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首页> 外文期刊>International Journal of Pharmaceutics >A multivariate raw material property database to facilitate drug product development and enable in-silico design of pharmaceutical dry powder processes
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A multivariate raw material property database to facilitate drug product development and enable in-silico design of pharmaceutical dry powder processes

机译:多变量原料性能数据库,以促进药品开发,并实现药物干粉工艺的硅设计

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摘要

In current study a holistic material characterization approach was proposed and an extensive raw material property database was developed including a wide variety of APIs and excipients with different functionalities. In total 55 different materials were characterized and described by over 100 raw material descriptors related to particle size and shape distribution, specific surface area, bulk, tapped and true density, compressibility, electrostatic charge, moisture content, hygroscopicity, permeability, flowability and wall friction. Principal component analysis (PCA) was applied to reveal similarities and dissimilarities between materials and to identify overarching properties. The developed PCA model allows to rationalize the number of critical characterization techniques in routine characterization and to identify surrogates for use during early drug product development stages when limited amounts of active pharmaceutical ingredients are available. Additionally, the developed database will be the basis to build predictive models forin silicoprocess and formulation development based on (a selection of) property descriptors.
机译:在目前研究中,提出了整体材料表征方法,并开发了广泛的原材料性能数据库,包括各种各样的API和具有不同功能的赋形剂。总共55种不同的材料被特征和描述了100多种原料描述符,与粒度和形状分布,比表面积,块状,螺纹,液体,耐压,耐压,水分含量,吸湿性,渗透率,流动性和壁摩擦有关的100多种原料描述符。 。应用主成分分析(PCA)以揭示材料之间的相似性和异化,并鉴定总体性质。开发的PCA模型允许在有限的活性药物成分可用时识别常规表征中的关键表征技术的数量,并识别早期药物产品开发阶段的使用。此外,开发的数据库将是基于(选择)属性描述符构建硅Process和配方开发的预测模型的基础。

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