An in silico Tool for Quantitative Kinetic Predictions of API Degradation
- Type: Conference Presentation
- Conference Type: AIChE Annual Meeting
- Presentation Date: November 10, 2021
- Duration: 24 minutes
- Skill Level: Intermediate
- PDHs: 0.50
Alternatively, supplementing the contemporary experimental approach with novel computational chemistry methods has the potential to significantly accelerate API stability studies and reduce R&D costs. In this talk, we present the development of a self-improving software that can readily predict API degradants, automatically build API degradation kinetic models, and reliably identify critical API decomposition pathways. Pfizer and MIT researchers collaboratively investigated the aqueous oxidative degradation chemistry of imipramine. The imipramine degradation model constructed by the MIT team using the newly developed software successfully predicted degradants observed experimentally by the Pfizer team. The model and experimental results also provide novel insights into imipramine degradation pathways and kinetics.
Based on the promising results, we believe the quantitative in silico tools that we are actively developing will greatly assist the pharmaceutical research community in performing drug stability studies. The computer-assisted drug stability analyses will guide future drug degradation experiments, assist in API formulation improvements to resist oxidation, and potentially reduce drug development costs.
|AIChE Member Credits||0.5|
|AIChE Graduate Student Members||Free|
|AIChE Undergraduate Student Members||Free|