(576b) Experimental Investigation of Wet-Mill Integrated Crystallization with Temperature Cycles for Size and Aspect Ratio Control of a Commercial Pharmaceutical Ingredient
AIChE Annual Meeting
2020
2020 Virtual AIChE Annual Meeting
Process Development Division
Crystallization Process Development
Thursday, November 19, 2020 - 8:15am to 8:30am
The work shows the implementation of a Quality-by-Control (QbC) guided wet-mill integrated crystallization design to produce large crystals with low AR. In this work, nine batch cooling crystallization experiments were performed. The first experiment was a seeded crystallization with very slow linear cooling rate. The remaining eight experiments were divided into two sets: (i) temperature cycling using simultaneous internal wet-mill; and (ii) crystallizations using temperature cycling but without milling. All experiments were performed with similar batch times but increasing the temperature cycle number from zero to four. Then, by using the same temperature profiles and operating procedure, simultaneous milling was applied for 75 % of the duration of the first temperature cycle as suggested in the literature, by using an immersion mill.3
A batch seeded cooling crystallization with very slow cooling (-0.02 °C/min) was performed, which showed that even this very slow cooling was insufficient to obtain the desired large crystals (> 150 µm) because of strong secondary nucleation in the process. Instead, applying internal fines removal by temperature cycles led to considerable increase of the product crystal size. Increasing the number of temperature cycles had a significant effect on producing large crystals (with mean size of 150-250 µm) by eliminating the fines produced by nucleation. These conclusions were also evidenced by using FBRM and in-line particle images. The results suggested that at least 2 temperature cycles were required to reach the desired product size for compound A. In the second part of the study, experiments with the same temperature profiles with wet-milling applied during the first cycle were performed. In these experiments, large crystals with low AR (>150 µm with mean AR around 2.5) could be successfully produced. The reason for using the wet-mill only at the beginning of the process is that it helps create large amount of small, low AR particles, which are partly removed by the first heat-up stage. In addition, it was shown with the 4 cycle-experiment that the milling rate does not have a significant effect on the CSD within the range applied (4000 and 8000 RPM) due to the achievable smallest size limit that characterizes the milling equipment. Therefore, the milling intensity was set to 4,000 RPM for all experiments. The experiments demonstrated that wet-mill contributed significantly to reaching the desired product crystal size and shape. This was quantified by 2D size distribution measurements based on optical microscopy images. Additionally, unseeded experiments were also performed, in which in situ seed generation was achieved by (1) cooling or (2) application of the immersion-mill as a high share nucleator. Both of these experiments demonstrated that applying wet-milling during the first temperature cycle not only significantly improves the CSD and AR of the product, but also considerably decreases the uncertainty caused by variation in the seed quality, and in combination with internal seeding via cooling or using the immersion mill as a nucleator can increase the overall efficiency and robustness of the process.
References:
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[2] D. Acevedo, V. K. Kamaraju, B. Glennon, and Z. K. Nagy, âModeling and Characterization of an in Situ Wet Mill Operation,â Org. Process Res. Dev., vol. 21, no. 7, pp. 1069â1079, 2017.
[3] Salvatori, F., Binel, P., & Mazzotti, M. (2019). Efficient assessment of combined crystallization, milling, and dissolution cycles for crystal size and shape manipulation. Chemical Engineering Science: X, 1, 100004.
[4] B. Szilagyi and Z. K. Nagy, âModel-based analysis and quality-by-design framework for high aspect ratio crystals in crystallizer-wet mill systems using GPU acceleration enabled optimization,â Comput. Chem. Eng., vol. 126, pp. 421â433, 2019.