mlsanityData to 14 Oct 2026

Biomedical reasoning in action: Multi-agent System for Auditable Biomedical Evidence Synthesis

arXiv 2510.05335 ↗First posted 6 Oct 2025cs.AIcited by 0

On the map: LLM reasoning → Clinical and biomedical applications

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Abstract (arXiv)

We present M-Reason, a demonstration system for transparent, agent-based reasoning and evidence integration in the biomedical domain, with a focus on cancer research. M-Reason leverages recent advances in large language models (LLMs) and modular agent orchestration to automate evidence retrieval, appraisal, and synthesis across diverse biomedical data sources. Each agent specializes in a specific evidence stream, enabling parallel processing and fine-grained analysis. The system emphasizes explainability, structured reporting, and user auditability, providing complete traceability from source evidence to final conclusions. We discuss critical tradeoffs between agent specialization, system complexity, and resource usage, as well as the integration of deterministic code for validation. An open, interactive user interface allows researchers to directly observe, explore and evaluate the multi-agent workflow. Our evaluation demonstrates substantial gains in efficiency and output consistency, highlighting M-Reason's potential as both a practical tool for evidence synthesis and a testbed for robust multi-agent LLM systems in scientific research, available at https://m-reason.digitalecmt.com.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Placed in Clinical and biomedical applications, one of 17 directions in LLM reasoning. Builds on 13 of its 35 references that are in the map. First posted on arXiv 6 Oct 2025.

Builds on

13 of 35 references.

References · 13

  1. 2023AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversationcited by 1,988
  2. 2025Towards Scientific Intelligence: A Survey of LLM-based Scientific Agentscited by 98
  3. 2025BixBench: a Comprehensive Benchmark for LLM-based Agents in Computational Biologycited by 89
  4. 2024CellAgent: An LLM-driven Multi-Agent Framework for Automated Single-cell Data Analysiscited by 39
  5. 2024Simulating Human Strategic Behavior: Comparing Single and Multi-agent LLMscited by 21
  6. 2025PharmAgents: Building a Virtual Pharma with Large Language Model Agentscited by 21
  7. 2024Accelerating Clinical Evidence Synthesis with Large Language Modelscited by 16
  8. 2024Automating Exploratory Proteomics Research via Language Modelscited by 11
  9. 2025Scientific Hypothesis Generation and Validation: Methods, Datasets, and Future Directionscited by 9
  10. 2025BioAgents: Democratizing Bioinformatics Analysis with Multi-Agent Systemscited by 8
  11. 2024From Intention To Implementation: Automating Biomedical Research via LLMscited by 7
  12. 2025Integrating Expert Knowledge into Logical Programs via LLMscited by 3
1 more
  1. 2025SciClaims: An End-to-End Generative System for Biomedical Claim Analysiscited by 2

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  1. 2025Explainable Biomedical Claim Verification with Large Language Models
  2. 2025BioDisco: Multi-agent hypothesis generation with dual-mode evidence, iterative feedback and temporal evaluation
  3. 2025MedMMV: A Controllable Multimodal Multi-Agent Framework for Reliable and Verifiable Clinical Reasoning
  4. 2025Haibu Mathematical-Medical Intelligent Agent:Enhancing Large Language Model Reliability in Medical Tasks via Verifiable Reasoning Chains
  5. 2026VERITAS: A Multi-Agent Co-Scientist for Verifiable Image-Derived Hypothesis Testing ↗
  6. 2026Generating Biomedical Fact-Checking Reports with RL-Enhanced Agentic Search
  7. 2026ClinSeekAgent: Automating Multimodal Evidence Seeking for Agentic Clinical Reasoning
  8. 2026Evidence, Logic, and Compliance: Multi-Agent Structured Graph Reasoning with Expert Arbitration for Medical Referral