Recent advances of pharmaceutical crystallization theories

Weng, Jingyun; Huang, Yiping; Hao, Dule; Ji, Yuanhui

doi:10.1016/j.cjche.2019.11.008

Cited by 26 publications

(19 citation statements)

References 109 publications

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“…It is necessary to combine the research of equilibrium thermodynamics and process kinetics to reveal the essential laws of the crystallization process and then realize the optimization of the crystallization process. Recently, the chemical-potential-gradient model combined with the perturbed-chain statistical associating fluid theory (PC-SAFT) was established to investigate the dissolution kinetics of drugs, including the mechanism information under different conditions and prediction of dissolution kinetics. − Furthermore, this model can also be extended for studying the crystallization process. , …”

Section: Introductionmentioning

confidence: 99%

“…38−49 Furthermore, this model can also be extended for studying the crystallization process. 50,51 In this work, the crystal growth kinetics of CSD were measured under different conditions. Furthermore, three chemical-potential-gradient models, in which the extended Debye−Huckel model was employed to calculate the activity coefficient of each component, were applied to analyze the crystal growth mechanism of CSD, describe, and predict the crystal growth kinetics.…”

Section: Introductionmentioning

confidence: 99%

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Crystallization Kinetics and Mechanisms of Calcium Sulfate Dihydrate: Experimental Investigation and Theoretical Analysis

Tang

2020

Ind. Eng. Chem. Res.

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In this work, four influencing factors including temperature, stirring speed, pH value, and polymer concentration were chosen to investigate crystallization kinetics of calcium sulfate dihydrate (CSD). At the same time, the chemical-potentialgradient models combined with the extended Debye−Huckel model were used to explore the growth mechanism of CSD and predict the crystal growth kinetics under different external conditions. The results indicated that temperature was the key influencing factor because of the sensitivity of the rate constant k t and driving force Δμ to temperature changes. Moreover, the pH nearly has little effect on them, while the stirring speed and polymer concentration primarily affected k t and Δμ, respectively. On the other hand, the theoretical models indicated that the crystallization mechanism of CSD belonged to the adhesive-type growth mechanism. Moreover, the CSD crystal growth kinetics was well predicted at different temperatures, pH values, and polymer concentrations. Unfortunately, the crystallization kinetics of CSD under different stirring speeds cannot be accurately predicted. The detailed information, such as the key influencing factor and the crystallization mechanism, could provide a reference for the removal of scale in industrial production.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Crystallization Kinetics and Mechanisms of Calcium Sulfate Dihydrate: Experimental Investigation and Theoretical Analysis

Tang

2020

Ind. Eng. Chem. Res.

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“…Many crystalline drugs have slow dissolution in aqueous solutions due to their low water solubility, which often leads to poor bioavailability. By integrating the amorphous drug into a polymeric excipient, denoted as amorphous solid dispersion (ASD), the dissolution rate of the drug in aqueous solutions can be ameliorated, which has been considered as a promising formulation approach to enhance dissolution 1,2 …”

Section: Introductionmentioning

confidence: 99%

Insights into influence mechanism of polymeric excipients on dissolution of drug formulations: A molecular interaction‐based theoretical model analysis and prediction

Hao

Luebbert

et al. 2021

AIChE Journal

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This study provides an analysis of the dissolution mechanism of poorly water‐soluble drugs, indomethacin (IND) and naproxen (NAP), from polyvinyl acetate (PVAc) and polyvinylpyrrolidone/vinyl acetate 64 (PVPVA 64) formulations under the combination of the Perturbed‐Chain Statistical Associating Fluid Theory (PC‐SAFT) and a chemical‐potential‐gradient model. Moreover, the dissolution kinetics of both drugs from these polymeric formulations were modeled in conformity with the in vitro experimental data obtained by means of a rotating disk system (USP II). The combination of the thermodynamic model PC‐SAFT and a chemical‐potential‐gradient model was demonstrated to be an efficient approach to explain the drug dissolution mechanism from the drug/PVAc and PVPVA 64 formulations. These results have implications in reducing experimental time and resources for the sustained dissolution kinetics profile determination without compromising accuracy, in particular for the system of the drug/PVAc formulation when obtaining continuous drug dissolution in this work.

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“…The nucleation and growth kinetics of crystallization strongly affects the crystal quality, especially the crystal size distribution (CSD) [1][2][3] and, hence, needs to be described in crystallization processes. However, nucleation occurs stochastically rather than deterministically [4][5][6], which may make it difficult to control the crystallization processes.…”

Section: Introductionmentioning

confidence: 99%

Parameter Estimation of the Stochastic Primary Nucleation Kinetics by Stochastic Integrals Using Focused-Beam Reflectance Measurements

Unno

Hirasawa

2020

Crystals

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The kinetic parameters of stochastic primary nucleation were estimated for the batch-cooling crystallization of L-arginine. It is difficult for process analytical tools to detect the first nucleus. In this study, the latent period for the total number of crystals to be increased to a predetermined threshold was repeatedly measured with focused-beam reflectance measurements. Consequently, the latent periods were different in each measurement due to the stochastic behavior of both primary and secondary nucleation. Therefore, at first, the distribution of the latent periods was estimated by a Monte Carlo simulation for some combinations of the kinetic parameters of primary nucleation. In the simulation, stochastic integrals of the population and mass balance equations were solved. Then, the parameters of the distribution of latent periods were estimated and correlated with the kinetic parameters of primary nucleation. The resulting correlation was represented by a mapping. Finally, the parameters of the actual distribution were input into the inverse mapping, and the kinetic parameters were estimated as the outputs. The estimated kinetic parameters were validated using statistical techniques, which implied that the observed distribution function of the latent periods for the thresholds used in the estimation coincided reasonably with the simulated one based on the estimated parameters.

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Recent advances of pharmaceutical crystallization theories

Cited by 26 publications

References 109 publications

Crystallization Kinetics and Mechanisms of Calcium Sulfate Dihydrate: Experimental Investigation and Theoretical Analysis

Crystallization Kinetics and Mechanisms of Calcium Sulfate Dihydrate: Experimental Investigation and Theoretical Analysis

Insights into influence mechanism of polymeric excipients on dissolution of drug formulations: A molecular interaction‐based theoretical model analysis and prediction

Parameter Estimation of the Stochastic Primary Nucleation Kinetics by Stochastic Integrals Using Focused-Beam Reflectance Measurements

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