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By: Jiajie Yu

In modern drug development, the focus of the research and development enterprise has evolved to include, in addition to the study of drug molecule properties, the mechanistic investigation and understanding of the interaction of the drug with both its intended target and the biology (human or preclinical) surrounding it. This has significantly increased the number of variables to be considered, including chemistry, pharmacology, and biology considerations. For example, a drug can only have an effect in the brain if it first passes through the blood brain barrier no matter how effective it is. This has also increased the number of variables to be simultaneously analyzed to the point that quantitative computer modeling approaches have become an integral part of the pharmaceutical scientist’s arsenal to discover and characterize new molecular entities.

Against this background, Quantitative Systems Pharmacology (QSP) is a collection of integrated multi-scale modeling approaches to understand drug mechanism of action in the context of the relevant biology. Due to their multiscale nature, these quantitative methods can serve as a living repository of information arising from preclinical studies and trials in various human populations. Lastly, QSP has been suggested as a promising approach to design cost-efficient studies, optimize target selection, and predict clinical efficacy and safety outcomes.

A challenge in developing QSP models is that biologic mechanisms need to be included in the model with an appropriate level of detail in order to allow for robust model predictions. The QSP model complexity is the subject of continuous debate, influenced by factors such as the availability of data, the stage of the program and specific questions to be addressed by QSP. Developing QSP models by its nature is a multi-disciplinary effort that commonly demands considerable resources and commitment. Therefore, it is of high interest to explore when and why QSP should be applied and what the return on investment is. Learn more about these topics as discussed by Mark Peterson, Ph.D., (Pfizer) in the AAPS webinar When and Why to Focus on Quantitative Systems Pharmacology (QSP) on Thursday, June 2.

Jiajie Yu, M.S, Ph.D. is a scientist at Amgen Inc. He received M.S. and Ph.D. degrees from Cornell University and completed a postdoctoral training in Massachusetts Institute of Technology. He has been serving in the AAPS Systems Pharmacology Focus Group Steering Committee since 2014.