(646c) Utilization of Quality-By-Control for Rapid Process Design of Agrochemical Crystallization | AIChE

(646c) Utilization of Quality-By-Control for Rapid Process Design of Agrochemical Crystallization

Authors 

Wu, W. L. - Presenter, Food and Drug Administration
Chappelow, C., Corteva Agriscience, a division of DowDupont
Larsen, P. A., The Dow Chemical Company
Nagy, Z. K., Purdue University
Patton, J. T., The Dow Chemical Company
Crystallization is a key separation process that is used in the agrochemical industry to separate the agrochemical actives from impure solutions. A poorly designed crystallization step can lead to poor yield, low purity, and long filtration time. Traditionally, a series of design of experiments led by the Quality-by-Design (QbD) approach is used to optimize operating profile of the crystallization process (i.e. temperature profile, solvent/antisolvent addition profile, pH profile).1 An exhaustive list of experiments covering all factors is needed to explore the whole design space experimentally. To minimize the number of experiments and personnel exposure to toxic chemicals, Quality-by-Control (QbC) utilizes control strategies implemented for the target critical quality attributes (CQAs) to determine the operating profile of the process.2 For rapid process design, direct design or model free approaches can be used to quickly determine an operating profile of a process leading the system to the desired CQAs. Two direct design approaches, direct nucleation control (DNC) and supersaturation control (SSC), are used in this work to control the crystallization of a model agrochemical compound. Both DNC and SSC utilize process analytical technology (PAT) tools to acquire data and control the process. DNC utilizes closed-loop feedback control approach with particle measurements from focused beam reflectance measurement (FBRM) to generate temperature cycles.3 On the other hand, SSC uses concentration measurement via UV/Vis detector in a closed-loop feedback control approach to control the concentration by manipulating temperature.4

In this work, both direct design approaches were implemented to improve the particle shape, length, and filtration time of needle shaped particles. Preliminary results have indicated significant improvement in the overall crystallization-filtration process performance. Using a DNC-based direct design approach, the filtration time was reduced by a factor of four compared to the standard recipe. The improved procedure not only reduces the unit operation cycle times, but also improves the particle shape for better downstream operations (i.e. drying, transport). The analysis of the product crystals using Ultra Performance Liquid Chromatography (UPLC) indicates that the impurity profile of the agrochemical compound was not compromised with the thermocycles. With SSC-based direct design approach, the concentration of the system was controlled via a set point of the absolute supersaturation. The system was able to perform a cooling profile and generate uniform needle particles. The QbC-based direct design approaches were also evaluated in larger scale (5 L) crystallization systems indicating that the feedback control based rapid design approach can lead to fast and robust scale-up of agrochemical crystallization processes.

References:

(1) Bondi, R. W.; Drennen, J. K. Quality by Design and the Importance of PAT in QbD; Academic Press, 2011; Vol. 10.

(2) Su, Q.; Ganesh, S.; Moreno, M.; Bommireddy, Y.; Gonzalez, M.; Reklaitis, G. V.; Nagy, Z. K. A Perspective on Quality-by-Control (QbC) in Pharmaceutical Continuous Manufacturing. Comput. Chem. Eng. 2019, 125, 216–231.

(3) Bakar, M. R. A.; Nagy, Z. K.; Saleemi, A. N.; Rielly, C. D. The Impact of Direct Nucleation Control on Crystal Size Distribution in Pharmaceutical Crystallization Processes. Cryst. Growth Des. 2009, 9 (3), 1378–1384.

(4) Saleemi, A. N.; Rielly, C. D.; Nagy, Z. K. Comparative Investigation of Supersaturation and Automated Direct Nucleation Control of Crystal Size Distributions Using ATR-UV/Vis Spectroscopy and FBRM. Cryst. Growth Des. 2012, 12 (4), 1792–1807.