title: TxAgent: An AI Agent for Therapeutic Reasoning Across a Universe of
    Tools
summary: 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.
paper_authors._id: 67d771335e9c4135a570f57f
paper_authors.name: Shanghua Gao
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paper_authors.name: Richard Zhu
paper_authors._id: 67d771335e9c4135a570f581
paper_authors.name: Zhenglun Kong
paper_authors.status: claimed_verified
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paper_authors.fullname: Tony Kong
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paper_authors.user: TonyK
paper_authors._id: 67d771335e9c4135a570f582
paper_authors.name: Ayush Noori
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paper_authors.fullname: Ayush
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paper_authors.user: ayushnoori
paper_authors._id: 67d771335e9c4135a570f583
paper_authors.name: Xiaorui Su
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paper_authors.fullname: Xiaorui Su
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paper_authors.user: Blair1213
paper_authors._id: 67d771335e9c4135a570f584
paper_authors.name: Curtis Ginder
paper_authors._id: 67d771335e9c4135a570f585
paper_authors.name: Theodoros Tsiligkaridis
paper_authors._id: 67d771335e9c4135a570f586
paper_authors.name: Marinka Zitnik
paper_authors.status: admin_assigned
paper_authors.statusLastChangedAt: 2025-03-17T08:55:18.525Z
paper_authors._id: 636826f95bb06007ea0e911e
paper_authors.avatarUrl: https://cdn-avatars.huggingface.co/v1/production/uploads/1667770136112-636826f95bb06007ea0e911e.jpeg
paper_authors.fullname: Marinka Zitnik
paper_authors.type: user
paper_authors.user: marinkaz
paper_title: TxAgent: An AI Agent for Therapeutic Reasoning Across a Universe of
    Tools
paper_summary: 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.
paper_ai_summary: TxAgent, an AI agent, uses multi-step reasoning and real-time biomedical knowledge retrieval to generate personalized treatment recommendations, outperforming leading models in drug reasoning tasks.
paper_ai_keywords: multi-step reasoning real-time biomedical knowledge retrieval drug interactions contraindications patient-specific treatment strategies ToolUniverse biomedical sources clinical reasoning cross-source validation drug reasoning tasks personalized treatment scenarios multi-step inference knowledge grounding tool-assisted decision-making