Experimental Investigation of an Integrated Crystallization and Wet-Milling System with Temperature Cycling to Control the Size and Aspect Ratio of Needle-Shaped Pharmaceutical Crystals

Eren, Ayşe; Szilágyi, Botond; Quon, Justin L.; Papageorgiou, Charles D.

doi:10.1021/acs.cgd.1c00308

Cited by 23 publications

(14 citation statements)

References 31 publications

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“…The solubility parameters are obtained by fitting the solubility model eq 10 to solubility data, obtained using the thermogravimetric method, in the 10−75 °C temperature range. 45 Spherical crystal shape was considered, which is a weak assumption given the high aspect-ratio crystal geometry, but the Mastersizer provides the distribution of the sphere-equivalent diameters. Hence, the shape assumption was driven by the sensor characteristics.…”

Section: Resultsmentioning

confidence: 99%

“…The material and system specific constants as well as the optimization settings are listed in Table . The solubility parameters are obtained by fitting the solubility model eq to solubility data, obtained using the thermogravimetric method, in the 10–75 °C temperature range . Spherical crystal shape was considered, which is a weak assumption given the high aspect-ratio crystal geometry, but the Mastersizer provides the distribution of the sphere-equivalent diameters.…”

Section: Resultsmentioning

confidence: 99%

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Digital Design of the Crystallization of an Active Pharmaceutical Ingredient Using a Population Balance Model with a Novel Size Dependent Growth Rate Expression. From Development of a Digital Twin to In Silico Optimization and Experimental Validation

Szilágyi

Eren

Quon

et al. 2021

Crystal Growth & Design

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Prediction and control of the product properties in crystallization processes are practical challenges in the pharmaceutical industry. Effective crystallization process design and operation techniques are needed to meet the critical quality attributes (CQAs) and minimize batch-to-batch variation. Mathematical modeling can enhance process understanding and save a considerable amount of time, effort and raw material when used in process development following the guidelines of the Quality-by-Design (QbD) framework. When the mathematical model of the process is fitted and validated with experimental data, it provides a digital twin of the process that enables execution of in silico design of experiments (DoEs), which is particularly beneficial when the number of factors increases or if the material is expensive or sparingly available, e.g., during early stage development. This work presents the benefits of crystallization process modeling by studying an active pharmaceutical ingredient (API) from Takeda Pharmaceuticals International Co., referred hereafter as Compound A. A framework for crystallization model construction, parameter estimation and validation are demonstrated through the case study of Compound A by using the population balance modeling (PBM) approach. Secondary nucleation, size dependent growth (SDG), and size dependent dissolution mechanisms are considered. Size dependency is introduced with a new formulation capturing the considerably slower growth of small crystals (D 90 < 10 μm) while having size dependency for the larger crystal size domain (D 90 > 200 μm) similar to the models from the literature. To make the model parameter estimation more industrially relevant, a novel method developed recently by the authors is applied to use the focused beam reflectance measurement (FBRM) data directly in the parameter estimation without further transformations. The kinetic parameters are estimated by minimizing the difference between measured and simulated concentrations, crystal size distributions (CSDs) and maximizing the correlation between the simulated crystal number density and measured FBRM counts. The paper also illustrates that the novel SDG rate expression can capture the CSD dynamics considerably better than the standard SDG rate models. The digital twin is used for in silico DoE and process optimization, and the simulation results are validated experimentally, demonstrating the benefits of model-based digital design for crystallization process development.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Digital Design of the Crystallization of an Active Pharmaceutical Ingredient Using a Population Balance Model with a Novel Size Dependent Growth Rate Expression. From Development of a Digital Twin to In Silico Optimization and Experimental Validation

Szilágyi

Eren

Quon

et al. 2021

Crystal Growth & Design

Self Cite

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“…Significant improvements in particle size and shape have been demonstrated using DNC and SSC methods for compounds with fast growth kinetics (e.g., paracetamol and glycine). These improvements with direct design crystallization methodologies are also translatable to commercial active ingredients with polymorphism, slow, and/or one-dimensional crystal growth kinetics. − Controlled thermocycling via ParticleTrack measurement or image analysis for the digestion of fines has been shown to be an effective method to improve the particle size and shape. In the case of high-aspect-ratio particle systems, however, the ParticleTrack may double count large particles or undercount overlapping particles.…”

Section: Introductionmentioning

confidence: 99%

Implementation and Application of Image Analysis-Based Turbidity Direct Nucleation Control for Rapid Agrochemical Crystallization Process Design and Scale-Up

Chappelow

Hanspal

et al. 2022

Ind. Eng. Chem. Res.

