通过将粉末压缩设备跨类型和规模转移,加快药品平板电脑开发
Luca Beccaro1, Pierantonio Facco1, Ranjit M Dhenge2
1CAPE-Lab - Computer-Aided Process Engineering Laboratory, Department of Industrial Engineering, University of Padova, via Marzolo 9, Padova PD, 35131, Italy.
International journal of pharmaceutics
|November 4, 2024
概括
一种新的转移学习方法从压缩机模拟器 (CS) 数据中预测滚筒压缩机 (RC) 配置文件. 这种方法准确地估计了使用较少材料的粉末缩行为,这对于制药开发至关重要.
科学领域:
- 制药制造业 制药制造业 制药制造业
- 粉末技术的粉末技术是什么
- 化学工程是化学工程的组成部分.
背景情况:
- 滚筒压缩 (RC) 对于制药片的生产至关重要,需要特定的设置才能达到预期的结果.
- 获得RC压缩配置文件需要大量的粉末,在早期药物开发过程中通常无法获得.
- 压缩机模拟器 (CS) 使用较少的粉末提供了具有成本效益的替代方案,但产生的配置不同于RCs.
研究的目的:
- 开发一种转移学习方法,用于从CS数据中预测RC压缩配置文件.
- 建立基于压缩压力的质量校正因子预测的通用相关性.
- 为了提高使用最小粉末预测RC压缩配置文件的准确性.
主要方法:
- 使用转移学习方法来关联CS和RC压缩配置文件.
- 应用约翰逊模型和质量校正因子理论来分析压缩行为.
- 开发了作为压力函数的质量校正因子的通用相关性.
- 使用六种不同的粉末配方验证了转移模型.
主要成果:
- 质量校正因子对特定粉末配方的依赖程度最小.
- 为了预测基于压力的质量校正因子,开发了一种通用相关性.
- 与使用恒定质量校正因子相比,转移模型显著提高了RC压缩配置文件的预测准确性.
结论:
- 拟议的转移学习方法有效地从压缩机模拟器数据中预测滚筒压缩机配置文件.
- 质量校正因子的概括相关性简化了预测粉末缩行为的方法.
- 这种方法减少了制药开发中大量粉末的需求,节省了成本和时间.
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