TxAgent：一款跨工具宇宙進行治療推理的AI代理

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

精準醫療需要多模態自適應模型來生成個性化治療建議。我們介紹了TxAgent，這是一種利用多步推理和實時生物醫學知識檢索的AI代理，通過211種工具組來分析藥物相互作用、禁忌症和患者特徵治療策略。TxAgent評估藥物在分子、藥代動力學和臨床層面的相互作用，根據患者共病和併用藥物識別禁忌症，並根據個體患者特徵定制治療策略。它從多個生物醫學來源檢索和綜合證據，評估藥物與患者狀況之間的相互作用，並通過迭代推理完善治療建議。它根據任務目標選擇工具，並執行結構化函數調用以解決需要臨床推理和跨來源驗證的治療任務。ToolUniverse整合了來自可信來源的211種工具，包括自1939年以來所有美國FDA批准的藥物以及來自Open Targets的驗證臨床見解。TxAgent在五個新基準測試（DrugPC、BrandPC、GenericPC、TreatmentPC和DescriptionPC）中表現優於領先的LLM、工具使用模型和推理代理，涵蓋了3,168個藥物推理任務和456個個性化治療場景。它在開放式藥物推理任務中達到了92.1%的準確率，超越了GPT-4o，並在結構化多步推理中優於DeepSeek-R1（671B）。TxAgent能夠泛化處理藥物名稱變體和描述。通過整合多步推理、實時知識基礎和工具輔助決策，TxAgent確保治療建議符合既定的臨床指南和現實世界證據，降低不良事件風險並改善治療決策。

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.