2019
DOI: 10.1002/psp4.12463
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Applications of Quantitative Systems Pharmacology in Model‐Informed Drug Discovery: Perspective on Impact and Opportunities

Abstract: Quantitative systems pharmacology (QSP) approaches have been increasingly applied in the pharmaceutical since the landmark white paper published in 2011 by a National Institutes of Health working group brought attention to the discipline. In this perspective, we discuss QSP in the context of other modeling approaches and highlight the impact of QSP across various stages of drug development and therapeutic areas. We discuss challenges to the field as well as future opportunities.

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Cited by 55 publications
(58 citation statements)
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“…Importantly, ongoing clinical trials may provide insights on the effect of entinostat and ipilimumab on the immune system and resistance mechanism in breast cancer development, which would allow us to make step-bystep modification of the model and its parameters and improve its predictive power (Pitt et al, 2016;Darvin et al, 2018;Eladdadi et al, 2018;Mahlbacher et al, 2019). Our goal is to understand the dynamic interactions between drugs and the immune system in cancer as a whole, to update our assumptions on drug/tumor-immune dynamics through comparison between model predictions and clinical observations, and thereby to guide drug development and clinical trial design (Cheng et al, 2017;Nijsen et al, 2018;Bai et al, 2019;Bradshaw et al, 2019).…”
Section: Discussionmentioning
confidence: 99%
“…Importantly, ongoing clinical trials may provide insights on the effect of entinostat and ipilimumab on the immune system and resistance mechanism in breast cancer development, which would allow us to make step-bystep modification of the model and its parameters and improve its predictive power (Pitt et al, 2016;Darvin et al, 2018;Eladdadi et al, 2018;Mahlbacher et al, 2019). Our goal is to understand the dynamic interactions between drugs and the immune system in cancer as a whole, to update our assumptions on drug/tumor-immune dynamics through comparison between model predictions and clinical observations, and thereby to guide drug development and clinical trial design (Cheng et al, 2017;Nijsen et al, 2018;Bai et al, 2019;Bradshaw et al, 2019).…”
Section: Discussionmentioning
confidence: 99%
“…4 Bradshaw and co-workers have recently argued that well-defined terminology provides direction, focus, and branding for a scientific discipline such as QSP. 5 From a semantic viewpoint, QSP includes any modeling approach that is quantitative and deals with systems pharmacology, however, the QSP model-specific definition and scope are as they are described in the National Institutes of Health (NIH) white paper. 6 In broader terms, PBPK and other emerging disciplines, like physiologically-based biopharmaceutics modeling and Quantitative Systems Toxicology and Safety, all fall under the umbrella of QSP approaches.…”
Section: Status Of Pbpk and Qspmentioning
confidence: 99%
“…Perhaps, as suggested by Bradshaw and co-workers, we should use the term "quantitative systems pharmacokinetic" models instead of PBPK to better encompass their broad range of application. 5 Examples of combining quantitative systems pharmacokinetic models with classic QSP models have been published and the integration of these complementary approaches can considerably expand their individual scope as suggested recently. 7 Integration of pharmacometric and systems pharmacology Integration of pharmacometric and system pharmacology disciplines requires collaboration and the ability of individuals in the different disciplines to relate to one another's needs and objectives.…”
Section: Status Of Pbpk and Qspmentioning
confidence: 99%
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