Evaluation of a basic physiologically based pharmacokinetic model for simulating the first-time-in-animal study
| Autor: | Philip S. Burton, Massimiliano Germani, Patrizia Crivori, Italo Poggesi, Mark E. Smith, Maurizio Rocchetti, Alan G. E. Wilson |
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| Rok vydání: | 2007 |
| Předmět: |
Prioritization
Physiologically based pharmacokinetic modelling Drug Evaluation Preclinical Pharmaceutical Science Rodentia Pharmacology Models Biological Benzodiazepines Diltiazem Mice Troglitazone Anti-Infective Agents Pharmaceutical technology Pharmacokinetics Acetamides Animals Hypoglycemic Agents Tissue Distribution Animal study Chromans Oxazolidinones Mathematics Principal Component Analysis Drug discovery Linezolid Antidepressive Agents Rats Liver metabolism Liver Thiazolidinediones Biological system Zidovudine Algorithms In vivo pharmacokinetics |
| Zdroj: | European Journal of Pharmaceutical Sciences. 31:190-201 |
| ISSN: | 0928-0987 |
| DOI: | 10.1016/j.ejps.2007.03.008 |
| Popis: | The objective of this study was to evaluate a physiologically based pharmacokinetic (PBPK) approach for predicting the plasma concentration-time curves expected after intravenous administration of candidate drugs to rodents. The predictions were based on a small number of properties that were either calculated based on the structure of the candidate drug (octanol:water partition coefficient, ionization constant(s)) or obtained from the typical high-throughput screens implemented in the early drug discovery phases (fraction unbound in plasma and hepatic intrinsic clearance). The model was tested comparing the predicted and the observed pharmacokinetics of 45 molecules. This dataset included six known drugs and 39 drug candidates from different discovery programs, so that the performance of the model could be evaluated in a real discovery case scenario. The plasma concentration-time curves were predicted with good accuracy, the pharmacokinetic parameters being on average two- to three-fold of actual values. Multivariate analysis was used for identifying the candidate properties which were likely associated to biased predictions. The application of this approach was found useful for the prioritization of the in vivo pharmacokinetics screens and the design of the first-time-in-animal studies. |
| Databáze: | OpenAIRE |
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