Literature DB >> 12100852

Prediction of passive intestinal absorption using bio-mimetic artificial membrane permeation assay and the paracellular pathway model.

Kiyohiko Sugano1, Noriyuki Takata, Minoru Machida, Kimitoshi Saitoh, Katsuhide Terada.   

Abstract

The purpose of this study was to construct and examine the prediction model for total passive permeation through the intestinal membrane. The paracellular pathway prediction model based on Renkin function (PP-RF) was combined with a bio-mimetic artificial membrane permeation assay (BAMPA), which is an in vitro method to predict transcellular pathway permeation, to construct the prediction model (BAMPA-PP-RF model). The parameters of the BAMPA-PP-RF model, e.g. apparent pore radius and potential drop of the paracellular pathway, were calculated from BAMPA permeability, the dissociation constant, the molecular radius and the fraction of a dose absorbed in humans consisting of 80 structurally diverse compounds. The apparent pore radius and the apparent potential drop obtained in this study were 5.61-5.65 A and 75-86 mV, respectively, and these were in accordance with the previously reported values. The mean square root error of the BAMPA-PP-RF model was 13-14%. The BAMPA-PP-RF model was shown to be able to predict the total passive permeability more adequately than BAMPA alone.

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Year:  2002        PMID: 12100852     DOI: 10.1016/s0378-5173(02)00240-5

Source DB:  PubMed          Journal:  Int J Pharm        ISSN: 0378-5173            Impact factor:   5.875


  16 in total

Review 1.  Coexistence of passive and carrier-mediated processes in drug transport.

Authors:  Kiyohiko Sugano; Manfred Kansy; Per Artursson; Alex Avdeef; Stefanie Bendels; Li Di; Gerhard F Ecker; Bernard Faller; Holger Fischer; Grégori Gerebtzoff; Hans Lennernaes; Frank Senner
Journal:  Nat Rev Drug Discov       Date:  2010-08       Impact factor: 84.694

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.  Comparative QSAR studies on PAMPA/modified PAMPA for high throughput profiling of drug absorption potential with respect to Caco-2 cells and human intestinal absorption.

Authors:  Rajeshwar P Verma; Corwin Hansch; Cynthia D Selassie
Journal:  J Comput Aided Mol Des       Date:  2007-01-26       Impact factor: 3.686

4.  QSAR application for the prediction of compound permeability with in silico descriptors in practical use.

Authors:  Kazuya Nakao; Masaaki Fujikawa; Ryo Shimizu; Miki Akamatsu
Journal:  J Comput Aided Mol Des       Date:  2009-02-25       Impact factor: 3.686

5.  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

6.  In situ artificial membrane permeation assay under hydrodynamic control: permeability-pH profiles of warfarin and verapamil.

Authors:  Matej Velický; Dan F Bradley; Kin Y Tam; Robert A W Dryfe
Journal:  Pharm Res       Date:  2010-05-07       Impact factor: 4.200

7.  Vehicle composition influence on the microneedle-enhanced transdermal flux of naltrexone hydrochloride.

Authors:  Mikolaj Milewski; Audra L Stinchcomb
Journal:  Pharm Res       Date:  2010-06-25       Impact factor: 4.200

8.  Microneedle-assisted percutaneous delivery of naltrexone hydrochloride in yucatan minipig: in vitro-in vivo correlation.

Authors:  Mikolaj Milewski; Kalpana S Paudel; Nicole K Brogden; Priyanka Ghosh; Stan L Banks; Dana C Hammell; Audra L Stinchcomb
Journal:  Mol Pharm       Date:  2013-09-23       Impact factor: 4.939

9.  Correction of permeability with pore radius of tight junctions in Caco-2 monolayers improves the prediction of the dose fraction of hydrophilic drugs absorbed by humans.

Authors:  Ryoichi Saitoh; Kiyohiko Sugano; Noriyuki Takata; Tatsuhiko Tachibana; Atsuko Higashida; Yoshiaki Nabuchi; Yoshinori Aso
Journal:  Pharm Res       Date:  2004-05       Impact factor: 4.200

10.  Distinguishing between the permeability relationships with absorption and metabolism to improve BCS and BDDCS predictions in early drug discovery.

Authors:  Caroline A Larregieu; Leslie Z Benet
Journal:  Mol Pharm       Date:  2014-03-28       Impact factor: 4.939

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