Nonlinear mixed effects modeling in systems pharmacology

Abstract

Quantitative systems pharmacology (QSP) is the design and application of mathematical models to explain how drugs function at a systems level. Whereas traditional pharmacokinetic-pharmacodynamic modeling takes an empirical or mechanistic approach to modeling, QSP takes a holistic approach exploring whole biochemical and metabolic pathways and how drugs interact in those pathways. These models are often unidentifiable from any single set of data. Instead they are built using diverse datasets with many parameters fixed to mean values from different experiments resulting in models that are over-confident in their parameter values. Few models currently take into account these sources of variability in their parameter estimation. This chapter discusses nonlinear mixed effects models, a modeling approach that specifically accounts for sources of variability in a model, and their application to QSP.