(676c) Digital Design Framework for the Continuous Crystallization of Diphenhydramine | AIChE

(676c) Digital Design Framework for the Continuous Crystallization of Diphenhydramine


Kilari, H., Purdue University
Mackey, J., Purdue University
Li, H., Purdue University
Nagy, Z., Purdue
In the pharmaceutical industry, the quality of the drug produced is a top priority because of the direct impact on human lives. Regulatory guidance for manufacturing processes has been provided by the U.S. Food and Drug Administration (FDA) to make sure that medications consistently meet quality standards. A key step in the purification of active pharmaceutical ingredients (APIs) is crystallization; a process that is stochastic and difficult to control. Through the use of process analytical technology (PAT) tools and modeling approaches, we aim to develop strategies for designing robust crystallization processes.

In this work, we demonstrate the application of combined model-free quality-by-control (mfQbC) and a model-based digital design approach for the design and optimization of crystallization of Diphenhydramine (DPH). DPH is an anti-histamine commonly found in Benadryl. While the continuous synthesis of DPH has been studied by multiple research groups in the past ten years, research literature lacks information on continuous crystallization development with modeling for the compound.1–4 The PAT-based mfQbC framework implementation reduces both the number of experiments and time needed to design crystallization processes, but often results in sub-optimal crystallization design. However, we can augment the mfQbC results to guide model-based digital design, by identifying key mechanisms to be included in the model and providing high quality data for parameter estimation, which would reduce the overall crystallization development time and lead to an optimal design.5

Under the mfQBC approach, initial solvent screening experiments were conducted to guide solvent selection and gain information about the meta-stable zone width (MSZW). Preliminary batch experiments provided valuable insights about the initial parameter estimation and crystallization mechanisms for model selection and discrimination. Continuous crystallization process alternatives were screened and evaluated according to the suspension ability and degree of fouling of each configuration, in addition to product size and variability. The crystallizer configurations evaluated in this study include mixed suspension-mixed product removal (MSMPR) and continuous oscillatory baffled crystallizer (COBC). Initial parameter estimation estimates were validated in the selected configuration, and improved estimates were used for model development. Under mbQbC framework, a population balance-based model is developed for selected configuration and is used to run the simulation studies. With the selection of best crystallization system for the compound and model development in place, robust-optimization studies have been performed to identify optimal trajectories and design parameters in the design space of the system. The optimal conditions were experimentally validated to complete the cycle of designing a robust continuous crystallization system for Diphenhydramine.

Funding for this paper was made possible by the United States Food and Drug Administration.


1. Snead, D. R. & Jamison, T. F. End-to-end continuous flow synthesis and purification of diphenhydramine hydrochloride featuring atom economy, in-line separation, and flow of molten ammonium salts. Chemical Science 4, 2822–2827 (2013).

2. Loren, B. P. et al. Mass spectrometric directed system for the continuous-flow synthesis and purification of diphenhydramine. Chemical Science 8, 4363–4370 (2017).

3. Adamo, A. et al. On-demand continuous-flow production of pharmaceuticals in a compact, reconfigurable system. Science 352, 61–67 (2016).

4. Collins, N. et al. Fully Automated Chemical Synthesis: Toward the Universal Synthesizer. Organic Process Research and Development 24, 2064–2077 (2020).

5. Szilagyi, B., Eren, A., Quon, J. L., Papageorgiou, C. D. & Nagy, Z. K. Application of Model-Free and Model-Based Quality-by-Control (QbC) for the Efficient Design of Pharmaceutical Crystallization Processes. Crystal Growth and Design 20, 3979–3996 (2020).