安渡分享 | FDA指导原则摘要:《临床药物基因组学：早期临床研究的上市前评价和标签建议》

• This guidance, issued January 2013, is intended to assist the pharmaceutical industry in evaluating how variations in the human genome, specifically DNA sequence variants, could affect a drug’s pharmacokinetics (PK), pharmacodynamics (PD), efficacy, or safety.

• The guidance provides recommendations on when and how genomic information should be considered to address questions arising during drug development and regulatory review.

• The focus of this guidance is to provide advice on general principles of study design, data collection, and data analysis in early-phase trials relevant for exploratory and observational studies intended to generate genomic hypotheses that may then be tested in prospectively designed phase 3 trials.

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A. Genetic Differences

• Genetic differences between individuals can affect virtually all aspects of a disease and its treatment, including the rate of disease occurrence; the risk of disease progression or recurrence; the drug or drug class; the therapeutic dose; the nature and extent of beneficial responses to treatment and the likelihood of drug toxicity.

• The genetic differences of most relevance in drug development are those associated with genes in four broad categories: (1) genes relevant to the drug’s PK (absorption, distribution, metabolism and excretion (ADME); (2) genes that code for intended or unintended drug targets and other pathways related to the drug’s pharmacologic effect; (3) genes not directly related to a drug’s pharmacology that can predispose to toxicities such as immune reactions; and (4) genes that influence disease susceptibility or progression.

• Genetic material collected and blood and/or urine drug concentration data are needed to determine the extent to which genetic polymorphisms in metabolism and/or transporter genes influence exposure to drugs and/or active metabolites and their responses.

B. Pharmacogenomics Studies

PGx studies can contribute to a greater understanding of interindividual differences in the efficacy and safety of investigational drugs.  PGx research depends on the collection and use of biological samples to generate data.

PGx assessment in early-phase clinical studies may:

1. Identify populations that should receive lower or higher doses of a drug or longer titration intervals based on genetic effects on drug exposure, dose-response, early effectiveness, and/or common adverse reactions.

2. Identify responder populations based on phenotypic, receptors, or genetic characteristics, is a critical element in treatment individualization that has been used primarily in the oncologic setting.

3. Identify high-risk groups which would not have the expected response.

A. General Considerations

• The value of DNA/RNA sample collection and the information that analysis of these samples can provide will vary for different drugs and indications.  Known PGx factors identified during nonclinical assessments that affect PK or PD should be considered, particularly when the threshold between activity and toxicity is narrow.

• When the pharmacology of the drug (i.e., mechanism of action or metabolism/transport) is not well-characterized, high-throughput platforms (such as ADME gene or genome-wide arrays or high-throughput sequencing) should be considered.

B. Clinical Pharmacogenomic Studies

In vitro studies of metabolism, transport, or drug targets could help identify the need for human PGx studies and contribute to the design and analysis of those studies. The following types of clinical pharmacology studies provide opportunities to prospectively integrate PGx factors for assessing interindividual variability and its implications for subsequent clinical studies.

1. PK and PD Studies in Healthy Volunteers

• Single- and multiple-dose PK studies provide information on drug PK, level of interindividual variability, and on common gene variants affecting ADME.

• For a drug that is a substrate of a polymorphic enzyme or transporter, the evaluation of comparative PK in the subgroups genetically defined as ultra-rapid, extensive, intermediate or poor metabolizers may provide essential information on potential drug–drug interactions.

2. PK and PD Studies in Patients

• If important variability in PK of active species (i.e., parent drug and/or its active metabolite) is observed in healthy volunteers, the significance of this finding should be considered in the design of subsequent studies in patients.

• When specific genotypes are shown to reliably predict blood levels and drug effect, this knowledge can be used in the subsequent design of other clinical trials, for example, by using genotypes to select patients for trials, to stratify groups within trials or to adjust doses in trials.

3. Dose-Response (D/R) Studies

• D/R studies are usually conducted in phase 2 using biomarkers or clinical endpoints that are relevant to clinical efficacy and safety to provide proof of concept, identify doses for phase 3 trials and establish dose-response for relatively common adverse effects.

• If previous PK and/or PD studies suggest that a genotype or phenotype is important in influencing systemic exposure-response or efficacy and safety responses, D/R studies that stratify dose groups by genotype or specific genotype-guided D/R studies (PK adjusted D/R or even a concentration-controlled study) should be considered.

C. Specific Considerations in Study Design

1. Overview

• The choice of study design depends on prior knowledge and the purpose of the study.  The study is straightforward when the goal is to compare PK in genomically defined subgroups of healthy volunteers or patients.

• Analytical validation of genotyping and phenotyping methods should be established before initiating a clinical PGx study. Appropriate quality control materials, standards and well validated protocols should be established.

• For use as an in vitro device companion diagnostic, the test must be approved or cleared at the same time the drug is approved for marketing, except in pre-specified circumstances.

