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使用非侵入性X射线显微镜和基于人工智能的图像分析对半固体药品进行表征

Semisolid Pharmaceutical Product Characterization Using Non-invasive X-ray Microscopy and AI-Based Image Analytics.

作者信息

Yeoh Thean, Ma Lisa, Badruddoza Abu Zayed, Shah Jaymin, Zhang Shawn

机构信息

Pfizer, Drug Product Design, Worldwide Research, Development and Medical, Pfizer Inc., Groton, Connecticut, 06340, USA.

DigiM Solution LLC, 67 South Bedford Street, Suite 400 West, Burlington, Massachusetts, 01803, USA.

出版信息

AAPS J. 2022 Mar 21;24(3):46. doi: 10.1208/s12248-022-00696-z.

Abstract

This work reports the use of X-ray microscopy (XRM) imaging to characterize the microstructure of semisolid formulations containing multiple immiscible phases. For emulsion-based semisolid formulations, the disperse phase globule size and its distribution can be critical quality attributes of the product. Optical microscopy and light diffraction techniques are traditionally used to characterize globule size distribution. These techniques are subjected to sample preparation bias and present challenges from matrix interference and data processing. XRM imaging is an emergent technique that when combined with intelligent data processing has been used to characterize microstructures of pharmaceutical dosage forms including oral solid formulations, controlled release microspheres, and lyophilized products. This work described our first attempt to use XRM imaging to characterize two complex emulsion-based semisolid formulations, a petrolatum-based ointment with a dispersed phase comprising a hydrophilic liquid, and an oil-in-water cream. This initial assessment of technology showed that microstructure details such as globule size distribution, volume fraction, spatial distribution uniformity, inter-globule spacing, and globule sphericity could be obtained and parameterized. It was concluded that XRM imaging, combined with artificial intelligence-based image processing is feasible to generate advanced characterization of semisolid formulation microstructure through 3D visualization and parameterization of globule attributes. This technique holds promise to provide significantly richer microstructure details of semisolid formulations. When fully developed and validated, it is potentially useful for quantitative comparison of microstructure equivalence of semisolid formulations.

摘要

这项工作报道了使用X射线显微镜(XRM)成像来表征含有多个不混溶相的半固体制剂的微观结构。对于基于乳液的半固体制剂,分散相小球的大小及其分布可能是产品关键的质量属性。传统上使用光学显微镜和光衍射技术来表征小球大小分布。这些技术存在样品制备偏差问题,并且在基质干扰和数据处理方面面临挑战。XRM成像作为一种新兴技术,与智能数据处理相结合,已被用于表征包括口服固体制剂、控释微球和冻干产品在内的药物剂型的微观结构。这项工作描述了我们首次尝试使用XRM成像来表征两种基于复杂乳液的半固体制剂,一种以凡士林为基质的软膏,其分散相包含亲水性液体,以及一种水包油乳膏。对该技术的初步评估表明,可以获得并参数化诸如小球大小分布、体积分数、空间分布均匀性、小球间距和小球球形度等微观结构细节。得出的结论是,XRM成像与基于人工智能的图像处理相结合,通过对小球属性进行三维可视化和参数化,生成半固体制剂微观结构的高级表征是可行的。这项技术有望提供半固体制剂更丰富的微观结构细节。当充分开发和验证后,它可能有助于对半固体制剂微观结构等效性进行定量比较。

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