Run-to-run temperature control for polymorphic transformation in pharmaceutical crystallization with uncertainties

Abstract

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 are 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 a-form to stable β-form adopted from [1] is considered, where the yield of β-form is to be maximized. © 2006 IEEE.