Guidelines for the quality control of population pharmacokinetic-pharmacodynamic analyses: an industry perspective.

Quality population modeling and simulation analyses and reports are something every modeler desires. However, little attention in the literature has been paid to what constitutes quality regarding population analyses. Very rarely do published manuscripts contain any statement about quality assurance of the modeling results contained therein. The purpose of this manuscript is to present guidelines for the quality assurance of population analyses, particularly with regards to the use of NONMEM from an industrial perspective. Quality guidelines are developed for the NONMEM installation itself, NONMEM data sets, control streams, output listings, output data files and resultant post-processing, reporting of results, and the review processes. These guidelines were developed to be thorough yet practical, though are not meant to be completely comprehensive. It is our desire to ensure that what is reported accurately reflects the collected data, the modeling process, and model outputs for a modeling project.

Modelling of the concentration--effect relationship of THC on central nervous system parameters and heart rate -- insight into its mechanisms of action and a tool for clinical research and development of cannabinoids.

Pharmacokinetics after pulmonary administration of delta-9-tetrahydrocannabinol (THC) and its major metabolites 11-OH-THC and 11-nor-9-COOH-THC was quantified. Additionally, the relationship between THC and its effects on heart rate, body sway and several visual analogue scales was investigated using pharmacokinetic-pharmacodynamic (PK-PD) modelling. This provided insights useful for the research and development of novel cannabinoids and the physiology and pharmacology of cannabinoid systems. First, the PK-PD model gave information reflecting various aspects of cannabinoid systems. The delay between THC concentration and effect was quantified in equilibration half-lives of 7.68 min for heart rate and from 39.2 to 84.8 min for the CNS responses. This suggests that the effect of THC on the different responses could be due to different sites of action or different physiological mechanisms. Differences in the shape of the concentration-effect relationship could indicate various underlying mechanisms. Second, the PK-PD model can be used for prediction of THC concentration and effect profiles. It is illustrated how this can be used to optimise studies with entirely different trial designs. Third, many new cannabinoid agonists and antagonists are in development. PK-PD models for THC can be used as a reference for new agonists or as tools to quantitate the pharmacological properties of cannabinoid antagonists.

Population pharmacokinetic modelling of the enterohepatic recirculation of diclofenac and rofecoxib in rats.

BACKGROUND AND PURPOSE: Enterohepatic recirculation (EHC) is a common pharmacokinetic phenomenon that has been poorly modelled in animals. The presence of EHC leads to the appearance of multiple peaks in the concentration-time profile and increased exposure, which may have implications for drug effect and extrapolation across species. The aim of this investigation was to develop a population pharmacokinetic model for diclofenac and rofecoxib that describes EHC and to assess its consequence for the pharmacodynamics of both drugs. EXPERIMENTAL APPROACH: The pharmacokinetics of diclofenac and rofecoxib was characterized in male rats following intravenous, intraperitoneal and oral administration. Blood samples were collected at pre-defined time points after dosing to determine plasma concentrations over time. A parametric approach using nonlinear mixed effects modelling was applied to describe EHC, whilst simulations were used to evaluate its impact on PGE(2) inhibition. KEY RESULTS: For diclofenac, EHC was described by a compartmental model with periodic transfer rate and metabolite formation rate. For rofecoxib, EHC modelling required a conversion compartment with first-order recycling rate and lag time. Based on model predictions, EHC causes an increase of 95% in the systemic exposure to diclofenac and of 15% in the exposure to rofecoxib. In addition, EHC prolongs the inhibition of PGE(2) and increases the duration of the anti-inflammatory effect (24 h for rofecoxib 10 mg kg(-1)) without affecting maximum inhibition. CONCLUSIONS AND IMPLICATIONS: Our findings show the relevance of exploring EHC in a quantitative manner to accurately interpret pharmacodynamic findings in vivo, in particular when scaling across species.