过去,现在和未来:图像分析在小分子制药开发中的应用
John F Gamble1, Hisham Al-Obaidi2
1Bristol Myers Squibb, Reeds Lane, Moreton, Wirral, CH46 1QW, UK; Department of Pharmacy, University of Reading, Reading RG6 6AH, UK.
Journal of pharmaceutical sciences
|August 17, 2024
概括
图像分析正在彻底改变制药中的颗粒特征. 先进的技术,包括人工智能,现在能够对粒子大小,形状和行为进行详细分析,改善药物开发.
科学领域:
- 制药科学 制药科学
- 材料科学 材料科学 材料科学
- 化学工程是化学工程的重要组成部分.
背景情况:
- 从历史上看,图像分析面临的局限性阻碍了其作为主要的特征化工具的使用.
- 制药应用的复苏是由增强的系统能力和需要进行详细的粒子形态评估所推动的.
- 在药物开发中,越来越多地认识到粒子大小和形状的重要性.
研究的目的:
- 提供当前在小分子制药领域的图像分析技术的概述.
- 突出粒子表征方法的创新和进步.
- 讨论整合人工智能 (AI) 进行增强的图像分析.
主要方法:
- 先进的图像分析用于精确的粒子大小和形状测量.
- 将建模和模拟与图像分析数据的整合.
- 机器学习和人工智能算法的应用用于数据解释.
- 在多组件系统中单个组件的表征.
主要成果:
- 图像分析现在提供了更丰富的数据集,超越了不那么有信息的描述符,向整个分布移动.
- 提高了粒子特性与散装粉末特性之间的联系的阐明.
- 增强对制造过程中材料变化的理解.
- 能够将最终的剂量形式行为与作用点上的粒子特性联系起来.
结论:
- 由人工智能和先进建模增强的图像分析为制药颗粒特征提供了强大的工具.
- 这些进步使我们能够更深入地了解材料特性及其对药物产品性能的影响.
- 这些技术的整合有助于更准确地预测和控制制造工艺和最终产品属性.
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