Population pharmacokinetics is the study of sources and correlates of variability in drug exposure and response. The study of population pharmacokinetics represents an important aspect of drug development and plays a key role in finding the right dose to inform product labeling decisions. Application of novel mathematical and statistical tools to the study of population pharmacokinetics has revolutionized the drug development process. Pharmacostatistical models composed on pharmacokinetic, pharmacodynamic, disease progression, trial design aspects, and econometrics are widely used in decision-making at every stage of drug development. Nonlinear mixed-effects modeling methodology enables the analysis of sparsely collected pharmacokinetic and pharmacodynamic data from large-scale late-stage clinical trials to understand drug exposure-response relationships. Regulatory authorities such as the US FDA and EMEA have supported and worked with pharmaceutical industry to bring about a successful culture of change in drug development, which has evolved into a concept called model-based drug development (MBDD). MBDD uses modeling and simulation to implement a "learn and confirm" paradigm. This chapter is intended to provide the reader with a basic understanding of the various methods involved in population pharmacokinetics with an emphasis on the current gold standard of nonlinear mixed-effects modeling methodology.
|Title of host publication||Applied Clinical Pharmacokinetics and Pharmacodynamics of Psychopharmacological Agents|
|Publisher||Springer International Publishing|
|Number of pages||20|
|State||Published - 1 Jan 2016|
- Nonlinear mixed-effects modeling (NONMEM)
- Population pharmacokinetics