No abstract

The rejection of process impurities from crystallizing products is an essential step for the purification of pharmaceutical drugs and for the isolation of active pharmaceutical ingredients with the right crystal quality attributes. While several impurity incorporation mechanisms have been reported in the literature, the frequency of those mechanisms in actual industrial processes is largely unknown. This work presents the outcome of a joint investigation by crystallization scientists from two pharmaceutical companies and an academic institution, on the prevalence of impurity retention mechanisms in cooling and antisolvent crystallizations. A total of 52 product-impurity pairs have been explored in detail using the so-called Solubility-Limited Impurity Purge (SLIP) test as the diagnostic tool to identify the underlying impurity retention mechanism of already crystallized materials with challenging impurities. The results show that formation of solid solutions is the most common mechanism, where the impurity and product are partially miscible in the solid state. In 73% of cases, only one solid solution phase was obtained in which the impurity became incorporated into the crystal lattice of the product (α phase). In 6% of the examples, two solid solution phases were obtained, where the second solid phase (β phase) comprised predominantly the impurity and the product was the minor component. The remaining impurity retention mechanisms (21%) are related to solid-state immiscible impurities that precipitated from solution resulting in a physical mixture between the product and the impurity. The reasons for the results are discussed through a comprehensive analysis of theoretical reported retention mechanisms, which includes physical constraints for the scale-up of isolation processes, thermodynamic assessments using ternary phase diagrams, and restrictions in the context of current pharmaceutical syntheses of small organic molecules. Three industrial case studies are presented that exemplify how knowledge of the retention mechanisms can be used to delineate appropriate strategies for process design and to effectively purge these impurities during crystallization or washing.

Enabling the paradigm of quality by design requires the ability to quantitatively correlate material properties and process variables to measureable product performance attributes. Conventional, quality-by-test methods for determining tablet breaking force and disintegration time usually involve destructive tests, which consume significant amount of time and labor and provide limited information. Recent advances in material characterization, statistical analysis, and machine learning have provided multiple tools that have the potential to develop nondestructive, fast, and accurate approaches in drug product development. In this work, a methodology to predict the breaking force and disintegration time of tablet formulations using nondestructive ultrasonics and machine learning tools was developed. The input variables to the model include intrinsic properties of formulation and extrinsic process variables influencing the tablet during manufacturing. The model has been applied to predict breaking force and disintegration time using small quantities of active pharmaceutical ingredient and prototype formulation designs. The novel approach presented is a step forward toward rational design of a robust drug product based on insight into the performance of common materials during formulation and process development. It may also help expedite drug product development timeline and reduce active pharmaceutical ingredient usage while improving efficiency of the overall process.

No abstract