First-principles and direct design approaches for the control of pharmaceutical crystallization

Optimal seed recipe design for crystal size distribution control for batch cooling crystallisation processes

“…One way to enhance the control of CSD is to use supersaturation control (SSC) (Aamir et al, 2009a;Braatz, 2002;Doki et al, 2004;Fujiwara et al, 2005;Liotta and Sabesan, 2004;Yu et al, 2006) or direct nucleation control (Abu Bakar et al, 2009aBakar et al, , 2009bWoo et al, 2009), which drives the process within the metastable zone to avoid nucleation, or to generate controlled nucleation/dissolution events, respectively. Although these approaches can provide improved consistency of the CSD, they do not address the actual design of the CSD.…”

Measurement, modelling, and closed-loop control of crystal shape distribution: Literature review and future perspectives

“…It is also common to avoid nucleation by seeding with crystals of the desired polymorphic form, which will then grow. A large number of papers about crystallisation process control have focused on the control of some properties (e.g., weight, mean, size, aspect ratio) of the CSD [84,85,[149][150][151]. Fujiwara et al [151] reviewed the application of the first-principles and direct design methods to optimize and control pharmaceutical crystallisation processes.…”

“…A large number of papers about crystallisation process control have focused on the control of some properties (e.g., weight, mean, size, aspect ratio) of the CSD [84,85,[149][150][151]. Fujiwara et al [151] reviewed the application of the first-principles and direct design methods to optimize and control pharmaceutical crystallisation processes. Either approach can be implemented with concentration-vs-temperature or temperature-vs-time setpoints, with these implementations having very different sensitivities to disturbances such as deviations in seed characteristics and changes in the contaminant profiles in the feed streams.…”

“…Once the model is sufficiently accurate, a dynamic optimization algorithm can be used to compute the physical design variables, initial conditions, startup procedures, setpoints to lower level feedback control loops, and the feedback control system. Several optimal control algorithms have been developed to provide robustness to parameter and control implementation uncertainties [151,163]. Costa et al [164,165] considered a procedure to minimize standard deviation of the final CSD using the successive quadratic progeamming coupled with the discretisation of the control variables, and also the generic algorithm coupled with parameterization of the control variables.…”

“…A much more efficient approach is direct design, which uses feedback control to follow a setpoint supersaturation curve in the metastable zone without accurate kinetics requirement. The method has been studied in the literature (see for example, [150,151] with a cascade control scheme being used for the concentration control and ATR-FTIR for the concentration measurement. The closed-loop control strategy used to implement direct design is most accurately referred to as concentration (or supersaturation) control.…”