QSP-IO: A Quantitative Systems Pharmacology Toolbox for Mechanistic Multiscale Modeling for Immuno-Oncology Applications

Richard J. Sové, Mohammad Jafarnejad, Chen Zhao, Hanwen Wang, Huilin Ma, Aleksander S. Popel

Research output: Contribution to journalArticlepeer-review

Abstract

Immunotherapy has shown great potential in the treatment of cancer; however, only a fraction of patients respond to treatment, and many experience autoimmune-related side effects. The pharmaceutical industry has relied on mathematical models to study the behavior of candidate drugs and more recently, complex, whole-body, quantitative systems pharmacology (QSP) models have become increasingly popular for discovery and development. QSP modeling has the potential to discover novel predictive biomarkers as well as test the efficacy of treatment plans and combination therapies through virtual clinical trials. In this work, we present a QSP modeling platform for immuno-oncology (IO) that incorporates detailed mechanisms for important immune interactions. This modular platform allows for the construction of QSP models of IO with varying degrees of complexity based on the research questions. Finally, we demonstrate the use of the platform through two example applications of immune checkpoint therapy.

Original languageEnglish (US)
Pages (from-to)484-497
Number of pages14
JournalCPT: Pharmacometrics and Systems Pharmacology
Volume9
Issue number9
DOIs
StatePublished - Sep 1 2020

ASJC Scopus subject areas

  • Modeling and Simulation
  • Pharmacology (medical)

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