建设未来的非临床病理学实验室,以实现制药研究的卓越
D G Rudmann1, L Bertrand1, A Zuraw1
1Charles River Laboratories, Digital Toxicologic Pathology, Discovery and Safety Assessment, Wilmington, DE, USA.
Drug discovery today
|August 20, 2023
概括
一个使用人工智能 (AI) 的数字病理学实验室在三大洲开发. 这种人工智能增强系统提高了效率,并在COVID-19大流行期间减轻了干扰,加速了药物开发.
科学领域:
- 数字病理学数字病理学
- 人工智能在药物开发中的作用
- 实验室信息管理系统的管理系统
背景情况:
- 非临床病理学实验室对于制药药物开发至关重要.
- 随着COVID-19的爆发,人们越来越需要有弹性和高效的实验室工作流程.
- 数字化转型对于科学研究的现代化至关重要.
研究的目的:
- 概述建立一个完全数字化的,人工智能增强的非临床病理学实验室的路线图.
- 展示数字化病理学工作流程的可行性和好处.
- 提高药物开发决策的效率和速度.
主要方法:
- 实验室信息管理系统 (LIMS) 验证的实验室良好实践 (GLP) 的实施.
- 整体幻灯片扫描仪 (WSS) 和图像管理系统 (IMS) 的集成.
- 利用基于人工智能的虚拟染色和深度学习来支持决策.
主要成果:
- 一个完全数字化的,人工智能增强的非临床病理学实验室在三大洲成功建立.
- 数字化工作流在很大程度上减轻了COVID-19大流行引起的干扰.
- 该系统支持使用先进的人工智能工具进行数字诊断.
结论:
- 非临床病理学实验室的数字化转型提高了效率和创新.
- 人工智能增强的数字病理学加速了药物开发决策.
- 这个模型为未来的制药研究提供了一个强大的框架.
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