Literature DB >> 35028797

Simplified Model-Dependent and Model-Independent Approaches for Dissolution Profile Comparison for Oral Products: Regulatory Perspective for Generic Product Development.

Sivacharan Kollipara1, Rajkumar Boddu1, Tausif Ahmed2, Siddharth Chachad1.   

Abstract

Dissolution profile comparison among different formulations plays a critical role during new drug as well as generic product development. In the generic product development, dissolution profile comparison is a mandate for biowaivers (BCS-based, for lower strengths and IVIVC-based biowaivers) and also from quality control perspective. Even though traditionally similarity factor or f2 is used as a metric for dissolution profile comparison, it comes with multiple limitations and requirements (e.g., number of time points and variability). To overcome this, regulatory agencies suggested model-independent (e.g., MSD) and model-dependent (e.g., zero order, Weibull) dissolution profile comparison methods. Although most of regulatory guidance documents mention about such approaches, their usage in reality is limited probably due to lack of clear, detailed, and step-wise procedure. In this context, the present article describes simplistic yet detailed procedures of dissolution profile comparison with case studies covering generic product development scenario's from a regulatory perspective. Detailed review of regulatory guidances from various agencies was made along with examples of such approaches in regulatory submissions. Data from three formulations-Formulations A, B, and C-were utilized to perform dissolution profile comparison using MSD, zero-order, and Weibull release profile-based comparisons. Dissolution profile comparisons were made using all of these three approaches complying with regulatory requirements. These examples demonstrated value and utility of these approaches and the simplified and detailed procedure explained in this manuscript can be adapted for generic product applications.
© 2022. The Author(s), under exclusive licence to American Association of Pharmaceutical Scientists.

Entities:  

Keywords:  Mahalanobis statistical distance; Weibull; confidence region; dissolution; similarity region; zero order

Mesh:

Year:  2022        PMID: 35028797     DOI: 10.1208/s12249-021-02203-7

Source DB:  PubMed          Journal:  AAPS PharmSciTech        ISSN: 1530-9932            Impact factor:   3.246


  5 in total

1.  DDSolver: an add-in program for modeling and comparison of drug dissolution profiles.

Authors:  Yong Zhang; Meirong Huo; Jianping Zhou; Aifeng Zou; Weize Li; Chengli Yao; Shaofei Xie
Journal:  AAPS J       Date:  2010-04-06       Impact factor: 4.009

2.  On the use of the Weibull function for the discernment of drug release mechanisms.

Authors:  Vasiliki Papadopoulou; Kosmas Kosmidis; Marilena Vlachou; Panos Macheras
Journal:  Int J Pharm       Date:  2005-12-20       Impact factor: 5.875

3.  In vitro dissolution profile comparison--statistics and analysis of the similarity factor, f2.

Authors:  V P Shah; Y Tsong; P Sathe; J P Liu
Journal:  Pharm Res       Date:  1998-06       Impact factor: 4.200

4.  In-vitro dissolution profile comparison: statistics and analysis, model dependent approach.

Authors:  P M Sathe; Y Tsong; V P Shah
Journal:  Pharm Res       Date:  1996-12       Impact factor: 4.200

5.  Comparison of Dissolution Profiles: A Statistician's Perspective.

Authors:  Thomas Hoffelder
Journal:  Ther Innov Regul Sci       Date:  2017-12-28       Impact factor: 1.778

  5 in total
  1 in total

Review 1.  Physiologically Based Pharmacokinetics Modeling in Biopharmaceutics: Case Studies for Establishing the Bioequivalence Safe Space for Innovator and Generic Drugs.

Authors:  Di Wu; Maitri Sanghavi; Sivacharan Kollipara; Tausif Ahmed; Anuj K Saini; Tycho Heimbach
Journal:  Pharm Res       Date:  2022-07-15       Impact factor: 4.580

  1 in total

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