Application of feedback control and in situ milling to improve particle size and shape in the crystallization of a slow growing needle-like active pharmaceutical ingredient

Yang, Yang; Pal, Kanjakha; Koswara, Andy; Sun, Qingqing; Zhang, Yuqi; Quon, Justin L.; McKeown, Rahn; Goss, Charles A.; Nagy, Zoltán K.

doi:10.1016/j.ijpharm.2017.09.050

Cited by 31 publications

(30 citation statements)

References 38 publications

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“…Yang et al , and He et al also found this phenomenon. This could be explained by absorption and scattering of submicron nuclei formed during the primary nucleation process.…”

Section: Resultsmentioning

confidence: 99%

Measurement of Disodium 5'‐Inosinate and Disodium 5'‐Guanylate in Aqueous Ethanol by Attenuated Total Reflection Ultraviolet Method

Song

Sun

et al. 2019

Chem Eng & Technol

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An online concentration monitoring method was established by using attenuated total reflection ultraviolet (ATR‐UV) coupled with a suitable partial least squares regression for a multi‐solute crystallization system, namely, disodium 5'‐inosinate (IMP) and disodium 5'‐guanylate (GMP) in aqueous ethanol. The results indicated that the established method accurately predicted the concentration of IMP and GMP in the solution. The solubility data was measured at various temperatures and ethanol/water mass ratios, and the experimental data was well correlated by applying the modified Apelblat equation and modified Jouyban‐Acree model. The implementation of cooling crystallization demonstrates that the developed calibration model is suitable for online concentration monitoring with reasonable accuracy and precision.

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“…Yang et al , and He et al also found this phenomenon. This could be explained by absorption and scattering of submicron nuclei formed during the primary nucleation process.…”

Section: Resultsmentioning

confidence: 99%

Measurement of Disodium 5'‐Inosinate and Disodium 5'‐Guanylate in Aqueous Ethanol by Attenuated Total Reflection Ultraviolet Method

Song

Sun

et al. 2019

Chem Eng & Technol

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“…These research advances have promoted the application of feedback control strategies in the field of crystal shape regulation. Yang et al [112] used online wet grinding in combination with SSC and DNC to change the aspect ratio of needle-like crystals. The IA-DNC strategy developed based on PVM also has some applications in controlling crystal shape [37].…”

Section: Crystal Morphology Controlmentioning

confidence: 99%

Application of PAT-Based Feedback Control Approaches in Pharmaceutical Crystallization

Gao

Zhang

et al. 2021

Crystals

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Crystallization is one of the important unit operations for the separation and purification of solid products in the chemical, pharmaceutical, and pesticide industries, especially for realizing high-end, high-value solid products. The precise control of the solution crystallization process determines the polymorph, crystal shape, size, and size distribution of the crystal product, which is of great significance to improve product quality and production efficiency. In order to develop the crystallization process in a scientific method that is based on process parameters and data, process analysis technology (PAT) has become an important enabling platform. In this paper, we review the development of PAT in the field of crystallization in recent years. Based on the current research status of drug crystallization process control, the monitoring methods and control strategies of feedback control in the crystallization process were systematically summarized. The focus is on the application of model-free feedback control strategies based on the solution and solid information collected by various online monitoring equipment in product engineering, including improving particle size distribution, achieving polymorphic control, and improving purity. In this paper, the challenges of feedback control strategy in the crystallization process are also discussed, and the development trend of the feedback control strategy has been prospected.

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“…For calibrating the Wen-Yu model of fluidization, the particle density and the particle size are normalized according to Eqs. (8) and (9). The purpose was to train a machine learning model on the model multiplier with the normalized particle density and particle size as explanatory variables.…”

Section: Machine Learning For Model Calibrationmentioning

confidence: 99%

“…Bayesian regularization with backpropagation [29] is used to train a neural network model on the log of Wen-Yu multiplier as a function of the regularized particle density and size viz. 8and (9). The function trainbr of Matlab R2016a was used for this purpose.…”

Section: Machine Learning For Model Calibrationmentioning

confidence: 99%

See 1 more Smart Citation

Multiphase Particle in Cell Simulations of Fluidized Beds: Studies on Bubble Rise Velocity and Minimum Fluidization Velocity

Pal

Theuerkauf

2021

Chemie Ingenieur Technik

Self Cite

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Ing. Matthias Kraume on the occasion of his 65th birthday Multiphase particle in a cell simulation of fluidized beds for different Geldart group particles (A, B and D) were investigated. The minimum fluidization velocities predicted by the Barracuda Virtual Reactor were compared and contrasted by theoretical predictions with the Wen-Yu model. The optimal drag force coefficients based on the Wen-Yu model for MP-PIC simulations was further evaluated for different particle sizes and densities for Group A catalysts. A neural network model was constructed for the optimal model constants as a function of the explanatory variables for group A catalysts. This work illustrates the importance of choosing the correct value for the drag force coefficients to obtain realistic simulation results for fluidized beds. This work clearly demonstrates that the Barracuda simulation results are very sensitive to the value of the Wen-Yu parameter. Using multiphase particle in cell simulations in conjunction with a neural network model can be directly used in further studies as a rapid tool to get the correct values for realistic drag force coefficients based on the Wen-Yu model.

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Application of feedback control and in situ milling to improve particle size and shape in the crystallization of a slow growing needle-like active pharmaceutical ingredient

Cited by 31 publications

References 38 publications

Measurement of Disodium 5'‐Inosinate and Disodium 5'‐Guanylate in Aqueous Ethanol by Attenuated Total Reflection Ultraviolet Method

Measurement of Disodium 5'‐Inosinate and Disodium 5'‐Guanylate in Aqueous Ethanol by Attenuated Total Reflection Ultraviolet Method

Application of PAT-Based Feedback Control Approaches in Pharmaceutical Crystallization

Multiphase Particle in Cell Simulations of Fluidized Beds: Studies on Bubble Rise Velocity and Minimum Fluidization Velocity

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