Barton HA, Clewell HJ, Yoon M. 2016. Systems pharmacology modeling. Chapter 17 in: New Horizons in Predictive Drug Metabolism and Pharmacokinetics, Royal Society of Chemistry, pp. 359–390.
Modeling and simulation play increasingly important roles in pharmaceutical discovery and development addressing both efficacy and safety. Mathematics has long played a fundamental role in the development of basic concepts of pharmacology and pharmacokinetcs, but the availability of vastly enhanced computing capability has influenced experimental methods and the approaches for analyzing the data. A tension now exists between well-established methods using PK/PD models for analyzing preclinical and clinical study data that restrict the model structure to only have parameters directly estimable from the specific data set and the widely perceived value of incorporating knowledge of the biological system into the analysis. Systems pharmacology models constructed by integrating physiologically based pharmacokinetic (PBPK) with mechanistic PD models, such as CSBP models, provide the potential to assess whether pharmacological interventions in a system will be beneficial prior to and during the costly experimental discovery and development process. Due to the resources required to develop larger systems pharmacology models, pharmaceutical modeling will continue to rely on a wide range of analyses intended to be fit for purpose in addressing the issues at hand. The value of bringing together the breadth of biological knowledge within a systems pharmacology modeling framework is increasingly recognized within academia, industry, and regulatory agencies worldwide.