The effectiveness of pharmacometrics and quantitative systems in pharmaceutical research

Author(s): Gopal Dixit

Pharmacokinetics and pharmacodynamics with mechanistic models of physiology in health and disease to predict effects at the system level, quantitative systems pharmacology (QSP) models are an important aspect of pharmaceutical and clinical research. Mechanistic modeling and population approaches have traditionally been included in the quantitative clinical pharmacology toolbox, which is also known as pharmacometrics. However, the current environment necessitates the optimization and utilization of multiple models simultaneously. Parallel synchronization, cross-informative use, and sequential integration are three methods for combining QSP and pharmacometrics models that are discussed in this section. These methods are illustrated by a number of drug development case studies. Even though these methods are being used more and more in drug development, a true convergence of QSP and pharmacometrics that fully uses their synergy will require new tools and methods that make it easier to integrate technical aspects, as well as scientists with different modeling skills who can use cross-discipline strategies. This convergence will be made possible by extending the methods that have been used in each approach and adding additional resources like machine learning models, data-at-scale, end-to-end computation platforms, and real-time analytics.