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Physiological Indirect Response Model to Omics-Powered Quantitative Systems Pharmacology Model.

Authors :
Uatay A
Gall L
Irons L
Tewari SG
Zhu XS
Gibbs M
Kimko H
Source :
Journal of pharmaceutical sciences [J Pharm Sci] 2024 Jan; Vol. 113 (1), pp. 11-21. Date of Electronic Publication: 2023 Oct 26.
Publication Year :
2024

Abstract

Over the past several decades, mathematical modeling has been applied to increasingly wider scopes of questions in drug development. Accordingly, the range of modeling tools has also been evolving, as showcased by contributions of Jusko and colleagues: from basic pharmacokinetics/pharmacodynamics (PK/PD) modeling to today's platform-based approach of quantitative systems pharmacology (QSP) modeling. Aimed at understanding the mechanism of action of investigational drugs, QSP models characterize systemic effects by incorporating information about cellular signaling networks, which is often represented by omics data. In this perspective, we share a few examples illustrating approaches for the integration of omics into mechanistic QSP modeling. We briefly overview how the evolution of PK/PD modeling into QSP has been accompanied by an increase in available data and the complexity of mathematical methods that integrate it. We discuss current gaps and challenges of integrating omics data into QSP models and propose several potential areas where integrated QSP and omics modeling may benefit drug development.<br />Competing Interests: Declaration of Competing Interests The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. All authors are employed by AstraZeneca<br /> (Copyright © 2023 American Pharmacists Association. Published by Elsevier Inc. All rights reserved.)

Details

Language :
English
ISSN :
1520-6017
Volume :
113
Issue :
1
Database :
MEDLINE
Journal :
Journal of pharmaceutical sciences
Publication Type :
Academic Journal
Accession number :
37898164
Full Text :
https://doi.org/10.1016/j.xphs.2023.10.032