FDA-Industry Scientific Exchange on assessing quantitative systems pharmacology models in clinical drug development: a meeting report, summary of challenges/gaps, and future perspective

The pharmaceutical industry is actively applying quantitative systems pharmacology (QSP) to make internal decisions and guide drug development. To facilitate the eventual development of a common framework for assessing the credibility of QSP models for clinical drug development, scientists from US F...

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Bibliographic Details
Published in:The AAPS journal Vol. 23; no. 3; p. 60
Main Authors: Bai, Jane P. F., Schmidt, Brian J., Gadkar, Kapil G., Damian, Valeriu, Earp, Justin C., Friedrich, Christina, van der Graaf, Piet H., Madabushi, Rajanikanth, Musante, Cynthia J., Naik, Kunal, Rogge, Mark, Zhu, Hao
Format: Journal Article
Language:English
Published: Cham Springer International Publishing 30.04.2021
Subjects:
Biochemistry
Biomedical and Life Sciences
Biomedicine
Biotechnology
Meeting Report
Pharmacology/Toxicology
Pharmacy
drug development
quantitative systems pharmacology
pharmacodynamics
model calibration and validation
model assessment
ISSN:1550-7416, 1550-7416
Online Access:Get full text
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Summary:The pharmaceutical industry is actively applying quantitative systems pharmacology (QSP) to make internal decisions and guide drug development. To facilitate the eventual development of a common framework for assessing the credibility of QSP models for clinical drug development, scientists from US Food and Drug Administration and the pharmaceutical industry organized a full-day virtual Scientific Exchange on July 1, 2020. An assessment form was used to ensure consistency in the evaluation process. Among the cases presented, QSP was applied to various therapeutic areas. Applications mostly focused on phase 2 dose selection. Model transparency, including details on expert knowledge and data used for model development, was identified as a major factor for robust model assessment. The case studies demonstrated some commonalities in the workflow of QSP model development, calibration, and validation but differ in the size, scope, and complexity of QSP models, in the acceptance criteria for model calibration and validation, and in the algorithms/approaches used for creating virtual patient populations. Though efforts are being made to build the credibility of QSP models and the confidence is increasing in applying QSP for internal decisions at the clinical stages of drug development, there are still many challenges facing QSP application to late stage drug development. The QSP community needs a strategic plan that includes the ability and flexibility to Adapt, to establish Common expectations for model Credibility needed to inform drug Labeling and patient care, and to AIM to achieve the goal (ACCLAIM). Graphical abstract
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ISSN:1550-7416
1550-7416
DOI:10.1208/s12248-021-00585-x