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Traditionally, the crystallization unit operation and process variables (e.g., temperature and/or antisolvent addition profile, agitation rate, and seeding parameters) are optimized using the design of experiments (DOE) methodology within the quality-by-design (QbD) framework. To achieve rapid process design, reduce the number of experiments, and minimize personnel exposure to toxic chemicals, quality-by-control (QbC)-based methods (i.e., direct design or model-free methods) such as supersaturation control and direct nucleation control can be applied to quickly determine an operating profile of a process, leading the system to the desired critical quality attributes (CQAs). In this work, various direct design approaches were implemented to investigate the impact on the particle length and filtration time of high-aspect-ratio particles. In addition, an alternative image-based direct design approach, called turbidity direct nucleation control (TDNC), was implemented, which improved the filtration time by 2.5 times compared to that in the standard process. The robustness, usability, and scalability of the TDNC approach were investigated by varying the solvent composition and running open-loop scale-up experiments. The improved procedure was applied to a commercial-scale crystallizer, resulting in similar improvements in the filtration rate. The commercial scale-up also resulted in a surprising reduction in wash efficiency requiring centrifuge optimization to be addressed.

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“…However, for pharmaceutical crystals, smaller particle sizes between 50-500 µm and a mean particle size of around 80 µm is targeted to enable direct compression while still enabling dissolution in the human body [35]. Additionally, more anisotropic structures such as cuboid-shaped or needles-shaped particles are common for APIs [34,36,37]. The smaller particle size and varying shape result in a more challenging separation task defined by the filter cake resistance [33,38].…”

Section: Introductionmentioning

confidence: 99%

Continuous Isolation of Particles with Varying Aspect Ratios up to Thin Needles Achieving Free-Flowing Products

2022

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The continuous vacuum screw filter (CVSF) for small-scale continuous product isolation of suspensions was operated for the first time with cuboid-shaped and needle-shaped particles. These high aspect ratio particles are very common in pharmaceutical manufacturing processes and provide challenges in filtration, washing, and drying processes. Moreover, the flowability decreases and undesired secondary processes of attrition, breakage, and agglomeration may occur intensively. Nevertheless, in this study, it is shown that even cuboid and needle-shaped particles (l-alanine) can be processed within the CVSF preserving the product quality in terms of particle size distribution (PSD) and preventing breakage or attrition effects. A dynamic image analysis-based approach combining axis length distributions (ALDs) with a kernel-density estimator was used for evaluation. This approach was extended with a quantification of the center of mass of the density-weighted ALDs, providing a measure to analyze the preservation of the inlet PSD statistically. Moreover, a targeted residual moisture below 1% could be achieved by adding a drying module (Tdry = 60 °C) to the modular setup of the CVSF.

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Experimental Investigation of an Integrated Crystallization and Wet-Milling System with Temperature Cycling to Control the Size and Aspect Ratio of Needle-Shaped Pharmaceutical Crystals

Cited by 23 publications

References 31 publications

Digital Design of the Crystallization of an Active Pharmaceutical Ingredient Using a Population Balance Model with a Novel Size Dependent Growth Rate Expression. From Development of a Digital Twin to In Silico Optimization and Experimental Validation

Digital Design of the Crystallization of an Active Pharmaceutical Ingredient Using a Population Balance Model with a Novel Size Dependent Growth Rate Expression. From Development of a Digital Twin to In Silico Optimization and Experimental Validation

Implementation and Application of Image Analysis-Based Turbidity Direct Nucleation Control for Rapid Agrochemical Crystallization Process Design and Scale-Up

Continuous Isolation of Particles with Varying Aspect Ratios up to Thin Needles Achieving Free-Flowing Products

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