatograms, standard curves used, where applicable, and a description of the validity of the methodologies. The report could also contain:

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  The response variable and all covariate information
  
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  An explanation of how they were obtained
  
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  A description of the sampling design used to collect the PK and PD measures
  
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  A description of the covariates, including their distributions and, where appropriate, the accuracy and precision with which the responses were measured
  
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  Data quality control and editing procedures
  
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  A detailed description of the criteria and procedures for model building and reduction, including exploratory data analysis
  

The following components of the data analysis method used in the study would also ordinarily be described: (1) the chosen dose-response or PK-PD model, (2) the assumptions and underlying rationale for model components (e.g., parameterization, error models), (3) the chosen model-fitting method, (4) a description of the treatment of outliers and missing data, where applicable, and (5) diagrams, if possible, of the analysis performed and representative control/command files for each significant model building and/or reduction step. In presenting results, complete output of results obtained for the final dose-response, or PK-PD model, and important intermediate steps can be included.

A complete report would include a comprehensive statement of the rationale for model building and reduction procedures, interpretation of the results, impact of protocol violations, discussion and presentation of supporting graphs, and the ability of the model to predict performance.

It is helpful if an appendix is provided containing the data set used in the dose-response or PK-PD analysis, the programming codes along with the printouts of the results of the final model, and any additional important plots.
Whether the analysis was performed as a result of an add-on to a clinical study or as a stand-alone exposure-response study, it is important that the original study protocol and amendments be included in the appendix.

The FDA’s Center for Drug Evaluation and Research (CDER) guidance for industry on Providing Regulatory Submissions in Electronic Format  NDAs includes information on how to submit the exposure-response study report in electronic format. Information on electronic submissions to FDA’s Center for Biologics Evaluation and Research (CBER) can be found in the guidance for industry on Providing Regulatory Submissions to the Center for Biologics Evaluation and Research (CBER) in Electronic Format  Biologics Marketing Applications (Biologics License Application (BLA), Product License Application (PLA)/Establishment License Application (ELA) and New Drug Application (NDA)). FDA is still actively working on standardizing data file formats for exposure-response and other clinical pharmacology data, and plans to provide these standards in future versions of the electronic guidance document. In the meantime, sponsors are encouraged to submit both the reports and data files with BLA or NDA submissions in electronic format. Until the details are included in an electronic BLA or NDA guidance document, sponsors can consult the clinical pharmacology and biopharmaceutics reviewer or team leader on the data sets to be provided and elements to be included in the data sets.

REFERENCES

Lesko, L.J., M. Rowland, C.C. Peck, T.F. Blaschke, 2000, “Optimizing the Science of Drug Development: Opportunities for Better Candidate Selection and Accelerated Evaluation in Humans,” J. Clin. Pharmacol., 40:803-814.

Lesko, L.J. and A.J. Atkinson, Jr., 2001, “Biomarkers and Surrogate Endpoints – Use in Drug Development and Regulatory Decision Making: Criteria, Validation, Strategies,” Ann. Rev. Pharmacol. Toxicol., 41:347-366.
Machado, S.G., R. Miller, C. Hu, 1999, “A Regulatory Perspective on Pharmacokinetic/Pharmacodynamic Modelling,” Statistical Methods in Medical Research, 8(3):217-45.

Peck, C.C., W.H. Barr, L.Z. Benet, J. Collins, R.E. Desjardins, D.E. Furst, J.G. Harter, G. Levy, T. Ludden, J.H. Rodman, et al., 1994, “Opportunities for Integration of Pharmacokinetics, Pharmacodynamics, and Toxicokinetics in Rational Drug Development,” J. Clin. Pharmacol., 34(2):111-119.

Sanathanan, L.P. and C.C. Peck, 1991, “The Randomized Concentration-Controlled Trial: An Evaluation of Its Sample Size Efficiency,” Controlled Clin. Trials, 12(6):780-94.
Sheiner L.B., Y. Hashimoto, S.L. Beal, 1991, “A Simulation Study Comparing Designs for Dose Ranging,” Stat. Med., 10(3):303-21.
Sheiner L.B., J.L. Steimer, 2000, “Pharmacokinetic/Pharmacodynamic Modeling in Drug Development,” Ann. Rev. Pharmacol. Toxicol., 40: 67-95.
Sheiner L.B., 1997, “Learning Versus Confirming in Clinical Drug Development,” Clin. Pharmacol. Ther., 61(3):275-91.
Temple, R.J., 1995, “A Regulatory Authority’s Opinion About Surrogate Endpoints,” in Clinical Measurement in Drug Evaluation, Nimmo and Tucker, Eds., Wiley & Sons.
Temple R.J., 1999, “Are Surrogate Markers Adequate to Assess Cardiovascular Disease Drugs?” JAMA, 282(8):790-5.

APPENDIX A: RELATED GUIDANCES³

The use of exposure-response relationships is considered in many FDA guidances for industry as well as in various ICH guidances. These guidances can be divided into those that provide general advice and those that provide specific recommendations about the use of exposure-response information to adjust a dosage regimen based on intrinsic and extrinsic factors. The ICH Common Technical Document (ICH M4, Efficacy) suggests a structure to organize the submission of exposure-response information. In addition, the statistical considerations for dose-response studies are briefly described in the ICH E9 Guidance on Statistical Principles for Clinical Trials.

A. Guidances Providing General Statements
The value of understanding exposure-response has been recognized in numerous domestic and international guidances. Brief abstracts of these guidances are provided below to focus on exposure-response relationships and the impact of intrinsic and extrinsic factors on these relationships.

