Linking preclinical and clinical whole body physiologically-based pharmacokinetic models with prior distributions in NONMEM
Langdon G (1), Gueorguieva I (2), Aarons L (3), Karlsson MO (1)
(1) Division of Pharmacokinetics and Drug Therapy, Uppsala University, Sweden; (2) Eli Lilly & Company Ltd, Surrey, United Kingdom; (3) School of Pharmacy and Pharmaceutical Sciences, University of Manchester, Manchester, United Kingdom
Purpose: The aim of this study was to evaluate the performance of the NONMEM prior functionality compared to a full Bayesian method when applied to population physiological models using diazepam as a case study.
Methods: Whole body physiologically based pharmacokinetic (WBPBPK) models for diazepam were initially developed, tested and calibrated for rats and man using a full Bayesian analysis as implemented in WinBUGS [1]. The final models were implemented in NONMEM and the results from the two analyses compared in terms of parameter estimates, measures of parameter precision and run times
Results: NONMEM mean parameter estimates were in close agreement with those produced by the full Bayesian analysis although there was a substantial improvement in run time for both the animal WBPBPK model (4.5 h vs. 21 h) and human WBPBPK models (2 h vs. 167 h). The model provided a good overall description of the plasma concentration-time data in both rat and man with comparable parameter precision.
Conclusions: The ease of implementation and reductions in run time hopefully provide a further step forward in allowing the wider use of these complex and information rich models together with clinical data in the future.
References:
[1] Gueorguieva I et al. J Pharmacokinet Pharmacodyn; 2006; In press