Chan, Jason, Allen, Richard, Boras, Britton, Cabal, Antonio, Damian, Valeriu, Gibbons, Francis, Gulati, Abhishek, Hosseini, Iraj, Kearns, Jeff, Ryuuta, Saitou, Cucurull-Sanchez, Lourdes, Selimkhanov, Jangir, Stein, Andrew, Umehara, Kenichi, Wang, Guanyu, Wang, Weirong and Neves-Zaph, Susana (2022) Current practices for QSP model assessment: an IQ consortium survey. Journal of pharmacokinetics and pharmacodynamics. ISSN 1573-8744

Abstract

Quantitative Systems Pharmacology (QSP) modeling is increasingly applied in the pharmaceutical industry to influence decision making across a wide range of stages from early discovery to clinical development to post-marketing activities. Development of standards for how these models are constructed, assessed, and communicated is of active interest to the modeling community and regulators but is complicated by the wide variability in the structures and intended uses of the underlying models and the diverse expertise of QSP modelers. With this in mind, the IQ Consortium conducted a survey across the pharmaceutical/biotech industry to understand current practices for QSP modeling. This article presents the survey results and provides insights into current practices and methods used by QSP practitioners based on model type and the intended use at various stages of drug development. The survey also highlights key areas for future development including better integration with statistical methods, standardization of approaches towards virtual populations, and increased use of QSP models for late-stage clinical development and regulatory submissions.

Item Type:	Article
Date Deposited:	31 Aug 2022 00:46
Last Modified:	31 Aug 2022 00:46
URI:	https://oak.novartis.com/id/eprint/47235