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In Vitro Dissolution and in Silico Modeling Shortcuts in Bioequivalence Testing

Purpose: To review in vitro testing and simulation platforms that are in current use to predict in vivo performances of generic products as well as other situations to provide evidence for biowaiver and support drug formulations development. Methods: Pubmed and Google Scholar databases were used to...

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Autores principales: Al-Tabakha, Moawia M., Alomar, Muaed J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7022479/
https://www.ncbi.nlm.nih.gov/pubmed/31947944
http://dx.doi.org/10.3390/pharmaceutics12010045
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author Al-Tabakha, Moawia M.
Alomar, Muaed J.
author_facet Al-Tabakha, Moawia M.
Alomar, Muaed J.
author_sort Al-Tabakha, Moawia M.
collection PubMed
description Purpose: To review in vitro testing and simulation platforms that are in current use to predict in vivo performances of generic products as well as other situations to provide evidence for biowaiver and support drug formulations development. Methods: Pubmed and Google Scholar databases were used to review published literature over the past 10 years. The terms used were “simulation AND bioequivalence” and “modeling AND bioequivalence” in the title field of databases, followed by screening, and then reviewing. Results: A total of 22 research papers were reviewed. Computer simulation using software such as GastroPlus™, PK-Sim(®) and SimCyp(®) find applications in drug modeling. Considering the wide use of optimization for in silico predictions to fit observed data, a careful review of publications is required to validate the reliability of these platforms. For immediate release (IR) drug products belonging to the Biopharmaceutics Classification System (BCS) classes I and III, difference factor (ƒ(1)) and similarity factor (ƒ(2)) are calculated from the in vitro dissolution data of drug formulations to support biowaiver; however, this method can be more discriminatory and may not be useful for all dissolution profiles. Conclusions: Computer simulation platforms need to improve their mechanistic physiologically based pharmacokinetic (PBPK) modeling, and if prospectively validated within a small percentage of error from the observed clinical data, they can be valuable tools in bioequivalence (BE) testing and formulation development.
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spelling pubmed-70224792020-03-09 In Vitro Dissolution and in Silico Modeling Shortcuts in Bioequivalence Testing Al-Tabakha, Moawia M. Alomar, Muaed J. Pharmaceutics Review Purpose: To review in vitro testing and simulation platforms that are in current use to predict in vivo performances of generic products as well as other situations to provide evidence for biowaiver and support drug formulations development. Methods: Pubmed and Google Scholar databases were used to review published literature over the past 10 years. The terms used were “simulation AND bioequivalence” and “modeling AND bioequivalence” in the title field of databases, followed by screening, and then reviewing. Results: A total of 22 research papers were reviewed. Computer simulation using software such as GastroPlus™, PK-Sim(®) and SimCyp(®) find applications in drug modeling. Considering the wide use of optimization for in silico predictions to fit observed data, a careful review of publications is required to validate the reliability of these platforms. For immediate release (IR) drug products belonging to the Biopharmaceutics Classification System (BCS) classes I and III, difference factor (ƒ(1)) and similarity factor (ƒ(2)) are calculated from the in vitro dissolution data of drug formulations to support biowaiver; however, this method can be more discriminatory and may not be useful for all dissolution profiles. Conclusions: Computer simulation platforms need to improve their mechanistic physiologically based pharmacokinetic (PBPK) modeling, and if prospectively validated within a small percentage of error from the observed clinical data, they can be valuable tools in bioequivalence (BE) testing and formulation development. MDPI 2020-01-04 /pmc/articles/PMC7022479/ /pubmed/31947944 http://dx.doi.org/10.3390/pharmaceutics12010045 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Review
Al-Tabakha, Moawia M.
Alomar, Muaed J.
In Vitro Dissolution and in Silico Modeling Shortcuts in Bioequivalence Testing
title In Vitro Dissolution and in Silico Modeling Shortcuts in Bioequivalence Testing
title_full In Vitro Dissolution and in Silico Modeling Shortcuts in Bioequivalence Testing
title_fullStr In Vitro Dissolution and in Silico Modeling Shortcuts in Bioequivalence Testing
title_full_unstemmed In Vitro Dissolution and in Silico Modeling Shortcuts in Bioequivalence Testing
title_short In Vitro Dissolution and in Silico Modeling Shortcuts in Bioequivalence Testing
title_sort in vitro dissolution and in silico modeling shortcuts in bioequivalence testing
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7022479/
https://www.ncbi.nlm.nih.gov/pubmed/31947944
http://dx.doi.org/10.3390/pharmaceutics12010045
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