Litcius/Paper detail

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

Megan McMahon, Helen Elizabeth Williams, Elke Debie, Mingkun Fu, Robert Bujalski, Fenghe Qiu, Yan Wu, Hanlin Li, Jin Wang, Cherokee Hoaglund-Hyzer, Donnie Pulliam

2020AAPS Open21 citationsDOIOpen Access PDF

Abstract

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.

Topics & Concepts

Stability (learning theory)Risk analysis (engineering)Computer scienceData scienceMachine learningBusinessCrystallization and Solubility StudiesProtein purification and stabilityComputational Drug Discovery Methods