使用大视野,相对显微镜-断层技术和支持人工智能的图像分析技术对现实世界药物片的定量结构和构成阐明
Yinshan Chen1, Sruthika Baviriseaty2, Prajwal Thool1
1Synthetic Molecule Pharmaceutical Sciences, Genentech, Inc., 1 DNA Way, South San Francisco, CA, 94080, USA.
Pharmaceutical research
|January 8, 2025
概括
这项研究引入了一种与AI结合的新型相关显微镜-断层扫描方法,用于分析药品片. 该技术准确量化了药片结构和成分,有助于配方开发.
科学领域:
- 制药科学 制药科学
- 材料科学 材料科学 材料科学
- 图像分析 图像分析
背景情况:
- 药物片的内部结构和成分的表征对于配方和工艺开发至关重要.
- 传统方法往往缺乏分辨率或定量能力,无法完全阐明复杂的平板电脑微架构.
研究的目的:
- 为药品片的定量结构和组成分析提供相关的显微镜-断层分析方法.
- 整合基于机器学习的图像细分,以详细阐明平板电脑组件和孔隙性.
主要方法:
- 相对的马赛克视野扫描电子显微镜 (SEM) 和能量分散式X射线光谱 (EDS) 用于成分识别.
- 阶段对比同步X射线微计算机断层扫描 (SyncCT) 用于高分辨率体积成像 (0.36-μm分辨率).
- 用户指导,代监督和深度学习用于细分和量化细分的组件和孔.
主要成果:
- 在真实世界中的平板电脑中成功细分和量化构成颗粒和毛孔.
- 验证的片剂成分和孔隙性与实验值相匹配,显示出有序的混合物形成.
- 图像衍生的粒子大小分布与激光衍射测量一致;关键孔隙属性得到了合格.
结论:
- 使用SyncCT和AI的相关显微镜-断层学方法提供了新的,实用的结构和组成见解.
- 这种方法促进了更高效的药物药片配方和工艺开发.
- 能够对平板电脑微架构进行详细的描述,包括粒子分布和孔状网络属性.
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