TxAgent：一款跨工具宇宙进行诊疗推理的AI智能体

TxAgent: An AI Agent for Therapeutic Reasoning Across a Universe of Tools

March 14, 2025

作者: Shanghua Gao, Richard Zhu, Zhenglun Kong, Ayush Noori, Xiaorui Su, Curtis Ginder, Theodoros Tsiligkaridis, Marinka Zitnik

cs.AI

摘要

精准医疗需要多模态自适应模型来生成个性化治疗建议。我们推出了TxAgent，这是一款AI智能体，它利用多步推理和实时生物医学知识检索，通过一个包含211种工具的工具箱来分析药物相互作用、禁忌症及针对患者的特定治疗策略。TxAgent评估药物在分子、药代动力学和临床层面的相互作用，根据患者共病和并发用药情况识别禁忌症，并依据个体患者特征定制治疗策略。它从多个生物医学来源检索并综合证据，评估药物与患者状况之间的相互作用，并通过迭代推理优化治疗建议。TxAgent根据任务目标选择工具，并执行结构化函数调用，以解决需要临床推理和跨源验证的治疗任务。ToolUniverse整合了来自可信来源的211种工具，包括自1939年以来所有美国FDA批准的药物以及Open Targets验证的临床见解。TxAgent在五个新基准测试（DrugPC、BrandPC、GenericPC、TreatmentPC和DescriptionPC）中超越了领先的大型语言模型、工具使用模型和推理智能体，覆盖了3,168个药物推理任务和456个个性化治疗场景。在开放式药物推理任务中，TxAgent达到了92.1%的准确率，超越了GPT-4o，并在结构化多步推理中优于DeepSeek-R1（671B）。TxAgent能够泛化处理药物名称变体和描述。通过整合多步推理、实时知识基础和工具辅助决策，TxAgent确保治疗建议符合既定的临床指南和现实世界证据，降低不良事件风险，提升治疗决策质量。

English

Precision therapeutics require multimodal adaptive models that generate personalized treatment recommendations. We introduce TxAgent, an AI agent that leverages multi-step reasoning and real-time biomedical knowledge retrieval across a toolbox of 211 tools to analyze drug interactions, contraindications, and patient-specific treatment strategies. TxAgent evaluates how drugs interact at molecular, pharmacokinetic, and clinical levels, identifies contraindications based on patient comorbidities and concurrent medications, and tailors treatment strategies to individual patient characteristics. It retrieves and synthesizes evidence from multiple biomedical sources, assesses interactions between drugs and patient conditions, and refines treatment recommendations through iterative reasoning. It selects tools based on task objectives and executes structured function calls to solve therapeutic tasks that require clinical reasoning and cross-source validation. The ToolUniverse consolidates 211 tools from trusted sources, including all US FDA-approved drugs since 1939 and validated clinical insights from Open Targets. TxAgent outperforms leading LLMs, tool-use models, and reasoning agents across five new benchmarks: DrugPC, BrandPC, GenericPC, TreatmentPC, and DescriptionPC, covering 3,168 drug reasoning tasks and 456 personalized treatment scenarios. It achieves 92.1% accuracy in open-ended drug reasoning tasks, surpassing GPT-4o and outperforming DeepSeek-R1 (671B) in structured multi-step reasoning. TxAgent generalizes across drug name variants and descriptions. By integrating multi-step inference, real-time knowledge grounding, and tool-assisted decision-making, TxAgent ensures that treatment recommendations align with established clinical guidelines and real-world evidence, reducing the risk of adverse events and improving therapeutic decision-making.