- FDA Pharmacometrics 2020 Strategic Goals
- Contact Information
- Selected Pharmacometric Reviews, Guidances and Presentations
- Model/Data Format
- Disease Specific Model Library [Archived]
- Program of physiologically-based pharmacokinetic and pharmacodynamic modeling (PBPK Program)
- QT Interdisciplinary Review Team (IRT)
Drug development and regulatory decisions are driven by information that is compiled primarily from clinical trials and other supportive experiments, but also through clinical experience in the post-market period. The wisdom of these decisions determines the efficiency of drug development, the decision to approve the drug, and the resultant drug product quality including guidance on how to use the product known as the label. While the decisions are usually simple in nature (e.g., trial design and project progression at the company, product and labeling approval at FDA), the data informing the decision are complex and diverse.
Pharmacometrics is an emerging science defined as the science that quantifies drug, disease and trial information to aid efficient drug development and/or regulatory decisions. Drug models describe the relationship between exposure (or pharmacokinetics), response (or pharmacodynamics) for both desired and undesired effects, and individual patient characteristics. Disease models describe the relationship between biomarkers and clinical outcomes, time course of disease and placebo effects. The trial models describe the inclusion/exclusion criteria, patient dis-continuation and adherence. Typical focus of Pharmacometrics has been on drug models, also referred to by terms such as: concentration-effect, dose-response, PKPD relationships. These Pharmacometric analyses are designed, conducted and presented in the context of drug development, therapeutic and regulatory decisions. The single-most important strength of such analyses is its ability to integrate knowledge across the development program and compounds, and biology.
The Pharmacometrics staff consists of a multidisciplinary team consisting of quantitative clinical pharmacologists, statisticians, engineers and data management experts, and work closely with clinicians and statisticians.
At FDA, pharmacometric work is conducted with three objectives:
- Most important is the decision to approve and label the drug product with particular attention to drug dosing for all patients. This has been the primary focus of our group.
- Providing advice on trial design decisions by sponsors is a consulting function where the focus is both trial success and rendering dosage regimens likely to be successful in all patients.
- Research is conducted to create new knowledge bases on the unique data available at FDA (i.e., prior NDA submissions) and literature both to inform better regulatory and drug development decisions by sponsors. Research is conducted to create or confirm prior models of disease change, placebo effect, drop-outs, and drug effect. Research is also conducted to help determine the value of biomarkers across clinical trials for a given disease or drug class to reflect change in primary disease endpoints. An important component of this research is training future Pharmacometricians.
- Train 20 Pharmacometricians
- Technical track
- Disease track
- Drug development track
- Implement 15 Standard Templates
- Develop disease specific data and analysis standards
- Expect industry to follow
- Develop 5 Disease models
- Create public disease model library
- International Harmonization
- Share expertise between global regulatory bodies
- Integrated Quantitative Clinical Pharmacology Summary
- All NDAs should have exposure-response analysis
- Design by Simulation: 100% Pediatric Written Requests
- Leverage prior knowledge to design Pediatrics Written Request trials
Yaning Wang, Ph.D.
Director, Division of Pharmacometrics
U.S. Food and Drug Administration
Center for Drug Evaluation and Research
E-mail: Yaning.Wang @fda.hhs.gov
Telephone: (301) 796-1624