Using pharmacokinetic/pharmacodynamic modelling in safety pharmacology to better define safety margins: a regional workshop of the Safety Pharmacology Society.

This meeting was convened to encourage the incorporation of empirical and mechanism-based pharmacokinetic/pharmacodynamic (PK/PD) modelling into safety pharmacology to improve the predictability of nonclinical investigations for human outcomes. These technologies make use of mathematical expressions relating measured variables to derive essential parameters for describing responses and predicting the behaviour of biological systems to a drug. Hence, empirical PK/PD modelling is intended to define the in vivo interrelationship between three basic entities: time; drug concentrations; and drug effects. The most widely applied equation relating drug bioresponses to plasma concentrations is the Hill sigmoidal E(max) model, which allows the calculation of drug potency (EC(50)) and intrinsic activity (E(max)). However, since the latter parameters depend on attributes of the drug and on the biological system itself, this approach can fail to accurately foretell drug concentration-effect behaviour, particularly between species. A particular phenomenon of PK/PD analysis is hysteresis, which refers to the delay of the bioresponse time-course with respect to exposure time-course, as this provides valuable information on the direct or indirect nature of the drug mechanism of action. The application of these concepts to the examination of the QT interval prolongation produced by dofetilide was discussed. A development surmounting the limitations of empirical PK/PD models is mechanism-based PK/PD modelling because its toolkits integrate specific mathematical expressions replicating the drug (e.g., affinity, intrinsic efficacy), and the physiological system (e.g., nonlinear, time-dependent, transduction processes), properties that play a crucial role in the cascade of biological events culminating in bioresponses. The usefulness of this approach was illustrated by a thorough analysis of nonclinical respiratory depressant and antinociceptive data on buprenorphine and fentanyl for successfully predicting the human safety and efficacy of these analgesic agents. Thus, PK/PD models can be viewed as in silico clones of drug and biological system activities that provide high-level knowledge that can avoid inappropriate attrition, and hasten the progress, of novel drugs, along the entire critical path of pharmaceutical development.