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

  • Bai, Jane P. F.1
  • Schmidt, Brian J.2
  • Gadkar, Kapil G.3, 4
  • Damian, Valeriu5
  • Earp, Justin C.1
  • Friedrich, Christina6
  • van der Graaf, Piet H.7, 8
  • Madabushi, Rajanikanth1
  • Musante, Cynthia J.9
  • Naik, Kunal1
  • Rogge, Mark10
  • Zhu, Hao1
  • 1 U.S. Food and Drug Administration, Silver Spring, Maryland, 20903, USA , Silver Spring (United States)
  • 2 Bristol Myers Squibb, Princeton, New Jersey, USA , Princeton (United States)
  • 3 Genentech Inc., South San Francisco, California, 94080, USA , South San Francisco (United States)
  • 4 Denali Therapeutics, San Francisco, California, USA , San Francisco (United States)
  • 5 GSK R&D – Upper Providence, 1250 S Collegeville Rd, Collegeville, Pennsylvania, 19426, USA , Collegeville (United States)
  • 6 Rosa & Co LLC, 751 Laurel St., Ste. 127, San Carlos, California, 94070, USA , San Carlos (United States)
  • 7 Certara, Canterbury, CT2 7FG, UK , Canterbury (United Kingdom)
  • 8 Leiden Academic Centre for Drug Research, Leiden, CC, 2333, the Netherlands , Leiden (Netherlands)
  • 9 Early Clinical Development, Pfizer Worldwide Research, Development, & Medical, 1 Portland Street, Cambridge, Massachusetts, 02139, USA , Cambridge (United States)
  • 10 Takeda Pharmaceuticals International Co, 40 Landsdowne Street, Cambridge, Massachusetts, 02139, USA , Cambridge (United States)
Published Article
The AAPS Journal
American Association of Pharmaceutical Scientists
Publication Date
Apr 30, 2021
DOI: 10.1208/s12248-021-00585-x
Springer Nature


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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