自主 Agentic-AI 系统能否在未来十年加速药物发现与开发？
Can autonomous Agentic-AI systems accelerate drug discovery and development in the next decade?
一篇发表于 Briefings in Bioinformatics 的综述评估了自主 Agentic-AI 系统在制药价值链各环节的影响，覆盖供应链编排、生产优化、早期药物发现、工艺开发和监管情报。这类系统具备自主推理、决策与自适应学习能力，可提升运营韧性、缩短开发周期并加速新治疗候选物的识别。文章同时指出，其广泛采用面临人力整合、伦理问责、治理与监管合规等挑战，解决这些问题是大规模可靠部署的前提。该综述还梳理了未来十年塑造 Agentic-AI 影响力的关键因素，并给出对其在制药创新中角色演变的前瞻判断。
来源：Briefings in Bioinformatics · doi.org
The pharmaceutical industry is experiencing a profound transformation driven by rapid advancements in artificial intelligence (AI), increasing research and development complexity, and the expiration of key patents. Agentic-AI systems, which enable autonomous reasoning, decision-making, and adaptive learning beyond traditional data-driven automation, represent a paradigm shift in this context. This review examines the impact of Agentic-AI across the pharmaceutical value chain, including supply chain orchestration, manufacturing optimization, early-stage drug discovery, process development, and regulatory intelligence. These systems enhance operational resilience, reduce development timelines, and accelerate the identification of new therapeutic candidates by fostering dynamic human-AI collaboration. However, the widespread adoption of Agentic-AI introduces significant challenges related to workforce integration, ethical accountability, governance, and regulatory compliance. Addressing these challenges is essential for reliable and scalable deployment. This study identifies key factors shaping Agentic-AI’s influence over the next decade and provides a forward-looking perspective on its evolving role in pharmaceutical innovation.