Clearance Prediction of Targeted Covalent Inhibitors by In Vitro-In Vivo Extrapolation of Hepatic and Extrahepatic Clearance Mechanisms.
Drug Metab Dispos
; 45(1): 1-7, 2017 01.
Article
em En
| MEDLINE
| ID: mdl-27784718
The concept of target-specific covalent enzyme inhibitors appears attractive from both an efficacy and a selectivity viewpoint considering the potential for enhanced biochemical efficiency associated with an irreversible mechanism. Aside from potential safety concerns, clearance prediction of covalent inhibitors represents a unique challenge due to the inclusion of nontraditional metabolic pathways of direct conjugation with glutathione (GSH) or via GSH S-transferase-mediated processes. In this article, a novel pharmacokinetic algorithm was developed using a series of Pfizer kinase selective acrylamide covalent inhibitors based on their in vitro-in vivo extrapolation of systemic clearance in rats. The algorithm encompasses the use of hepatocytes as an in vitro model for hepatic clearance due to oxidative metabolism and GSH conjugation, and the use of whole blood as an in vitro surrogate for GSH conjugation in extrahepatic tissues. Initial evaluations with clinical covalent inhibitors suggested that the scaling algorithm developed from rats may also be useful for human clearance prediction when species-specific parameters, such as hepatocyte and blood stability and blood binding, were considered. With careful consideration of clearance mechanisms, the described in vitro-in vivo extrapolation approach may be useful to facilitate candidate optimization, selection, and prediction of human pharmacokinetic clearance during the discovery and development of targeted covalent inhibitors.
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Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Plasma
/
Microssomos Hepáticos
/
Preparações Farmacêuticas
/
Hepatócitos
/
Inibidores de Proteínas Quinases
/
Modelos Biológicos
Tipo de estudo:
Prognostic_studies
/
Risk_factors_studies
Limite:
Animals
/
Humans
/
Male
Idioma:
En
Revista:
Drug Metab Dispos
Ano de publicação:
2017
Tipo de documento:
Article