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Prediction of Phase Behavior of Spray-Dried Amorphous Solid Dispersions: Assessment of Thermodynamic Models Standard Screening Methods and a Novel Atomization Screening Device with Regard to Prediction Accuracy

机译:喷雾干燥无定形固体分散体的相行为预测:热力学模型评估标准筛选方法和一种基于预测准确性的新型雾化筛选装置

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摘要

The evaluation of drug–polymer miscibility in the early phase of drug development is essential to ensure successful amorphous solid dispersion (ASD) manufacturing. This work investigates the comparison of thermodynamic models, conventional experimental screening methods (solvent casting, quench cooling), and a novel atomization screening device based on their ability to predict drug–polymer miscibility, solid state properties (Tg value and width), and adequate polymer selection during the development of spray-dried amorphous solid dispersions (SDASDs). Binary ASDs of four drugs and seven polymers were produced at 20:80, 40:60, 60:40, and 80:20 (w/w). Samples were systematically analyzed using modulated differential scanning calorimetry (mDSC) and X-ray powder diffraction (XRPD). Principal component analysis (PCA) was used to qualitatively assess the predictability of screening methods with regards to SDASD development. Poor correlation was found between theoretical models and experimentally-obtained results. Additionally, the limited ability of usual screening methods to predict the miscibility of SDASDs did not guarantee the appropriate selection of lead excipient for the manufacturing of robust SDASDs. Contrary to standard approaches, our novel screening device allowed the selection of optimal polymer and drug loading and established insight into the final properties and performance of SDASDs at an early stage, therefore enabling the optimization of the scaled-up late-stage development.
机译:在药物开发的早期阶段,评估药物与聚合物的混溶性对于确保成功生产无定形固体分散体(ASD)至关重要。这项工作基于热力学模型,常规实验筛查方法(溶剂浇铸,淬火冷却)和新型雾化筛查设备的预测能力进行了比较,它们具有预测药物与聚合物混溶性,固态性质(Tg值和宽度)以及适当的能力。在喷雾干燥的无定形固体分散体(SDASD)开发过程中选择聚合物。在20:80、40:60、60:40和80:20(w / w)产生四种药物和七种聚合物的二元ASD。使用调制差示扫描量热法(mDSC)和X射线粉末衍射(XRPD)对样品进行系统分析。主成分分析(PCA)用于定性评估关于SDASD发展的筛选方法的可预测性。在理论模型和实验获得的结果之间发现相关性较差。此外,常规筛查方法预测SDASD混溶性的能力有限,并不能保证为制造坚固的SDASD而适当选择铅赋形剂。与标准方法相反,我们的新型筛选设备允许选择最佳的聚合物和载药量,并在早期阶段了解SDASD的最终特性和性能,因此可以优化扩大规模的后期开发。

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