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A Strategy to Refine the Phenotyping Approach and Its Implementation to Predict Drug Clearance: A Physiologically Based Pharmacokinetic Simulation Study

The phenotyping approach to predict drug metabolism activity is often hampered by a lack of correlation between the probe and the drug of interest. In this article, we present a strategy to refine the phenotyping approach based on a physiologically based pharmacokinetic simulation (implemented in Si...

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Detalles Bibliográficos
Autores principales: Adiwidjaja, Jeffry, Boddy, Alan V., McLachlan, Andrew J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6310868/
https://www.ncbi.nlm.nih.gov/pubmed/30260092
http://dx.doi.org/10.1002/psp4.12355
Descripción
Sumario:The phenotyping approach to predict drug metabolism activity is often hampered by a lack of correlation between the probe and the drug of interest. In this article, we present a strategy to refine the phenotyping approach based on a physiologically based pharmacokinetic simulation (implemented in Simcyp Simulator version 17) using previously published models. The apparent clearance (CL/F) of erlotinib was better predicted by the sum of caffeine and i.v. midazolam CL/F (r (2) = 0.60) compared to that of either probe drug alone. The clearance of atorvastatin and repaglinide had a strong correlation (r (2) = 0.70 and 0.63, respectively) with that of pitavastatin (a SLCO1B1 probe). Use of multiple probes for drugs that are predominantly metabolized by more than one cytochrome P450 (CYP) enzyme should be considered. In a case in which hepatic uptake transporters play a significant role in the disposition of a drug, the pharmacokinetic of a transporter probe will provide better predictions of the drug clearance.