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BDDCS Predictions, Self-Correcting Aspects of BDDCS Assignments, BDDCS Assignment Corrections, and Classification for More Than 175 Additional Drugs

Overview
Journal AAPS J
Specialty Pharmacology
Date 2015 Nov 22
PMID 26589308
Citations 32
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Abstract

The biopharmaceutics drug disposition classification system was developed in 2005 by Wu and Benet as a tool to predict metabolizing enzyme and drug transporter effects on drug disposition. The system was modified from the biopharmaceutics classification system and classifies drugs according to their extent of metabolism and their water solubility. By 2010, Benet et al. had classified over 900 drugs. In this paper, we incorporate more than 175 drugs into the system and amend the classification of 13 drugs. We discuss current and additional applications of BDDCS, which include predicting drug-drug and endogenous substrate interactions, pharmacogenomic effects, food effects, elimination routes, central nervous system exposure, toxicity, and environmental impacts of drugs. When predictions and classes are not aligned, the system detects an error and is able to self-correct, generally indicating a problem with initial class assignment and/or measurements determining such assignments.

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References
1.
Varma M, Feng B, Obach R, Troutman M, Chupka J, Miller H . Physicochemical determinants of human renal clearance. J Med Chem. 2009; 52(15):4844-52. DOI: 10.1021/jm900403j. View

2.
Yang X, Gandhi Y, Duignan D, Morris M . Prediction of biliary excretion in rats and humans using molecular weight and quantitative structure-pharmacokinetic relationships. AAPS J. 2009; 11(3):511-25. PMC: 2758117. DOI: 10.1208/s12248-009-9124-1. View

3.
Giacomini K, Huang S, Tweedie D, Benet L, Brouwer K, Chu X . Membrane transporters in drug development. Nat Rev Drug Discov. 2010; 9(3):215-36. PMC: 3326076. DOI: 10.1038/nrd3028. View

4.
Skolnik S, Lin X, Wang J, Chen X, He T, Zhang B . Towards prediction of in vivo intestinal absorption using a 96-well Caco-2 assay. J Pharm Sci. 2010; 99(7):3246-65. DOI: 10.1002/jps.22080. View

5.
Tapaninen T, Backman J, Kurkinen K, Neuvonen P, Niemi M . Itraconazole, a P-glycoprotein and CYP3A4 inhibitor, markedly raises the plasma concentrations and enhances the renin-inhibiting effect of aliskiren. J Clin Pharmacol. 2010; 51(3):359-67. DOI: 10.1177/0091270010365885. View