Role of Population Pharmacokinetics in Drug Development

Abstract

Population pharmacokinetic analysis is a relatively new approach which can be used to obtain important pharmacokinetic and pharmacodynamic information from sparse data sets routinely obtained in phase II and III clinical trials, these studies typically have many patients but few observations per patient. Similarly, this approach is beneficial for studies in which intensive blood sampling is not attainable, such as in children and patients with cancer and AIDS. It was not until the late 1980s and the early 1990s that this approach (which had been introduced by Sheiner and Beal approximately 20 years earlier) gained appreciable momentum. Today many pharmaceutical companies use this approach routinely, to differing extents, during their drug development process. Advocacy by the US Food and Drug Administration for pharmacokinetic screening during phase II and III studies was an important factor in the widespread adoption of this approach. A second factor was the gradual realisation that the approach can be cost effective in revealing clinically important information about the determinants of interpatient pharmacokinetic and pharmacodynamic variability in treated patients. However, several important issues remain to be resolved (such as the optimal study design, quality of the data and user-friendly software) which could determine the future role of the population approach in drug development.

Individual and population pharmacokinetic compartment analysis: a graphic procedure for quantification of predictive performance

“…These developments have enhanced the ability to conduct comprehensive pharmacokinetic studies to define population pharmacokinetics of drugs, e.g., in the pediatric population19, otherwise limited due to practical and ethical considerations20.…”

Population pharmacokinetics: an overview

“…There are excellent reviews from the pharmaceutical industry 10 and regulatory perspectives, 11 and web-based guidelines from regulatory agencies. 12,13 Studies have involved research and clinical applications in a wide variety of patients and conditions including diabetes, 9 clotting disorders, 14 …”

Population Analysis of the Pharmacokinetics of Tiagabine in Patients with Epilepsy

“…These random components and the intrapatient error terms were assumed to be mutually independent. NONMEM provides estimates of the population central values of the parameters, individual patient parameter values, related interpatient variability, SE of the parameter estimates, and the objective function value that reflects the goodness of fit of the model (6,7). The adequacy of different models in fitting the data was assessed using the minimum value of objective function.…”