Researchers present ClinAgent, an agent built on the ReAct pattern that lets users query clinical trial registries through natural language instead of manual searching. The system is designed to handle semi-structured registry data and combine information across sources. The work is described in an arXiv preprint (2609.13860).
A new arXiv paper introduces ClinicalReTrial, a system that uses self-evolving AI agents to revise clinical trial protocols. The work targets the high cost and complexity of drug development, where trial designs are written as lengthy natural-language documents that are difficult to analyze manually. The authors frame agent-based redesign as an alternative to conventional manual protocol review.
A new arXiv paper introduces SatIR, a retrieval method aimed at settings where candidates must meet a specific profile's constraints rather than just be topically similar. Clinical trial matching is used as the motivating high-stakes case, where missing an eligible patient or trial carries real cost. The approach targets scalable, high-recall constraint satisfaction across many competing profiles.