2. Study Population

• Clinical PGx studies focused on pharmacokinetics are usually performed in phase 1 using healthy volunteers, with additional attention to the effects of gender, age, and race/ethnicity.

• The exclusion of patients with certain genotypes from a clinical trial should be considered on a case-by-case basis.

• When a drug–drug interaction study is intended to evaluate the impact of an investigational drug as an inhibitor of enzyme metabolism, it would be appropriate to carry out an evaluation of the extent of drug interactions in subjects with various genotypes.

3. Multiple Covariate Considerations

• Observable phenotypes of drug response in humans result from the interactions of multiple factors or covariates, including genetic, demographic, and environmental factors.  The understanding of specific covariates (e.g., age, sex, and race) and gene-covariate interactions on variability in drug response could be useful in understanding the relative impact of genetics, versus other nongenetic factors, on the PK, PD, dosing, efficacy, and safety of a drug.

• Mathematical simulations using population-based, physiological PK models (i.e., physiologically based pharmacokinetic (PBPK) models) that simultaneously integrate various patient-intrinsic and -extrinsic factors can provide an understanding of the potential complex changes in E/R relationships in patients when multiple covariates are present.

• Some applications of these models, including the design of clinical trials to evaluate the effects of drug-metabolizing enzyme polymorphisms on PK and PD, are increasingly being seen in regulatory submissions.

4. Dose Selection

• A clinical PGx study should be conducted at relevant clinical doses.  A lower dose or different titration interval could cause high and unsafe exposure or excessive pharmacological response to the drug.

• Interpretation of findings in a clinical PGx study, such as changes in exposure in specific genotypes, may be aided by a good understanding of dose- or concentration-response relationships for both desirable and undesirable drug effects in the general population and in subpopulations with different genetic variations.

5. Measurements of Interest

• PK measurements and parameters that should be useful for consideration of genotypic effects on drug exposure include AUC, Cmax, and time-to-Cmax (Tmax), clearance, volumes of distribution, and half-lives. Additional measures, such as trough drug concentrations in multiple-dose PK studies can help determine appropriate dosing strategies to achieve similar exposure across different subsets of the population.

• Biomarkers of drug response related to a drug’s intended pharmacological effect, suspected off-target effects, and/or safety should be incorporated into clinical PGx studies to measure whether or not genetic factors influencing exposure or target response will have an impact on clinical outcomes.

6. Statistical Considerations

• Statistical considerations in PGx studies are important. The hypotheses and conclusions arising from early-phase clinical studies should be sufficiently supported with credible data.

• For exploratory and observational studies, which generally do not involve randomization of subjects to treatment, the statistical concepts that are most relevant to clinical pharmacogenomics include the following:

   

• Avoid confounding by balancing the testing of samples on all controllable confounding factors, which include technical variations  and patient variations.

• Control for the multiplicity and the risk of incorrectly identifying associations in genomic data when many searches are performed.

• Quantitatively characterize the preliminary marker classifier performance and explore the prognostic and predictive attributes of the marker when appropriate.

• Address the potential for population stratification due to admixture and other confounding factors.

• Assess the reproducibility of a genetic finding so that it can be used reliably and evaluated in follow-up development in later-phase clinical trials.

• Highly multiplexed genotyping methods are available to interrogate hundreds or thousands of sequence variations in ADME-related genes.  These methods may be useful when exploring causes for PK variability in the absence of in vitro data that suggest a single causal pathway.

• In PGx substudies that are not randomized, it is possible for the substudy population to be different from the overall trial population in a variety of ways.  If a trial is randomized and the substudy is selected based on a baseline feature, the groups in the randomized sample, if they are a reasonably large fraction of the sample, should be sufficiently similar to allow for meaningful assessment.

• Statistical issues for early pharmacogenomic assessments can define differences in metabolism or clearance that will affect the PK of a drug in the magnitude or presence of a favorable response to a treatment  or identify genomic predictors of an increased likelihood of an adverse effect.

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Labeling should include information on PGx only if it is useful to inform prescribers about the impact (or lack of impact) of genotype on phenotype or to indicate whether a genomic test is available.

In labeling, pharmacogenomic information can include, but is not limited to, the following:

• Information on the frequencies of alleles, genotypes, haplotypes, or other genomic markers of relevance.

• Description of the functional effects of genomic variants (e.g., genetically based differences in enzyme activity such as reduced cytochrome P450 enzyme activity attributable to polymorphisms in a CYP gene).

• Effect of genotype on important PK parameters or PD endpoints.

• Description of pharmacogenomic studies that provided evidence of genetically-based differences in drug benefit or risk.

• Dosing and patient selection recommendations based on genotype.

When the information has important implications for the safe and effective use of a drug and the consequences of the genetic variations result in recommendations for restricted use, dosage adjustments, contraindications, or warnings, this information will be summarized in other sections of the labeling, as appropriate.