Impurity incorporation in solution crystallization: diagnosis, prevention, and control

Selective product crystallization for separation and recycling of homogeneous catalysts represents one novel promising method to develop sustainable chemical processes. This specific application holds two main challenges: (1) In the crystallization and subsequent filtration and washing process, isolation of a pure crystalline product is required to obtain the maximum quantity of catalyst in the filtrate for recycling, and (2) the entire process must be operated in an inert atmosphere to maintain the catalytic activity of oxygen-sensitive species. Key to the isolation of a pure product is precise control of the crystallization process, which is realized in this work by gassing-induced nucleation using inert argon. Assuming that the nucleation step is crucial for the control of particle properties of the crystalline product and the related efficiency of downstream separation by filtration and washing, we systematically investigated the effect of controlled nucleation by gassing on these quantities using the oleo-chemical model system, 1,12-dimethyl dodecanedioate/methanol. The experimental results verify that by gassing with argon, the nucleation step can be initiated at lower supersaturation compared to uncontrolled cooling crystallization with spontaneous nucleation despite the comparably small metastable zone width of the investigated model system in the range of 1–3 K. It is further demonstrated that consequently less nuclei are formed that grow to larger product crystals, which can be more efficiently separated from the mother liquor in the filtration and washing step, reducing the mother liquor leaching to the isolated product to nearly 100 ppm. Finally, it is verified that gassing crystallization with argon offers a considerable benefit for the isolation of a pure crystalline product while maintaining inert operating conditions required for recycling of oxygen-sensitive catalysts.

Section: Introductionmentioning

confidence: 99%

Inert Gassing Crystallization for Improved Product Separation of Oleo-Chemicals toward an Efficient Circular Economy

Seifert

Simons

Gutsch

et al. 2022

“…The underlying impurity purge mechanisms that are responsible for rejecting the impurities into the liquid phase are still subject of debate, in part because of lack of research in this area compared to crystallization studies on polymorphism or particle properties. While there have been several recent reports in the literature on theoretical impurity retention mechanisms, − there are few examples that provide quantitative information on the frequency of those mechanisms, or even direct evidence on the physical and thermodynamic basis for why certain impurities are rejected and others are not. Moreover, even with the identified retention mechanisms that may be possible, there is no contribution that reports the prevalence of observed retention mechanisms in crystallizations in the presence of industrially relevant synthetic impurities.…”

Section: Introductionmentioning

confidence: 99%

Prevalence of Impurity Retention Mechanisms in Pharmaceutical Crystallizations

Nordström

Sirota

Hartmanshenn

et al. 2023

Self Cite

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.

“…The definition of an impurity control strategy is core to the development of a pharmaceutical manufacturing process. Various studies on impurity control at both the unit operation and whole process level exist in the literature, including specific workflows to identify which impurity incorporation mechanisms are occuring in a given crystallization process and practical actions to minimize the said impurities. ,, Despite efforts to make these workflows as general as possible, the nature of active pharmaceutical ingredient (API) manufacturing (i.e., complex multistep syntheses, workups, and crystallization of organic molecules) renders impurity control strategies defined mostly on a case-by-case basis . These are still predominantly carried out solely via design of experiment (DoE) approaches, which are useful in gaining initial insights into processes with several input factors varying simultaneously but can be resource-intensive with respect to API and intermediates that may be scarce and expensive during process development.…”

Section: Introductionmentioning

confidence: 99%

“…7,12,13 Despite efforts to make these workflows as general as possible, the nature of active pharmaceutical ingredient (API) manufacturing (i.e., complex multistep syntheses, workups, and crystallization of organic molecules) renders impurity control strategies defined mostly on a case-by-case basis. 14 These are still predominantly carried out solely via design of experiment (DoE) approaches, which are useful in gaining initial insights into processes with several input factors varying simultaneously but can be resource-intensive with respect to API and intermediates that may be scarce and expensive during process development. Moreover, DoE does not fully capture the inherent nonlinearities of the physical mechanisms underpinning pharmaceutical manufacturing processes.…”

Section: Introduction 1drug Substance Quality In Pharmaceuticalmentioning

confidence: 99%

Mathematical Modeling and Optimization to Inform Impurity Control in an Industrial Active Pharmaceutical Ingredient Manufacturing Process

Diab

Christodoulou

Taylor

et al. 2022

Mathematical modeling of pharmaceutical manufacturing processes can provide insights and understanding regarding the key factors impacting product quality. In this study, we describe the development of a dynamic model for a stage in an active pharmaceutical ingredient (API) manufacturing process, its calibration and validation versus industrial experimental data, and its use to address three objectives: (1) assessment of process operating parameter criticality on key performance indicators (KPIs); (2) confirming whether the considered process operating space safely respected limits of critical quality attribute (CQA) impurities; and(3) finding process setpoints that can potentially improve the KPIs. Objective 1 used global sensitivity analysis (GSA) to find that only operating parameters associated with the reactor were significant. Objectives 2 and 3 used nonlinear optimization, confirming that impurity limits are respected at any point in the considered process operating space and suggesting a shifted process setpoint that could allow enhanced yield (∼4% absolute increase) and reduced impurity content (∼0.5 mol % absolute reduction).