Gabriel Helmlinger, Victor Sokolov, Kirill Peskov, Karen M Hallow, Yuri Kosinsky, Veronika Voronova, Lulu Chu, Tatiana Yakovleva, Ivan Azarov, Daniel Kaschek, Artem Dolgun, Henning Schmidt, David W Boulton, Robert C Penland
Journal: CPT: pharmacometrics & systems pharmacology 2020;8(6):380-395
PMID: 31087533
Quantitative systems pharmacology (QSP), a mechanistically oriented form of drug and disease modeling, seeks to address a diverse set of problems in the discovery and development of therapies. These problems bring a considerable amount of variability and uncertainty inherent in the nonclinical and clinical data. Likewise, the available modeling techniques and related software tools are manifold. Appropriately, the development, qualification, application, and impact of QSP models have been similarly varied. In this review, we describe the progressive maturation of a QSP modeling workflow: a necessary step for the efficient, reproducible development and qualification of QSP models, which themselves are highly iterative and evolutive. Furthermore, we describe three applications of QSP to impact drug development; one supporting new indications for an approved antidiabetic clinical asset through mechanistic hypothesis generation, one highlighting efficacy and safety differentiation within the sodium-glucose cotransporter-2 inhibitor drug class, and one enabling rational selection of immuno-oncology drug combinations.
2019 Astrazeneca Company. CPT: Pharmacometrics & Systems Pharmacology published by Wiley Periodicals, Inc. on behalf of the American Society for Clinical Pharmacology & Therapeutics.
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