Aug 2026· Drug Discovery Today· pp.
104781
· 0 citations· 131 references
Medicine
TL;DR
Evidence is synthesised on agentic AI and LLMs applied to precision medicine, encompassing drug discovery, genomics, oncology, rare disease diagnostics and clinical pharmacology, which examines architectural components, recent validation milestones and emerging challenges.
Abstract
Precision medicine seeks to individualise care by integrating multimodal biomedical data, yet most deployed clinical artificial intelligence (AI) remains assistive, providing predictions without managing workflows or adapting autonomously. Agentic AI, built on large language models (LLMs), has emerged as a paradigm characterised by autonomy, goal-directed reasoning, memory, planning and tool use. This review synthesises evidence on agentic AI and LLMs applied to precision medicine, encompassing drug discovery, genomics, oncology, rare disease diagnostics and clinical pharmacology. This review also examines architectural components, recent validation milestones and emerging challenges, including hallucination, sociodemographic bias and evolving regulatory frameworks across the FDA, the EU AI Act and the WHO.
Artificial intelligence (AI) in biomedicine has evolved from pattern-recognition for medical image analysis to generative models like AlphaFold that predict protein structures. Tools such as Elicit, GPT-Rosalind, and Claude Science now bridge prediction and reasoning through literature synthesis, domain-tuned models, a...
Lucie Y. Guo, D. S. Ting, Xin-Yi Su et al.· Cell· 0 citations
Multimodal artificial intelligence (AI) agents are emerging in healthcare as systems that integrate heterogeneous clinical data, foundation models (FMs), tools, and agentic workflows, but their applications and translational readiness remain unclear. We conducted a scoping review of 37 peer-reviewed studies publish...
Kai Yu, Shuang Zhou, Yu Hou et al.· npj Digital Medicine· 1 citation
This work states that network medicine (NM), which models biological systems as dynamic, interconnected networks, enables integration of multiomic data and better characterizes disease mechanisms to guide precision therapies when combined with AI.
P. Portincasa, M. Khalil, P. Novielli et al.· European Journal of Clinical...· 0 citations
This review evaluates the current state of AI applications in medicine, focusing on clinical knowledge encoding, molecular drug discovery, and administrative workflow optimization, while critically addressing the technical, ethical, and systemic challenges of their institutional implementation.
Aleksandra Stańczyk, Kinga Haduch, Zuzanna Michalska et al.· International Journal of Inn...· 0 citations
This survey aims to examine the paradigm shift from predictive, assistive artificial intelligence (AI) to agentic AI in healthcare. Agentic AI refers to systems capable of perceiving, reasoning, planning and acting with adaptive autonomy, enabling more proactive and intelligent decision-making within complex health...
M. Albashrawi· Information Discovery and De...· 0 citations
