Non-compartment model to compartment model pharmacokinetics transformation meta-analysis – a multivariate nonlinear mixed model

Background To fulfill the model based drug development, the very first step is usually a model establishment from published literatures. Pharmacokinetics model is the central piece of model based drug development. This paper proposed an important approach to transform published non-compartment model pharmacokinetics (PK) parameters into compartment model PK parameters. This meta-analysis was performed with a multivariate nonlinear mixed model. A conditional first-order linearization approach was developed for statistical estimation and inference. Results Using MDZ as an example, we showed that this approach successfully transformed 6 non-compartment model PK parameters from 10 publications into 5 compartment model PK parameters. In simulation studies, we showed that this multivariate nonlinear mixed model had little relative bias (<1%) in estimating compartment model PK parameters if all non-compartment PK parameters were reported in every study. If there missing non-compartment PK parameters existed in some published literatures, the relative bias of compartment model PK parameter was still small (<3%). The 95% coverage probabilities of these PK parameter estimates were above 85%. Conclusions This non-compartment model PK parameter transformation into compartment model meta-analysis approach possesses valid statistical inference. It can be routinely used for model based drug development

Safety and pharmacokinetics of the CIME combination of drugs and their metabolites after a single oral dosing in healthy volunteers

International audienceThis phase I, pilot clinical study was designed to evaluate the safety and the pharmacokinetic (PK) profiles of the CIME (Metabolic Identity Card) combination of ten drugs, with a view to its use as a phenotyping cocktail. Ten healthy Caucasian subjects were orally dosed with the CIME combination (caffeine-CYP1A2, repaglinide-CYP2C8, tolbutamide-CYP2C9, omeprazole-CYP2C19, dextromethorphan-CYP2D6, midazolam-CYP3A, acetaminophen-UGT1A1, 6&9 and 2B15, digoxin-P-gp, rosuvastatin-OATP1B1&3 and memantine-active renal transport). Blood was collected over 3 days and on day 7. CIME probes and relevant metabolites were assayed by LC-MS/MS and PK parameters were calculated. Main results were: (1) good safety with reversible mild or moderate adverse effects, (2) an analytical method able to quantify simultaneously the 10 probes and the major metabolites, (3) calculation of PK parameters for all probes in general agreed with published values, and (4) identification of the low CYP2D6 metabolizer. This pilot study showed that the CIME combination was well tolerated and that its pharmacokinetics could be accurately measured in healthy volunteers. This combination can now confidently be checked for sensitivity and specificity and for lack of interaction to be validated as a phenotyping cocktail