Literature DB >> 24854895

Statistical comparison of dissolution profiles to predict the bioequivalence of extended release formulations.

J D Gomez-Mantilla1, U F Schaefer, V G Casabo, T Lehr, C M Lehr.   

Abstract

Appropriate setting of dissolution specification of extended release (ER) formulations should include precise definition of a multidimensional space of complex definition and interpretation, including limits in dissolution parameters, lag time (t-lag), variability, and goodness of fit. This study aimed to set dissolution specifications of ER by developing drug-specific dissolution profile comparison tests (DPC tests) that are able to detect differences in release profiles between ER formulations that represent a lack of bioequivalence (BE). Dissolution profiles of test formulations were simulated using the Weibull and Hill models. Differential equations based in vivo-in vitro correlation (IVIVC) models were used to simulate plasma concentrations. BE trial simulations were employed to find the formulations likely to be declared bioequivalent and nonbioequivalent (BE space). Customization of DPC tests was made by adjusting the delta of a recently described tolerated difference test (TDT) or the limits of rejection of f2. Drug ka (especially if ka is small), formulation lag time (t-lag), the number of subjects included in the BE studies, and the number of sampled time points in the DPC test were the factors that affected the most these setups of dissolution specifications. Another recently described DPC test, permutation test (PT), showed excellent statistical power. All the formulations declared as similar with PT were also bioequivalent. Similar case-specific studies may support the biowaiving of ER drug formulations based on customized DPC tests.

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Year:  2014        PMID: 24854895      PMCID: PMC4070268          DOI: 10.1208/s12248-014-9615-6

Source DB:  PubMed          Journal:  AAPS J        ISSN: 1550-7416            Impact factor:   4.009


  44 in total

1.  Dissolution testing as a prognostic tool for oral drug absorption: dissolution behavior of glibenclamide.

Authors:  R Löbenberg; J Krämer; V P Shah; G L Amidon; J B Dressman
Journal:  Pharm Res       Date:  2000-04       Impact factor: 4.200

2.  In vitro-in vivo correlation (IVIVC) models for metformin after administration of modified-release (MR) oral dosage forms to healthy human volunteers.

Authors:  G Balan; P Timmins; D S Greene; P H Marathe
Journal:  J Pharm Sci       Date:  2001-08       Impact factor: 3.534

3.  Direct, differential-equation-based in-vitro-in-vivo correlation (IVIVC) method.

Authors:  Peter Buchwald
Journal:  J Pharm Pharmacol       Date:  2003-04       Impact factor: 3.765

Review 4.  Review of methodologies for the comparison of dissolution profile data.

Authors:  T O'Hara; A Dunne; A Kinahan; S Cunningham; P Stark; J Devane
Journal:  Adv Exp Med Biol       Date:  1997       Impact factor: 2.622

5.  Convolution-based approaches for in vivo-in vitro correlation modeling.

Authors:  W R Gillespie
Journal:  Adv Exp Med Biol       Date:  1997       Impact factor: 2.622

6.  Draft guidance for industry extended-release solid oral dosage forms. Development, evaluation and application of in vitro-in vivo correlations.

Authors:  H Malinowski; P Marroum; V R Uppoor; W Gillespie; H Y Ahn; P Lockwood; J Henderson; R Baweja; M Hossain; N Fleischer; L Tillman; A Hussain; V Shah; A Dorantes; R Zhu; H Sun; K Kumi; S Machado; V Tammara; T E Ong-Chen; H Mahayni; L Lesko; R Williams
Journal:  Adv Exp Med Biol       Date:  1997       Impact factor: 2.622

Review 7.  Mathematical modeling of drug dissolution.

Authors:  J Siepmann; F Siepmann
Journal:  Int J Pharm       Date:  2013-04-22       Impact factor: 5.875

8.  Methods to compare dissolution profiles and a rationale for wide dissolution specifications for metoprolol tartrate tablets.

Authors:  J E Polli; G S Rekhi; L L Augsburger; V P Shah
Journal:  J Pharm Sci       Date:  1997-06       Impact factor: 3.534

9.  In vitro-in vivo correlation for modified-release formulations.

Authors:  J Drewe; P Guitard
Journal:  J Pharm Sci       Date:  1993-02       Impact factor: 3.534

10.  Linearization of dissolution rate curves by the Weibull distribution.

Authors:  F Langenbucher
Journal:  J Pharm Pharmacol       Date:  1972-12       Impact factor: 3.765

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  2 in total

1.  Dissolution comparisons using a Multivariate Statistical Distance (MSD) test and a comparison of various approaches for calculating the measurements of dissolution profile comparison.

Authors:  J-M Cardot; B Roudier; H Schütz
Journal:  AAPS J       Date:  2017-03-28       Impact factor: 4.009

2.  Slow drug delivery decreased total body clearance and altered bioavailability of immediate- and controlled-release oxycodone formulations.

Authors:  Yan Li; Duxin Sun; Maria Palmisano; Simon Zhou
Journal:  Pharmacol Res Perspect       Date:  2016-01-22
  2 in total

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