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First-Principles and Empirical Approaches to Predicting In Vitro Dissolution for Pharmaceutical Formulation and Process Development and for Product Release Testing
This manuscript represents the perspective of the Dissolution Working Group of the International Consortium for Innovation and Quality in Pharmaceutical Development (IQ) and of two focus groups of the American Association of Pharmaceutical Scientists (AAPS): Process Analytical Technology (PAT) and I...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6394641/ https://www.ncbi.nlm.nih.gov/pubmed/30790200 http://dx.doi.org/10.1208/s12248-019-0297-y |
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author | Zaborenko, Nikolay Shi, Zhenqi Corredor, Claudia C. Smith-Goettler, Brandye M. Zhang, Limin Hermans, Andre Neu, Colleen M. Alam, Md Anik Cohen, Michael J. Lu, Xujin Xiong, Leah Zacour, Brian M. |
author_facet | Zaborenko, Nikolay Shi, Zhenqi Corredor, Claudia C. Smith-Goettler, Brandye M. Zhang, Limin Hermans, Andre Neu, Colleen M. Alam, Md Anik Cohen, Michael J. Lu, Xujin Xiong, Leah Zacour, Brian M. |
author_sort | Zaborenko, Nikolay |
collection | PubMed |
description | This manuscript represents the perspective of the Dissolution Working Group of the International Consortium for Innovation and Quality in Pharmaceutical Development (IQ) and of two focus groups of the American Association of Pharmaceutical Scientists (AAPS): Process Analytical Technology (PAT) and In Vitro Release and Dissolution Testing (IVRDT). The intent of this manuscript is to show recent progress in the field of in vitro predictive dissolution modeling and to provide recommended general approaches to developing in vitro predictive dissolution models for both early- and late-stage formulation/process development and batch release. Different modeling approaches should be used at different stages of drug development based on product and process understanding available at those stages. Two industry case studies of current approaches used for modeling tablet dissolution are presented. These include examples of predictive model use for product development within the space explored during formulation and process optimization, as well as of dissolution models as surrogate tests in a regulatory filing. A review of an industry example of developing a dissolution model for real-time release testing (RTRt) and of academic case studies of enabling dissolution RTRt by near-infrared spectroscopy (NIRS) is also provided. These demonstrate multiple approaches for developing data-rich empirical models in the context of science- and risk-based process development to predict in vitro dissolution. Recommendations of modeling best practices are made, focused primarily on immediate-release (IR) oral delivery products for new drug applications. A general roadmap is presented for implementation of dissolution modeling for enhanced product understanding, robust control strategy, batch release testing, and flexibility toward post-approval changes. |
format | Online Article Text |
id | pubmed-6394641 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-63946412019-03-15 First-Principles and Empirical Approaches to Predicting In Vitro Dissolution for Pharmaceutical Formulation and Process Development and for Product Release Testing Zaborenko, Nikolay Shi, Zhenqi Corredor, Claudia C. Smith-Goettler, Brandye M. Zhang, Limin Hermans, Andre Neu, Colleen M. Alam, Md Anik Cohen, Michael J. Lu, Xujin Xiong, Leah Zacour, Brian M. AAPS J White Paper This manuscript represents the perspective of the Dissolution Working Group of the International Consortium for Innovation and Quality in Pharmaceutical Development (IQ) and of two focus groups of the American Association of Pharmaceutical Scientists (AAPS): Process Analytical Technology (PAT) and In Vitro Release and Dissolution Testing (IVRDT). The intent of this manuscript is to show recent progress in the field of in vitro predictive dissolution modeling and to provide recommended general approaches to developing in vitro predictive dissolution models for both early- and late-stage formulation/process development and batch release. Different modeling approaches should be used at different stages of drug development based on product and process understanding available at those stages. Two industry case studies of current approaches used for modeling tablet dissolution are presented. These include examples of predictive model use for product development within the space explored during formulation and process optimization, as well as of dissolution models as surrogate tests in a regulatory filing. A review of an industry example of developing a dissolution model for real-time release testing (RTRt) and of academic case studies of enabling dissolution RTRt by near-infrared spectroscopy (NIRS) is also provided. These demonstrate multiple approaches for developing data-rich empirical models in the context of science- and risk-based process development to predict in vitro dissolution. Recommendations of modeling best practices are made, focused primarily on immediate-release (IR) oral delivery products for new drug applications. A general roadmap is presented for implementation of dissolution modeling for enhanced product understanding, robust control strategy, batch release testing, and flexibility toward post-approval changes. Springer International Publishing 2019-02-21 /pmc/articles/PMC6394641/ /pubmed/30790200 http://dx.doi.org/10.1208/s12248-019-0297-y Text en © The Author(s) 2019 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. |
spellingShingle | White Paper Zaborenko, Nikolay Shi, Zhenqi Corredor, Claudia C. Smith-Goettler, Brandye M. Zhang, Limin Hermans, Andre Neu, Colleen M. Alam, Md Anik Cohen, Michael J. Lu, Xujin Xiong, Leah Zacour, Brian M. First-Principles and Empirical Approaches to Predicting In Vitro Dissolution for Pharmaceutical Formulation and Process Development and for Product Release Testing |
title | First-Principles and Empirical Approaches to Predicting In Vitro Dissolution for Pharmaceutical Formulation and Process Development and for Product Release Testing |
title_full | First-Principles and Empirical Approaches to Predicting In Vitro Dissolution for Pharmaceutical Formulation and Process Development and for Product Release Testing |
title_fullStr | First-Principles and Empirical Approaches to Predicting In Vitro Dissolution for Pharmaceutical Formulation and Process Development and for Product Release Testing |
title_full_unstemmed | First-Principles and Empirical Approaches to Predicting In Vitro Dissolution for Pharmaceutical Formulation and Process Development and for Product Release Testing |
title_short | First-Principles and Empirical Approaches to Predicting In Vitro Dissolution for Pharmaceutical Formulation and Process Development and for Product Release Testing |
title_sort | first-principles and empirical approaches to predicting in vitro dissolution for pharmaceutical formulation and process development and for product release testing |
topic | White Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6394641/ https://www.ncbi.nlm.nih.gov/pubmed/30790200 http://dx.doi.org/10.1208/s12248-019-0297-y |
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