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A cooling profile for a seeded pharmaceutical crystallization designed to achieve a desired mean crystal size is found by minimizing the batch operating time subject to a crystallization model. In many systems, optimizing a characteristic of the product crystal size density is the usual objective. This objective is not feasible for this system because growth-dependent dispersion occurs in the absence of secondary nucleation. Instead, the batch operating time is minimized, and the resulting characteristics of the crystal size density are then fixed by the operating policy. To prevent undesired secondary nucleation, both a cooling-rate constraint and a supersaturation constraint are investigated. The optimal policies are implemented and verified experimentally. The experimental measurements include solution concentration, slurry transmittance, and video microscopy. The video microscopy is used to determine the mean crystal size and standard deviation. These values are found to agree closely with the model predictions for the optimal operating policies. In addition to determining the optimal operating policies, this study is the first to use video images for monitoring crystal size density mean and standard deviation as part of crystallizer model validation.

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A flow-controlled microfluidic device for parallel and combinatorial screening of crystalline materials can profoundly impact the discovery and development of active pharmaceutical ingredients and other crystalline materials. While the existing...

An unusual pharmaceutical solid containing a pleuromutilin derivative, succinic acid and water is studied with a combination of physiochemical methods. The parent pleuromutilin derivative creates a host structure that contains large channels, which are occupied by variable amounts of both succinic acid and water. The inherent disorder of the system does not lend itself to detailed single-crystal X-ray diffraction studies; hence a combination of powder X-ray diffraction (PXRD) and solid-state NMR (SSNMR) techniques were used to characterize this system and understand its behavior. A variety of one and two-dimensional SSNMR experiments were used to understand the proton transfer and the hydrogen bonding network, including 1 H-13 C heteronuclear correlation experiments and measurements of the principal components of 13 C chemical shift tensors. This crystal system can exist as two distinct phases; a hemisuccinate phase containing a doubly ionized succinate molecule with two cations of the pleuromutilin derivative, and a succinic acid rich phase which contains a singly ionized succinate molecule hydrogen bonded to another fully protonated succinic acid for every mole of the pleuromutilin derivative. Individual particles can contain mixtures of these two phases, leading to a range of apparent stoichiometries between the succinic acid and pleuromutilin derivative. Both phases are variable hydrates and were characterized by gravimetric vapor sorption and variable humidity 13 C SSNMR techniques.

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Melt crystallization of anhydrous milk fat and subsequent filtration of the slurry is a common process for obtaining milk fat fractions with different physical and chemical properties. The crystallization mechanism is very complex and little is known about how the crystallizer conditions and the crystal size distribution (CSD) affect the filtration process. The objective of this study was to characterize the fractionation process and determine which geometric parameters of the crystallizer affect the filtration step. Two scales of fractionation were studied, 0.6 L and 3.6 L, with crystallization at 28°C. The slurry was pressure-filtered after 24 h at 500 kPa in a 1-L chamber. Impeller diameters and speeds were varied for both scales. Photomicroscopy and spectrophotometry were used to characterize the crystallization process, and filtration rates were measured by weighing the amount of filtrate passing through the filter. Filtration resistance values, calculated using the constant pressure filtration equation, as well as photomicroscopy results indicated that the agglomerates and crystals that formed had different morphological characteristics for the different mixing and flow regimes in the crystallizer. Crystallization conditions that provide an optimal filtration time, a solid fraction with minimal liquid entrainment, and a CSD with an intermediate range of sizes (80-500 µm) having good packing properties for filtration were found.Paper no. J9087 in JAOCS 76, 585-594 (1999).

Precompetitive collaborations on new enabling technologies for research and development are becoming popular among pharmaceutical companies. The Enabling Technologies Consortium (ETC), a precompetitive collaboration of leading innovative pharmaceutical companies, identifies and executes projects, often with third-party collaborators, to develop new tools and technologies of mutual interest. Here, we report the results of one of the first ETC projects: the development of a user-friendly population balance model (PBM)-based crystallization simulator software. This project required the development of PBM software with integrated experimental data handling, kinetic parameter regression, interactive process simulation, visualization, and optimization capabilities incorporated in a computationally efficient and robust software platform. Inputs from a team of experienced scientists at 10 ETC member companies helped define a set of software features that guided a team of crystallization modelers to develop software incorporating these features. Communication, continuous testing, and feedback between the ETC and the academic team facilitated the software development. The product of this project, a software tool called CrySiV, an acronym for Crystallization Simulation and Visualization, is reported herein. Currently, CrySiV can be used for cooling, antisolvent, and combined cooling and antisolvent crystallization processes, with primary and secondary nucleation, growth, dissolution, agglomeration, and breakage of crystals. This paper describes the features and the numerical methods of the software and presents two case studies demonstrating its use for parameter estimation. In the first case study, a simulated data set is used to demonstrate the capabilities of the software to find kinetic parameters and its goodness of fit to a known solution. In the second case study, the kinetics of an antisolvent crystallization of indomethacin from a ternary solvent system are estimated, providing a practical example of the tool.