Literature DB >> 22489626

pH-Dependent solubility and permeability criteria for provisional biopharmaceutics classification (BCS and BDDCS) in early drug discovery.

Manthena V Varma1, Iain Gardner, Stefanus J Steyn, Paul Nkansah, Charles J Rotter, Carrie Whitney-Pickett, Hui Zhang, Li Di, Michael Cram, Katherine S Fenner, Ayman F El-Kattan.   

Abstract

The Biopharmaceutics Classification System (BCS) is a scientific framework that provides a basis for predicting the oral absorption of drugs. These concepts have been extended in the Biopharmaceutics Drug Disposition Classification System (BDDCS) to explain the potential mechanism of drug clearance and understand the effects of uptake and efflux transporters on absorption, distribution, metabolism, and elimination. The objective of present work is to establish criteria for provisional biopharmaceutics classification using pH-dependent passive permeability and aqueous solubility data generated from high throughput screening methodologies in drug discovery settings. The apparent permeability across monolayers of clonal cell line of Madin-Darby canine kidney cells, selected for low endogenous efflux transporter expression, was measured for a set of 105 drugs, with known BCS and BDDCS class. The permeability at apical pH 6.5 for acidic drugs and at pH 7.4 for nonacidic drugs showed a good correlation with the fraction absorbed in human (Fa). Receiver operating characteristic (ROC) curve analysis was utilized to define the permeability class boundary. At permeability ≥ 5 × 10(-6) cm/s, the accuracy of predicting Fa of ≥ 0.90 was 87%. Also, this cutoff showed more than 80% sensitivity and specificity in predicting the literature permeability classes (BCS), and the metabolism classes (BDDCS). The equilibrium solubility of a subset of 49 drugs was measured in pH 1.2 medium, pH 6.5 phosphate buffer, and in FaSSIF medium (pH 6.5). Although dose was not considered, good concordance of the measured solubility with BCS and BDDCS solubility class was achieved, when solubility at pH 1.2 was used for acidic compounds and FaSSIF solubility was used for basic, neutral, and zwitterionic compounds. Using a cutoff of 200 μg/mL, the data set suggested a 93% sensitivity and 86% specificity in predicting both the BCS and BDDCS solubility classes. In conclusion, this study identified pH-dependent permeability and solubility criteria that can be used to assign provisional biopharmaceutics class at early stage of the drug discovery process. Additionally, such a classification system will enable discovery scientists to assess the potential limiting factors to oral absorption, as well as help predict the drug disposition mechanisms and potential drug-drug interactions.

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Year:  2012        PMID: 22489626     DOI: 10.1021/mp2004912

Source DB:  PubMed          Journal:  Mol Pharm        ISSN: 1543-8384            Impact factor:   4.939


  19 in total

1.  Physiologically based modeling of pravastatin transporter-mediated hepatobiliary disposition and drug-drug interactions.

Authors:  Manthena V S Varma; Yurong Lai; Bo Feng; John Litchfield; Theunis C Goosen; Arthur Bergman
Journal:  Pharm Res       Date:  2012-05-26       Impact factor: 4.200

Review 2.  BDDCS Predictions, Self-Correcting Aspects of BDDCS Assignments, BDDCS Assignment Corrections, and Classification for more than 175 Additional Drugs.

Authors:  Chelsea M Hosey; Rosa Chan; Leslie Z Benet
Journal:  AAPS J       Date:  2015-11-20       Impact factor: 4.009

3.  Discovery of an in Vivo Tool to Establish Proof-of-Concept for MAP4K4-Based Antidiabetic Treatment.

Authors:  Mark Ammirati; Scott W Bagley; Samit K Bhattacharya; Leonard Buckbinder; Anthony A Carlo; Rebecca Conrad; Christian Cortes; Robert L Dow; Matthew S Dowling; Ayman El-Kattan; Kristen Ford; Cristiano R W Guimarães; David Hepworth; Wenhua Jiao; Jennifer LaPerle; Shenping Liu; Allyn Londregan; Paula M Loria; Alan M Mathiowetz; Michael Munchhof; Suvi T M Orr; Donna N Petersen; David A Price; Athanasia Skoura; Aaron C Smith; Jian Wang
Journal:  ACS Med Chem Lett       Date:  2015-10-06       Impact factor: 4.345

4.  Predicting Clearance Mechanism in Drug Discovery: Extended Clearance Classification System (ECCS).

Authors:  Manthena V Varma; Stefanus J Steyn; Charlotte Allerton; Ayman F El-Kattan
Journal:  Pharm Res       Date:  2015-07-09       Impact factor: 4.200

5.  Re-evaluation of Quillaia extract (E 999) as a food additive and safety of the proposed extension of use.

Authors:  Maged Younes; Gabriele Aquilina; Laurence Castle; Karl-Heinz Engel; Paul Fowler; Maria Jose Frutos Fernandez; Peter Fürst; Rainer Gürtler; Ursula Gundert-Remy; Trine Husøy; Wim Mennes; Agneta Oskarsson; Romina Shah; Ine Waalkens-Berendsen; Detlef Wölfle; Polly Boon; Claude Lambré; Paul Tobback; Matthew Wright; Ana Maria Rincon; Camilla Smeraldi; Alexandra Tard; Peter Moldeus
Journal:  EFSA J       Date:  2019-03-06

6.  Predicting the extent of metabolism using in vitro permeability rate measurements and in silico permeability rate predictions.

Authors:  Chelsea M Hosey; Leslie Z Benet
Journal:  Mol Pharm       Date:  2015-04-23       Impact factor: 4.939

7.  Reliable Rate Measurements for Active and Passive Hepatic Uptake Using Plated Human Hepatocytes.

Authors:  Yi-An Bi; Renato J Scialis; Sarah Lazzaro; Sumathy Mathialagan; Emi Kimoto; Julie Keefer; Hui Zhang; Anna M Vildhede; Chester Costales; A David Rodrigues; Larry M Tremaine; Manthena V S Varma
Journal:  AAPS J       Date:  2017-02-10       Impact factor: 4.009

8.  Projecting ADME Behavior and Drug-Drug Interactions in Early Discovery and Development: Application of the Extended Clearance Classification System.

Authors:  Ayman F El-Kattan; Manthena V Varma; Stefan J Steyn; Dennis O Scott; Tristan S Maurer; Arthur Bergman
Journal:  Pharm Res       Date:  2016-09-12       Impact factor: 4.200

Review 9.  The role of BCS (biopharmaceutics classification system) and BDDCS (biopharmaceutics drug disposition classification system) in drug development.

Authors:  Leslie Z Benet
Journal:  J Pharm Sci       Date:  2012-11-12       Impact factor: 3.534

10.  Novel high/low solubility classification methods for new molecular entities.

Authors:  Rutwij A Dave; Marilyn E Morris
Journal:  Int J Pharm       Date:  2016-06-24       Impact factor: 5.875

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