Literature DB >> 17990312

A comparison of the prediction accuracy of two IVIVC modelling techniques.

Clare Gaynor1, Adrian Dunne, John Davis.   

Abstract

The goal when developing an in vitro-in vivo correlation (IVIVC) model is the ability to accurately predict the in vivo plasma concentration profile of a drug formulation using only its in vitro dissolution data. The prediction accuracy of any model depends on the reliability of the method used to develop it. Some statistical concerns regarding methods based on deconvolution have been highlighted and a convolution based technique has been proposed as an alternative. This comparison shows, by means of a simulation study, that the modelling approach which uses convolution produces far more accurate results, accurately predicting the observed plasma concentration-time profile and, therefore, comfortably meeting the FDA validation criteria. The fact that the model developed using the deconvolution based technique fails to describe the simulated data and thus fails the FDA validation test when it ought to pass should be of great concern to those currently implementing this method.

Mesh:

Year:  2008        PMID: 17990312     DOI: 10.1002/jps.21220

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


  12 in total

1.  In vitro-in vivo correlations: tricks and traps.

Authors:  J-M Cardot; B M Davit
Journal:  AAPS J       Date:  2012-05-01       Impact factor: 4.009

2.  Comparison of Deconvolution-Based and Absorption Modeling IVIVC for Extended Release Formulations of a BCS III Drug Development Candidate.

Authors:  Filippos Kesisoglou; Binfeng Xia; Nancy G B Agrawal
Journal:  AAPS J       Date:  2015-08-20       Impact factor: 4.009

3.  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

4.  A population approach to in vitro-in vivo correlation modelling for compounds with nonlinear kinetics.

Authors:  Clare Gaynor; Adrian Dunne; Cian Costello; John Davis
Journal:  J Pharmacokinet Pharmacodyn       Date:  2011-03-16       Impact factor: 2.745

5.  A time scaling approach to develop an in vitro-in vivo correlation (IVIVC) model using a convolution-based technique.

Authors:  Cian Costello; Stefaan Rossenu; An Vermeulen; Adriaan Cleton; Adrian Dunne
Journal:  J Pharmacokinet Pharmacodyn       Date:  2011-07-07       Impact factor: 2.745

6.  In vitro- in vivo correlation's dissolution limits setting.

Authors:  B Roudier; B M Davit; E Beyssac; J-M Cardot
Journal:  Pharm Res       Date:  2014-03-28       Impact factor: 4.200

7.  Regulatory Experience with In Vivo In Vitro Correlations (IVIVC) in New Drug Applications.

Authors:  Sandra Suarez-Sharp; Min Li; John Duan; Heta Shah; Paul Seo
Journal:  AAPS J       Date:  2016-08-01       Impact factor: 4.009

8.  Evaluating In Vivo-In Vitro Correlation Using a Bayesian Approach.

Authors:  Junshan Qiu; Marilyn Martinez; Ram Tiwari
Journal:  AAPS J       Date:  2016-02-19       Impact factor: 4.009

9.  Comparison of Alternative Population Modeling Approaches for Implementing a Level A IVIVC and for Assessing the Time-Scaling Factor Using Deconvolution and Convolution-Based Methods.

Authors:  Roberto Gomeni; Françoise Bressolle-Gomeni
Journal:  AAPS J       Date:  2020-04-15       Impact factor: 4.009

10.  Screening of Bioequivalent Extended-Release Formulations for Metformin by Principal Component Analysis and Convolution-Based IVIVC Approach.

Authors:  Yufeng Zhang; Hua Liu; Minghui Johnson Tang; Nicolas James Ho; Tsun Lam Shek; Zhijun Yang; Zhong Zuo
Journal:  AAPS J       Date:  2021-03-04       Impact factor: 4.009

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