Retrospectively, demographic and clinical data of two similar sets of a total of 88 intensive care unit (ICU) patients were gathered for calculation and validation of 5-FC pharmacokinetics respectively. 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.The objective of this study is to compare and validate three models of flucytosine (5-FC) population pharmacokinetics using three methods of analysis to elucidate which model describes 5-FC pharmacokinetics most accurately and which method is the most suitable for this purpose.
MBDD uses modeling and simulation to implement a “learn and confirm” paradigm. 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). 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. 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. Application of novel mathematical and statistical tools to the study of population pharmacokinetics has revolutionized the drug development process. 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. Population pharmacokinetics is the study of sources and correlates of variability in drug exposure and response.
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