History and Future Perspectives on the Discipline of Quantitative Systems Pharmacology Modeling and Its Applications

Abstract

Mathematical biology and pharmacology models have a long and rich history in the fields of medicine and physiology, impacting our understanding of disease mechanisms and the development of novel therapeutics. With an increased focus on the pharmacology application of system models and the advances in data science spanning mechanistic and empirical approaches, there is a significant opportunity and promise to leverage these advancements to enhance the development and application of the systems pharmacology field. In this paper, we will review milestones in the evolution of mathematical biology and pharmacology models, highlight some of the gaps and challenges in developing and applying systems pharmacology models, and provide a vision for an integrated strategy that leverages advances in adjacent fields to overcome these challenges.

A quantitative systems pharmacology approach to support mRNA vaccine development and optimization

“…Systems biology and in particular quantitative systems pharmacology (QSP) has been proven to be instrumental in reducing in vitro – in vivo disconnections, by generating in silico tools capable of helping in go/no‐go decisions 7 …”

Reconstruction of the Cytokine Signaling in Lysosomal Storage Diseases by Literature Mining and Network Analysis

“…QSP models are mathematical tools that allow studying in silico the perturbations exerted by drugs on a biological system and test hypotheses on their mechanism of action. Literature mining can be effectively incorporated in the multistep process that leads to model development, becoming particularly useful for the definition of the model scheme and facilitating the identification of key biological processed to represent, along with data sources and parameter constraints needed for the model development ( Azer et al, 2021 ).…”

Precision Cardio-Oncology: Use of Mechanistic Pharmacokinetic and Pharmacodynamic Modeling to Predict Cardiotoxicities of Anti-Cancer Drugs

“…Specifically, basic mechanism-based PK-PD modeling often incorporates one or more critical drug action steps, such as receptor binding or cell turnover, to capture major rate-limiting steps in drug dispositions and explain between-subject variabilities ( 7 ). Furthermore, systems pharmacology modeling provides a comprehensive modeling approach that has as objective to integrate the structures of physiological and pharmacological networks through PK-PD modeling ( 8 , 9 ). On the one hand, the physiological-based pharmacokinetic (PBPK) modeling framework enables the mechanistic description of drug absorption, distribution, metabolism, and excretion processes at the physiological level.…”

“…Thus, these mechanistic descriptions can be extrapolated to different populations and disease states if the associated physiological changes can be elucidated ( 10 ). On the other hand, with the development of high-throughput analytical methods, bioinformatics, and system biology, quantitative systems pharmacology (QSP) aims to quantitatively describe the behaviors of biological systems, and explain between-subject variabilities at genetic, protein, cellular, and whole-body levels ( 9 ).…”