TY - JOUR
T1 - QSP-IO
T2 - A Quantitative Systems Pharmacology Toolbox for Mechanistic Multiscale Modeling for Immuno-Oncology Applications
AU - Sové, Richard J.
AU - Jafarnejad, Mohammad
AU - Zhao, Chen
AU - Wang, Hanwen
AU - Ma, Huilin
AU - Popel, Aleksander S.
N1 - Funding Information:
This work was supported by National Institutes of Health Grants U01CA212007 and R01CA138264.
Publisher Copyright:
© 2020 The Authors. CPT: Pharmacometrics & Systems Pharmacology published by Wiley Periodicals LLC on behalf of the American Society for Clinical Pharmacology and Therapeutics.
PY - 2020/9/1
Y1 - 2020/9/1
N2 - 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.
AB - 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.
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U2 - 10.1002/psp4.12546
DO - 10.1002/psp4.12546
M3 - Article
C2 - 32618119
AN - SCOPUS:85090315539
SN - 2163-8306
VL - 9
SP - 484
EP - 497
JO - CPT: Pharmacometrics and Systems Pharmacology
JF - CPT: Pharmacometrics and Systems Pharmacology
IS - 9
ER -