1. 
   Providing Clinical Evidence of Effectiveness for Human Drugs and Biological Products
   

This guidance provides general information about the efficacy standard (section I) and comments further on the quantity (section II) and quality (section III) of efficacy information needed for a regulatory determination of efficacy based on both statutory and scientific considerations. The guidance focuses on (1) when efficacy for a new product can be extrapolated entirely from existing efficacy studies, (2) when one adequate and well-controlled study of a particular condition, regimen, or dose supported by information from other adequate and well-controlled studies may be appropriate, and (3) when information from a single multicenter study may be appropriate.

2. 
   Guideline for the Format and Content of the Clinical and Statistical Sections of an Application
   

This guidance provides a description of the format and content of the clinical and statistical data package required as part of a new drug application under Title 21, Code of Federal Regulations (CFR) § 314.50. It emphasizes the importance of conducting an integrated analysis of all clinical and preclinical exposure-response data that forms the foundation for dose and dosing regimen determinations and dose adjustments for subpopulations.

3. 
   ICH E4, Dose Response Information to Support Drug Registration
   

This guidance describes the purpose of exposure-response information and the uses of dose-response and/or concentration-response data in choosing doses during the drug development process. The guidance emphasizes the importance of developing exposure-response data throughout development. It further comments on the use of population and individual dose-concentration, and concentration- and/or dose-response relationships to provide dosage and administration instructions in product labeling. The guidance notes that these instructions can include information about both starting dosages and subsequent titration steps based on response to the drug, as well as information on how to adjust dose in the presence of factors that are intrinsic (age, gender, race, organ dysfunction, body size, differences in absorption, distribution, metabolism, and excretion) and extrinsic (diet, concomitant medications). The guidance emphasizes the importance of early exposure-response data to allow efficient design of later studies and the value of examining the entire database to assess exposure-response relationships. The guidance further comments on strengths and limitations of various study designs to assess exposure-response. The guidance comments briefly on the use of models to amplify understanding of exposure-response-relationships and, consistent with 21 CFR 314.126, indicates that a well-controlled dose-response study may be one type of study that supports efficacy.

4. 
   ICH E5, Ethnic Factors in the Acceptability of Foreign Clinical Data
   

This guidance provides descriptions of PK and PD studies and expresses PD endpoints as safety and/or efficacy measures of activity thought, but not documented, to be related to clinical benefit (biomarkers), surrogate endpoints, and clinical benefit endpoints. The guidance further defines a PD study as one that describes the relationship between a pharmacological effect or clinical benefit effect in relation to dose or drug concentration. The guidance establishes a classification system of intrinsic (genetic polymorphism, age, gender, height, weight, lean body mass, body composition, and organ dysfunction) and extrinsic (medical practice, diet, use of tobacco, use of alcohol, exposure to pollution and sunshine, practices in clinical trial design and conduct, socioeconomic status, compliance with medication) ethnic factors that can affect safety, efficacy, dosage, and dosage regimen determinations. The guidance provides an additional set of factors that indicate whether a drug may be sensitive to ethnic factors (linear PK, flat PD curve, wide therapeutic range). It focuses on the bridging studies that may be critical for an application in a new region based on a clinical data package developed in another region. These bridging studies range from those that establish similarity of exposure-response relationship in the two regions for a well-established PD effect (e.g., ACE inhibition or short-term blood pressure response) to a controlled trial in the new region, preferably a dose-response study, using the pertinent clinical endpoint.

B. Guidances Providing Specific Statements
FDA has issued final or draft⁴ guidances that focus on how to adjust dosages and dosing regimens in the presence of selected intrinsic and extrinsic factors. A general theme of these guidances is that information relating exposure to response can be used to adjust dosages and dosing regimens in the presence of influences on PK such as age, gender (demographic factors), impaired organ function (intrinsic factors), or concomitant medications and diet (extrinsic factors). In many circumstances, where the assumption can be made that the exposure-response relationships are not disturbed by these factors, PK data alone can be used to guide dosages and dosing regimens. This principle is articulated in the following FDA guidances:

1. 
   ICH E7, Studies in Support of Special Populations: Geriatrics
   
   
   
2. 
   Study and Evaluation of Gender Differences in the Clinical Evaluation of Drugs
   
   
   
3. 
   General Considerations for Pediatric Pharmacokinetic Studies for Drugs and Biological Products (draft)
   
   
   
4. 
   Pharmacokinetics in Patients with Impaired Renal Function: Study Design, Data Analysis and Impact on Dosing and Labeling
   
   
   
5. 
   Pharmacokinetics in Patients with Hepatic Insufficiency: Study Design, Data Analysis and Impact on Dosing and Labeling (draft)
   
   
   
6. 
   In Vivo Metabolism/Drug Interactions Studies: Study Design, Data Analysis and Recommendations for Dosing and Labeling (draft)
   
7. 
   Population Pharmacokinetics
   

APPENDIX B: PEDIATRIC DECISION TREE INTEGRATION OF PK-PD

1 This guidance has been prepared by the Exposure-Response Working Group under the Medical Policy Coordinating Committee, Center for Drug Evaluation and Research (CDER), in cooperation with the Center for Biologics Evaluation and Research (CBER) at the Food and Drug Administration (FDA).

2 This document is available on the Internet at http://www.fda.gov/cder/guidance/stereo.htm.

3 We update guidances periodically. To make sure you have the most recent version of a guidance, check the CDER guidance page at http://www.fda.gov/cder/guidance/index.htm or the CBER guidance page at http://www.fda.gov/cber/guidelines.htm.

4 Draft guidances have been included for completeness only. As draft documents, they are not intended to be implemented until published in final form.