Population pharmacometrics in support of analgesics studies

Abstract

Population pharmacometric modeling is used to explain both population trends as well as the sources and magnitude of variability in pharmacokinetic and pharmacodynamics data; the later, in part, by taking into account patient characteristics such as weight, age, renal function and genetics. The approach is best known for its ability to analyze sparse data, i.e. when only a few measurements have been collected from each subject, but other benefits include its flexibility and the potential to construct more detailed models than those used in the traditional individual curve fitting approach. This review presents the basic concepts of population pharmacokinetic and pharmacodynamic modeling and includes several analgesic drug examples. In addition, the use of these models to design and optimize future studies is discussed. In this context, finding the best design factors, such as the sampling times or the dose, for future studies within pre-defined criteria using a previously constructed population pharmacokinetic model can help researchers acquire clinically meaningful data without wasting resources and unnecessarily exposing vulnerable patient groups to study drugs and additional blood sampling.