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

Autor:	Megan McMahon, Helen Williams, Elke Debie, Mingkun Fu, Robert Bujalski, Fenghe Qiu, Yan Wu, Hanlin Li, Jin Wang, Cherokee Hoaglund-Hyzer, Donnie Pulliam
Jazyk:	angličtina
Rok vydání:	2020
Předmět:	Risk-based predictive stability RBPS Clinical shelf-life Predictive Regulatory feedback Therapeutics. Pharmacology RM1-950 Pharmacy and materia medica RS1-441
Zdroj:	AAPS Open, Vol 6, Iss 1, Pp 1-11 (2020)
Druh dokumentu:	article
ISSN:	2364-9534
DOI:	10.1186/s41120-020-00034-7
Popis:	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.
Databáze:	Directory of Open Access Journals
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