Utilization of risk-based predictive stability within regulatory submissions; industry’s experience

Abstract Risk-Based Predictive Stability (RBPS) tools, such as the Accelerated Stability Assessment Program (ASAP) and other models, are used routinely within pharmaceutical development to quickly assess stability characteristics, especially to understand mechanisms of degradation. These modeling to...

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Main Authors:	Megan McMahon, Helen Williams, Elke Debie, Mingkun Fu, Robert Bujalski, Fenghe Qiu, Yan Wu, Hanlin Li, Jin Wang, Cherokee Hoaglund-Hyzer, Donnie Pulliam
Format:	Article
Language:	English
Published:	SpringerOpen 2020-05-01
Series:	AAPS Open
Subjects:	Risk-based predictive stability RBPS Clinical shelf-life Predictive Regulatory feedback
Online Access:	http://link.springer.com/article/10.1186/s41120-020-00034-7

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spelling	doaj-d72552a8dab247988747c117598e117e2020-11-25T02:15:09ZengSpringerOpenAAPS Open2364-95342020-05-016111110.1186/s41120-020-00034-7Utilization of risk-based predictive stability within regulatory submissions; industry’s experienceMegan McMahon0Helen Williams1Elke Debie2Mingkun Fu3Robert Bujalski4Fenghe Qiu5Yan Wu6Hanlin Li7Jin Wang8Cherokee Hoaglund-Hyzer9Donnie Pulliam10Pfizer Inc.AstraZenecaJanssen Pharmaceutica R&D, a Division of Janssen Pharmaceutica NVSunovion PharmaceuticalsSunovion PharmaceuticalsBoehringer IngelheimMerck & Co., Inc.Vertex PharmaceuticalsGenentechEli Lilly & CompanyBiogenAbstract Risk-Based Predictive Stability (RBPS) tools, such as the Accelerated Stability Assessment Program (ASAP) and other models, are used routinely within pharmaceutical development to quickly assess stability characteristics, especially to understand mechanisms of degradation. These modeling tools provide stability insights within weeks that could take months or years to understand using long-term stability conditions only. Despite their usefulness, the knowledge gained through these tools are not as broadly used to support regulatory filing strategies. This paper aims to communicate how industry has used RBPS data to support regulatory submissions and discuss the regulatory feedback that was received.http://link.springer.com/article/10.1186/s41120-020-00034-7Risk-based predictive stabilityRBPSClinical shelf-lifePredictiveRegulatory feedback
collection	DOAJ
language	English
format	Article
sources	DOAJ
author	Megan McMahon Helen Williams Elke Debie Mingkun Fu Robert Bujalski Fenghe Qiu Yan Wu Hanlin Li Jin Wang Cherokee Hoaglund-Hyzer Donnie Pulliam
spellingShingle	Megan McMahon Helen Williams Elke Debie Mingkun Fu Robert Bujalski Fenghe Qiu Yan Wu Hanlin Li Jin Wang Cherokee Hoaglund-Hyzer Donnie Pulliam Utilization of risk-based predictive stability within regulatory submissions; industry’s experience AAPS Open Risk-based predictive stability RBPS Clinical shelf-life Predictive Regulatory feedback
author_facet	Megan McMahon Helen Williams Elke Debie Mingkun Fu Robert Bujalski Fenghe Qiu Yan Wu Hanlin Li Jin Wang Cherokee Hoaglund-Hyzer Donnie Pulliam
author_sort	Megan McMahon
title	Utilization of risk-based predictive stability within regulatory submissions; industry’s experience
title_short	Utilization of risk-based predictive stability within regulatory submissions; industry’s experience
title_full	Utilization of risk-based predictive stability within regulatory submissions; industry’s experience
title_fullStr	Utilization of risk-based predictive stability within regulatory submissions; industry’s experience
title_full_unstemmed	Utilization of risk-based predictive stability within regulatory submissions; industry’s experience
title_sort	utilization of risk-based predictive stability within regulatory submissions; industry’s experience
publisher	SpringerOpen
series	AAPS Open
issn	2364-9534
publishDate	2020-05-01
description	Abstract Risk-Based Predictive Stability (RBPS) tools, such as the Accelerated Stability Assessment Program (ASAP) and other models, are used routinely within pharmaceutical development to quickly assess stability characteristics, especially to understand mechanisms of degradation. These modeling tools provide stability insights within weeks that could take months or years to understand using long-term stability conditions only. Despite their usefulness, the knowledge gained through these tools are not as broadly used to support regulatory filing strategies. This paper aims to communicate how industry has used RBPS data to support regulatory submissions and discuss the regulatory feedback that was received.
topic	Risk-based predictive stability RBPS Clinical shelf-life Predictive Regulatory feedback
url	http://link.springer.com/article/10.1186/s41120-020-00034-7
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Utilization of risk-based predictive stability within regulatory submissions; industry’s experience

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