在制药研发领域实施数据科学和人工智能战略:挑战和解决方案
Vincenzo Garzya1, Gabriella Rustici1, Tom Diethe1
1Data Science & Artificial Intelligence, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK.
Drug discovery today
|November 3, 2025
概括
制药行业需要数据科学 (DS) 和人工智能 (AI) 来保持竞争力. 本文概述了一个操作框架,以克服挑战,并实现DS&AI在药物开发中的潜力.
科学领域:
- 制药研发领域的研究和开发.
- 数据科学是数据科学.
- 人工智能的人工智能是人工智能.
背景情况:
- 制药行业面临着越来越大的压力,需要创新和加速药物发现.
- 数据科学和人工智能 (DS&AI) 的整合对于保持竞争力至关重要.
研究的目的:
- 提出实施DS&AI在制药研发中的操作框架.
- 应对挑战并提出解决方案,以实现DS&AI的潜力.
主要方法:
- 审查当前的DS&AI在药物研发中的应用.
- 开发一个概念性的操作框架.
- 确定关键挑战和相应的解决方案.
主要成果:
- 拟议的框架为DS&AI集成提供了一个结构化的方法.
- 关键的挑战包括数据可访问性,人才获取和监管障碍.
- 解决方案包括战略数据治理,跨学科团队建设和适应性监管策略.
结论:
- 在药品研发中实施DS&AI需要一个强大的运营框架.
- 克服已识别的挑战对于成功的采用和创新至关重要.
- 该框架有助于实现DS&AI在药物开发中的变革潜力.
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