期刊
PHARMACEUTICAL RESEARCH
卷 32, 期 12, 页码 3785-3802出版社
SPRINGER/PLENUM PUBLISHERS
DOI: 10.1007/s11095-015-1749-4
关键词
extended clearance classification system (ECCS); hepatic uptake; metabolism; permeability; renal clearance
Early prediction of clearance mechanisms allows for the rapid progression of drug discovery and development programs, and facilitates risk assessment of the pharmacokinetic variability associated with drug interactions and pharmacogenomics. Here we propose a scientific framework - Extended Clearance Classification System (ECCS) - which can be used to predict the predominant clearance mechanism (rate-determining process) based on physicochemical properties and passive membrane permeability. Compounds are classified as: Class 1A - metabolism as primary systemic clearance mechanism (high permeability acids/zwitterions with molecular weight (MW) a parts per thousand currency sign400 Da), Class 1B - transporter-mediated hepatic uptake as primary systemic clearance mechanism (high permeability acids/zwitterions with MW > 400 Da), Class 2 - metabolism as primary clearance mechanism (high permeability bases/neutrals), Class 3A -renal clearance (low permeability acids/zwitterions with MW a parts per thousand currency sign400 Da), Class 3B - transporter mediated hepatic uptake or renal clearance (low permeability acids/zwitterions with MW > 400 Da), and Class 4 - renal clearance (low permeability bases/neutrals). The performance of the ECCS framework was validated using 307 compounds with single clearance mechanism contributing to a parts per thousand yen70% of systemic clearance. The apparent permeability across clonal cell line of Madin -aEuro parts per thousand Darby canine kidney cells, selected for low endogenous efflux transporter expression, with a cut-off of 5 x 10(-6) cm/s was used for permeability classification, and the ionization (at pH7) was assigned based on calculated pKa. The proposed scheme correctly predicted the rate-determining clearance mechanism to be either metabolism, hepatic uptake or renal for similar to 92% of total compounds. We discuss the general characteristics of each ECCS class, as well as compare and contrast the framework with the biopharmaceutics classification system (BCS) and the biopharmaceutics drug disposition classification system (BDDCS). Collectively, the ECCS framework is valuable in early prediction of clearance mechanism and can aid in choosing the right preclinical tool kit and strategy for optimizing drug exposure and evaluating clinical risk of pharmacokinetic variability caused by drug interactions and pharmacogenomics.
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