POLARIZED LIGHT MICROSCOPY AND MICROFLUIDICS ENABLED IMAGE ANALYTICS FOR CRYSTALLIZATION

Abstract

Crystallization is an integral operation for producing active pharmaceutical ingredients in the pharmaceutical industry. The ability to characterize and control crystal attributes during crystallization, such as crystal size distribution (CSD) and crystal form, is crucial for ensuring in vivo efficacy of the final drug product. Therefore, process analytical instruments are typically used to analyze these crystal attributes. This thesis explores the application of polarized light microscopy (PLM) with microfluidics for rapid, automated detection of dynamic size distributions, extraction of size-dependent growth rates, and crystal form characterization. We further demonstrate a methodology leveraging PLM, microfluidics, and machine learning for rapid, direct quantification of polymorphs and pseudopolymorphs in crystal populations. Finally, we showcase the exciting ability to monitor and quantify crystal structure changes in dynamic populations of crystals during polymorphic transformation. These methodologies potentially enable the exploration of the polymorphic, pseudopolymorphic landscapes and guide process control strategies for achieving desired crystal attributes.