Literature DB >> 8819002

Novel approach to the analysis of in vitro-in vivo relationships.

J E Polli1, J R Crison, G L Amidon.   

Abstract

The objective of this study was to quantify the dependence of degree of in vitro-in vivo correlation on the relative rates of dissolution and intestinal permeation and on the fraction of dose absorbed. The following equation was derived assuming first-order dissolution and permeation after oral drug administration: Fa = fa-1(1 - alpha(alpha - 1)-1 (1 - Fd) + (alpha - 1)-1(1 - Fd)alpha), where Fa is the fraction of the total amount of drug absorbed at time t, fa the fraction of the dose absorbed at t = infinitive, alpha is the ratio of the first-order permeation rate constant to the first-order dissolution rate constant, and Fd is the fraction of dose dissolved in vitro at time t. This equation was examined in order to pursue a theoretical treatment of in vitro-in vivo correlation. The degree of in vitro-in vivo correlation between Fa and Fd was measured by r2. alpha was varied between 1000 and 0.001. fa was varied between 0.1 and 1.0. Points employed in the linear regression were geometrically balanced about the derived equation. r2 values decreased as alpha decreased for all values of fa. r2 values were virtually independent of fa for all values of alpha, except for 0.01 < alpha < 1.0. The slope of the regression was modulated by both alpha and fa; larger alpha and smaller fa each increased slope. Application of the equation to a piroxicam data set demonstrated the equation's utility relative to the USP Level A correlation approach. It is concluded that the degree of in vitro-in vivo correlation depends on the relative rates of dissolution and intestinal permeation and on the fraction of dose absorbed and that the derived model merits further study.

Keywords:  Non-programmatic

Mesh:

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Year:  1996        PMID: 8819002     DOI: 10.1021/js9503587

Source DB:  PubMed          Journal:  J Pharm Sci        ISSN: 0022-3549            Impact factor:   3.534


  13 in total

1.  In vivo-in vitro correlation (IVIVC) modeling incorporating a convolution step.

Authors:  T O'Hara; S Hayes; J Davis; J Devane; T Smart; A Dunne
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2.  Prediction of modified release pharmacokinetics and pharmacodynamics from in vitro, immediate release, and intravenous data.

Authors:  Viera Lukacova; Walter S Woltosz; Michael B Bolger
Journal:  AAPS J       Date:  2009-05-09       Impact factor: 4.009

Review 3.  Clinical relevance of dissolution testing in quality by design.

Authors:  Paul A Dickinson; Wang Wang Lee; Paul W Stott; Andy I Townsend; John P Smart; Parviz Ghahramani; Tracey Hammett; Linda Billett; Sheena Behn; Ryan C Gibb; Bertil Abrahamsson
Journal:  AAPS J       Date:  2008-08-07       Impact factor: 4.009

4.  A population growth model of dissolution.

Authors:  A Dokoumetzidis; P Macheras
Journal:  Pharm Res       Date:  1997-09       Impact factor: 4.200

5.  Mathematical Models to Explore Potential Effects of Supersaturation and Precipitation on Oral Bioavailability of Poorly Soluble Drugs.

Authors:  Mary S Kleppe; Kelly M Forney-Stevens; Roy J Haskell; Robin H Bogner
Journal:  AAPS J       Date:  2015-04-08       Impact factor: 4.009

6.  Development of a bionic system for the simultaneous prediction of the release/absorption characteristics of enteric-coated formulations.

Authors:  Weijun Liu; Xin He; Ziqiang Li; Xiumei Gao; Yetao Ma; Mingjin Xun; Changxiao Liu
Journal:  Pharm Res       Date:  2012-11-08       Impact factor: 4.200

7.  Human drug absorption kinetics and comparison to Caco-2 monolayer permeabilities.

Authors:  J E Polli; M J Ginski
Journal:  Pharm Res       Date:  1998-01       Impact factor: 4.200

Review 8.  In vitro-in vivo correlation: perspectives on model development.

Authors:  Ying Lu; Sungwon Kim; Kinam Park
Journal:  Int J Pharm       Date:  2011-01-13       Impact factor: 5.875

9.  Prediction of dissolution-absorption relationships from a continuous dissolution/Caco-2 system.

Authors:  M J Ginski; R Taneja; J E Polli
Journal:  AAPS PharmSci       Date:  1999

10.  Feasibility of biowaiver extension to biopharmaceutics classification system class III drug products: cimetidine.

Authors:  Ekarat Jantratid; Sompol Prakongpan; Gordon L Amidon; Jennifer B Dressman
Journal:  Clin Pharmacokinet       Date:  2006       Impact factor: 6.447

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