Abstract:
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The science of pharmacometrics (Pm) pertains to model-based characterization of the pharmacokinetics and pharmacological effect of drugs, which encompasses a broad variety of models, ranging from bottom-up systems pharmacology models that consist of explicit mathematical representation of biological processes, to top-down empirical models that focus mainly on a parsimonious description of the observed data. These models are being increasing utilized in the pharmaceutical industry to inform the development of drugs. Irrespective of the modeling approach and methodology, the quality of the analyses and results is highly dependent upon the quality of the data (GIGO). The types of Pm models will be reviewed, and examples of their use will be presented, along with a discussion of the varied data set requirements for these models, ranging from individual level repeated measures experimental data to summary level data gleaned from the literature. The challenges in assembling quality data sets for the various types of models, and analysis software will also be reviewed.
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