Run-to-run Temperature Control for Polymorphic Transformation in Pharmaceutical Crystallization with Uncertainties

Polymorphism is a phenomenon that a substance can have more than one crystal form, each with distinct characteristics. Consequently, controlling polymorphism in drug manufacturing industries is crucial in order to ensure consistent production of the desired polymorph. In this paper, a run-to-run temperature control with model updating mechanism is developed. This strategy features the ability to learn from previous batches to obtain iteratively the optimal temperature profile and adjust the model parameters. As a result, model uncertainties can be handled with less cost in nominal performance. As a case study, a model of polymorphic transformation of L-glutamic acid from metastable alpha-form to stable beta-form adopted from "process modeling of the polymorphic transformation of 1-glutamic acid" by Ono et al. (2004) is considered, where the yield of beta-form is to be maximized