The Application of a Semi-Automated Crystallizer to Study Oiling-Out and Agglomeration

The crystallization under investigation was prone to oiling-out, which led to agglomeration and crystallization stalling. A semi-automated crystallizer—designed and built iteratively as the crystallization needs changed—was used to study the crystallization and identify the failure modes. A fiber optic probe was included in this setup to track turbidity, which was found to drop in signal whenever an oiling-out/agglomeration event was observed with in situ video microscopy. With this knowledge turbidity was monitored to detect oiling-out and was subsequently used as a feedback mechanism to change the temperature profile to reverse oiling-out/resume crystal growth during the crystallization. The automated sampler, coupled with offline HPLC analysis, provided valuable insight about the behavior of impurities during oiling-out and identified one specific impurity that influenced the formation of the second liquid phase and crystallization rate. The data-rich experimentation performed allowed for the expedient optimization of crystallization parameters, such as temperature profile, seed loading and cycle time. The final crystallization was robust, predictable and capable of self-correction, should a potential failure mode be encountered.

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