Accelerating pharmaceutical development through predictive stability approaches
There has been significant growth in the use of modeling tools to accelerate development and enhance pharmaceutical quality. Among these are empirical and semi-empirical modeling of accelerated stability studies which can be used to predict product shelf-life (Waterman, Pharm Res 24:780–790, 2007; (Wu et al., AAPS Pharm Sci Tech,16:986–991, 2016); (Lavrich, Rapid Development of Robust Stability Models Using Semi-Empirical Design Space, AAPS Webinar, 2016)). These approaches coupled with Lean Stability and Quality by Design (QbD) Analytical Method Development have been discussed at a recent AAPS Workshop (AAPS Workshop, Accelerating Pharmaceutical Development through Predictive Stability Approaches, 2016) with subsequent discussions at a Face-to-Face Focus Group meeting (AAPS, Joint Face-to-Face meeting summary, 6-April, part1, 2017; AAPS, Joint Face-to-Face meeting summary, 6-April, Part II, 2017; Huynh-Ba, et al., Meeting Report, Analytical Approaches to Ensure Product Quality – AAPS Joint Face-to-Face Meeting of the Stability, the Pharmaceutical Impurities, and the CMC Statistics Focus Group, 2017) and the AAPS Annual meeting (AAPS Annual Meeting Sunrise Session, Accelerating Pharmaceutical Development through Predictive Stability Approaches, AAPS Annual Meeting, 2016). A summary/overview and the outcome from the workshop are captured in this publication. The first part focuses on use of Lean Stability Strategies to expedite the development of new chemical entities in early phase development, and to facilitate process, formulation for various dosage forms (solid, liquid, etc.) and product changes throughout development and post-approval. Also, presented, are the global regulatory agencies feedback, challenges and future direction. For Lean Stability and predictive stability approaches to be successful, the methods used must be accurate, precise and consistent across stability time points, analysts, instruments and testing sites, so the data and predictions are meaningful. For both small and large molecules, the use of QbD for analytical method development aids in achieving this goal; and, the second part of this publication discusses such approaches. These approaches are essential to build an overall optimized stability strategy to meet today’s challenges to advance new medicines and enhance quality.