Literature DB >> 14998573

PAMPA--a drug absorption in vitro model 7. Comparing rat in situ, Caco-2, and PAMPA permeability of fluoroquinolones.

Marival Bermejo1, Alex Avdeef, Ana Ruiz, Ricardo Nalda, Jeffrey A Ruell, Oksana Tsinman, Isabel González, Carlos Fernández, Gloria Sánchez, Teresa M Garrigues, Virginia Merino.   

Abstract

Parallel artificial membrane permeability assay (PAMPA) was used to measure the effective permeability, P(e), as a function of pH from 4 to 10, of 17 fluoroquinolones, including three congeneric series with systematically varied alkyl chain length at the 4'N-position of the piperazine residue. The permeability values spanned over three orders of magnitude. The intrinsic permeability, P(o), and the membrane permeability, P(m), were determined from the pH dependence of the effective permeability. The pK(a) values were determined potentiometrically. The PAMPA method employed stirring, adjusted such that the unstirred water layer (UWL) thickness matched the 30-100 microm range estimated to be in the human small intestine. The intrinsic permeability coefficients (10(-6)cm/s), representing the permeability of the uncharged form of the drug, are for 4'N-R-norfloxacin: 0.7 (R=H), 49 (Me), 132 (n-Pr), 365 (n-Bu); 4'N-R-ciprofloxacin: 2.7 (H), 37 (Me), 137 (n-Pr), 302 (n-Bu); 4'N-R-3'-methylciprofloxacin: 3.8 (H), 20 (Me), 51 (Et), 160 (n-Pr), 418 (n-Bu). Increasing the alkyl chain length in the congeneric series resulted in increased permeability, averaging about 0.34 log units per methylene group, except that of the first (H-to-Me), which was about 1.2 log units. These results were compared to Caco-2 and rat in situ permeability measurements. The in situ closed loop technique used for obtaining permeability values in rat showed a water layer thickness effect quite consistent with in vivo expectations. The rat-PAMPA correlation (r2=0.87) was better than that of rat-Caco-2 (r2=0.63). Caco-2-PAMPA correlation indicated r2=0.66. The latter correlation improved significantly (r2=0.82) when the Caco-2 data were corrected for the UWL effect.

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Year:  2004        PMID: 14998573     DOI: 10.1016/j.ejps.2003.10.009

Source DB:  PubMed          Journal:  Eur J Pharm Sci        ISSN: 0928-0987            Impact factor:   4.384


  28 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

2.  Highly predictive and interpretable models for PAMPA permeability.

Authors:  Hongmao Sun; Kimloan Nguyen; Edward Kerns; Zhengyin Yan; Kyeong Ri Yu; Pranav Shah; Ajit Jadhav; Xin Xu
Journal:  Bioorg Med Chem       Date:  2016-12-31       Impact factor: 3.641

3.  Permeation of aromatic carboxylic acids across lipid bilayers: the pH-partition hypothesis revisited.

Authors:  Anita V Thomae; Heidi Wunderli-Allenspach; Stefanie D Krämer
Journal:  Biophys J       Date:  2005-06-10       Impact factor: 4.033

Review 4.  Pharmacophore-based discovery of ligands for drug transporters.

Authors:  Cheng Chang; Sean Ekins; Praveen Bahadduri; Peter W Swaan
Journal:  Adv Drug Deliv Rev       Date:  2006-09-26       Impact factor: 15.470

5.  Evaluation of the membrane permeability (PAMPA and skin) of benzimidazoles with potential cannabinoid activity and their relation with the Biopharmaceutics Classification System (BCS).

Authors:  M Javiera Alvarez-Figueroa; C David Pessoa-Mahana; M Elisa Palavecino-González; Jaime Mella-Raipán; Cristián Espinosa-Bustos; Manuel E Lagos-Muñoz
Journal:  AAPS PharmSciTech       Date:  2011-05-04       Impact factor: 3.246

6.  Comparison of drug permeabilities and BCS classification: three lipid-component PAMPA system method versus Caco-2 monolayers.

Authors:  Zeynep S Teksin; Paul R Seo; James E Polli
Journal:  AAPS J       Date:  2010-03-12       Impact factor: 4.009

7.  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

8.  Testing physical models of passive membrane permeation.

Authors:  Siegfried S F Leung; Jona Mijalkovic; Kenneth Borrelli; Matthew P Jacobson
Journal:  J Chem Inf Model       Date:  2012-05-24       Impact factor: 4.956

9.  Utilizing In Vitro Dissolution-Permeation Chamber for the Quantitative Prediction of pH-Dependent Drug-Drug Interactions with Acid-Reducing Agents: a Comparison with Physiologically Based Pharmacokinetic Modeling.

Authors:  Andy Z X Zhu; Ming-Chih David Ho; Christopher K Gemski; Bei-Ching Chuang; Mingxiang Liao; Cindy Q Xia
Journal:  AAPS J       Date:  2016-09-06       Impact factor: 4.009

10.  PAMPA - excipient classification gradient map.

Authors:  Stefanie Bendels; Oksana Tsinman; Björn Wagner; Dana Lipp; Isabelle Parrilla; Manfred Kansy; Alex Avdeef
Journal:  Pharm Res       Date:  2006-10-20       Impact factor: 4.200

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