Pharmacodynamic-Pharmacokinetic Integration as a Guide to Medicinal Chemistry

Johan      Gabrielsson; Ola      Fjellstrom; Johan      Ulander; Michael      Rowley; Piet      H. Van Der Graaf

Abstract

A primary objective of pharmacokinetic-pharmacodynamic (PKPD) reasoning is to identify key in vivo drug and system properties, enabling prediction of the magnitude and time course of drug responses under physiological and pathological conditions in animals and man. Since the pharmacological response generated by a drug is highly dependent on the actual system used to study its action, knowledge about its potency and efficacy at a given concentration or dose is insufficient to obtain a proper understanding of its pharmacodynamic profile. Hence, the output of PKPD activities extends beyond the provision of quantitative measures (models) of results, to the design of future protocols. Furthermore, because PKPD integrates DMPK (e.g. clearance) and pharmacology (e.g. potency),it provides an anchor point for compound selection, and, as such, should be viewed as an important weapon in medicinal chemistry. Here we outline key PK concepts relevant to PD, and then consider real-life experiments to illustrate the importance to the medicinal chemist of data obtained by PKPD. Useful assumptions and potential pitfalls are described, providing a holistic view of the plethora of determinants behind in vitro-in vivo correlations. By condensing complexity to simplicity, there are not only consequences for experimental design, and for the ranking and design of compounds, but it is also possible to make important predictions such as the impact of changes in drug potency and kinetics. In short, by using quantitative methods to tease apart pharmacodynamic complexities such as temporal differences and changes in plasma protein binding, it is possible to target the changes necessary for improving a compounds profile.

Keywords: Mechanism-based PKPD modelling, potency, efficacy, lipophilicity, structure-activity relationship, turnover models, effect compartment models, occupancy binding models