College of Pharmacy, University of Illinois, Chicago, IL, USA.
Drug Des Devel Ther. 2023 Sep 6;17:2691-2725. doi: 10.2147/DDDT.S424991. eCollection 2023.
Artificial intelligence (AI) and machine learning (ML) represent significant advancements in computing, building on technologies that humanity has developed over millions of years-from the abacus to quantum computers. These tools have reached a pivotal moment in their development. In 2021 alone, the U.S. Food and Drug Administration (FDA) received over 100 product registration submissions that heavily relied on AI/ML for applications such as monitoring and improving human performance in compiling dossiers. To ensure the safe and effective use of AI/ML in drug discovery and manufacturing, the FDA and numerous other U.S. federal agencies have issued continuously updated, stringent guidelines. Intriguingly, these guidelines are often generated or updated with the aid of AI/ML tools themselves. The overarching goal is to expedite drug discovery, enhance the safety profiles of existing drugs, introduce novel treatment modalities, and improve manufacturing compliance and robustness. Recent FDA publications offer an encouraging outlook on the potential of these tools, emphasizing the need for their careful deployment. This has expanded market opportunities for retraining personnel handling these technologies and enabled innovative applications in emerging therapies such as gene editing, CRISPR-Cas9, CAR-T cells, mRNA-based treatments, and personalized medicine. In summary, the maturation of AI/ML technologies is a testament to human ingenuity. Far from being autonomous entities, these are tools created by and for humans designed to solve complex problems now and in the future. This paper aims to present the status of these technologies, along with examples of their present and future applications.
人工智能 (AI) 和机器学习 (ML) 是计算领域的重大进展,建立在人类数百万年来开发的技术基础上——从算盘到量子计算机。这些工具已经发展到了一个关键的时刻。仅在 2021 年,美国食品和药物管理局 (FDA) 就收到了超过 100 份产品注册申请,这些申请大量依赖人工智能/机器学习来应用于监测和提高人类在编写档案方面的表现等。为了确保人工智能/机器学习在药物发现和制造中的安全有效使用,FDA 和众多其他美国联邦机构发布了不断更新的严格指南。有趣的是,这些指南通常是借助人工智能/机器学习工具本身生成或更新的。总体目标是加快药物发现速度,提高现有药物的安全性,引入新的治疗方式,并提高制造合规性和稳健性。最近 FDA 的出版物对这些工具的潜力持乐观态度,强调需要谨慎部署。这为处理这些技术的人员的再培训扩大了市场机会,并为新兴疗法(如基因编辑、CRISPR-Cas9、CAR-T 细胞、基于 mRNA 的治疗方法和个性化医学)提供了创新应用。总之,人工智能/机器学习技术的成熟是人类智慧的证明。这些技术远非自主实体,而是为人类创建和设计的工具,旨在解决现在和未来的复杂问题。本文旨在介绍这些技术的现状,并举例说明它们目前和未来的应用。