(701f) Hybrid-Modeling Approaches for Rapid Quantification of Reaction Kinetics

Rapid quantification of reaction kinetics is crucial during drug substance process development as key decisions need to be made very quickly. To this end, one of the bottlenecks kineticists face is rapid determination of key reaction kinetics, given the novel nature of active pharmaceutical ingredients and the wide range of the chemistry routes interrogated. This includes kinetic information such as reaction stoichiometry, relative reaction rates, process condition dependency, etc., and potentially complex kinetics mechanisms associated with multi-step elementary reactions, catalyst deactivation, hard-to-detect intermediates, varying reaction time scales, and multiphase reactions. The issue is exacerbated by the fact that different experimental designs are deployed across different organizations, e.g., One-Factor-At a-Time (OFAT) vs multivariate Design of Experiments (DoE), which typically require different data analysis and modeling techniques. This presentation introduces and showcases simple hybrid-modeling approach that can be used to address such challenges. How the introduced approach can complement some of the more recently proposed approaches will also be discussed, i.e., model based DoE, model discrimination, and dynamic DoE.