TxAgent: An AI Agent for Therapeutic Reasoning Across a Universe of Tools
On the map: LLM reasoning → Clinical and biomedical applications
also in 1 more
Abstract (arXiv)
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.
Key facts. Cited by 59 papers in the map (data through 14 Oct 2026). Placed in Clinical and biomedical applications, one of 17 directions in LLM reasoning. Builds on 14 of its 44 references that are in the map. First posted on arXiv 14 Mar 2025.
Builds on
14 of 44 references.
References · 14
- 2024The Llama 3 Herd of Modelscited by 14,715
- 2021LoRA: Low-Rank Adaptation of Large Language Modelscited by 14,380
- 2023LLaMA: Open and Efficient Foundation Language Modelscited by 14,132
- 2025DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learningcited by 6,330
- 2023Qwen Technical Reportcited by 3,344
- 2023Mistral 7Bcited by 3,164
- 2023Retrieval-Augmented Generation for Large Language Models: A Surveycited by 2,212
- 2023Towards General Text Embeddings with Multi-stage Contrastive Learningcited by 723
- 2023ChemCrow: Augmenting large-language models with chemistry toolscited by 631
- 2023MEDITRON-70B: Scaling Medical Pretraining for Large Language Modelscited by 274
- 2024ToolACE: Winning the Points of LLM Function Callingcited by 216
- 2024ClinicalBench: Can LLMs Beat Traditional ML Models in Clinical Prediction?cited by 32
2 more
- 2024Language Models are Surprisingly Fragile to Drug Names in Biomedical Benchmarkscited by 17
- 2025Multimodal Medical Code Tokenizercited by 14
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Citing papers per year: 2025: 27; 2026: 32.
59 papers.
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- 2025RCR-Router: Efficient Role-Aware Context Routing for Multi-Agent LLM Systems with Structured Memorycited by 27
- 2025A Survey on Agent Workflow -- Status and Futurecited by 14
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- 2026Autonomous Research Agents: A Survey of AI Scientists and the Verification Gapcited by 9
- 2025BioVerge: A Comprehensive Benchmark and Study of Self-Evaluating Agents for Biomedical Hypothesis Generationcited by 4
- 2025MolAct: An Agentic RL Framework for Molecular Editing and Property Optimizationcited by 2
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- 2026PrivMeSA: Privacy-Aware Self-Evolving Multi-Agent System for Medicine via Local-Remote LLM Collaboration29 Sep 2026
- 2026Asclepius: An Adaptive Harness for Long-Horizon Clinical Agents11 Sep 2026
- 2026CAi Copilot: Reducing Operational Workload in Molecular Design through Intent-Driven Agentic Workflows7 Aug 2026
- 2026EMBL AI Librarian: Life-Sciences Knowledge Layer for AI Agents30 Jul 2026
- 2026Evaluating Agentic Bioinformatics through Function, Evidence, and Validation30 Jul 2026
- 2026Autonomous Research Agents: A Survey of AI Scientists and the Verification Gap29 Jun 2026
- 2026DrugClaw and DrugAudit: A Primary-Source-Grounded Agent and Authority-Aware Benchmark for Drug-Information Question Answering31 May 2026
- 2026BioResearcher: Scenario-Guided Multi-Agent for Translational Medicine7 May 2026
- 2026TheraAgent: Self-Improving Therapeutic Agent for Precise and Comprehensive Treatment Planning7 May 2026
- 2026Externalization in LLM Agents: A Unified Review of Memory, Skills, Protocols and Harness Engineering9 Apr 2026
- 2026Which Tool Response Should I Trust? Tool-Expertise-Aware Chest X-ray Agent with Multimodal Agentic Learning25 Feb 2026
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- 2025MedAgentGym: A Scalable Agentic Training Environment for Code-Centric Reasoning in Biomedical Data Sciencecited by 23
- 2025End-to-End Agentic RAG System Training for Traceable Diagnostic Reasoningcited by 10
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- 2025Unleashing Scientific Reasoning for Bio-experimental Protocol Generation via Structured Component-based Reward Mechanismcited by 3
- 2025Traj-CoA: Patient Trajectory Modeling via Chain-of-Agents for Lung Cancer Risk Predictioncited by 2
- 2026Med-CoReasoner: Reducing Language Disparities in Medical Reasoning via Language-Informed Co-Reasoningcited by 2
- 2025When Retrieval Succeeds and Fails: Rethinking Retrieval-Augmented Generation for LLMscited by 1
- 2025How Well Do LLMs Understand Drug Mechanisms? A Knowledge + Reasoning Evaluation Datasetcited by 1
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- 2026Med-CoReasoner: Reducing Language Disparities in Medical Reasoning via Language-Informed Co-Reasoning13 Jan 2026
- 2025CureAgent: A Training-Free Executor-Analyst Framework for Clinical Reasoning5 Dec 2025
- 2025How Well Do LLMs Understand Drug Mechanisms? A Knowledge + Reasoning Evaluation Dataset9 Nov 2025
- 2025Unleashing Scientific Reasoning for Bio-experimental Protocol Generation via Structured Component-based Reward Mechanism17 Oct 2025
- 2025CGBench: Benchmarking Language Model Scientific Reasoning for Clinical Genetics Research13 Oct 2025
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- 2025When Retrieval Succeeds and Fails: Rethinking Retrieval-Augmented Generation for LLMs10 Oct 2025
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- 2026From Literature to Hypotheses: An AI Co-Scientist System for Biomarker-Guided Drug Combination Hypothesis Generationcited by 0
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- 2026Benchmarking AI Agents for Addressing Scientific Challenges Across Scales10 Jun 2026
- 2026AutoScientists: Self-Organizing Agent Teams for Long-Running Scientific Experimentation27 May 2026
- 2026An explainable hypothesis-driven approach to Drug-Induced Liver Injury with HADES4 May 2026
- 2026Vibe Medicine: Redefining Biomedical Research Through Human-AI Co-Work26 Apr 2026
- 2026MedProbeBench: Systematic Benchmarking at Deep Evidence Integration for Expert-level Medical Guideline20 Apr 2026
- 2026Large Language Models Meet Biomedical Knowledge Graphs for Mechanistically Grounded Therapeutic Prioritization17 Apr 2026
- 2026The limits of bio-molecular modeling with large language models : a cross-scale evaluation3 Apr 2026
- 2026MolClaw: An Autonomous Agent with Hierarchical Skills for Drug Molecule Evaluation, Screening, and Optimization2 Apr 2026
- 2026Qworld: Question-Specific Evaluation Criteria for LLMs6 Mar 2026
12 newest of 19 All 19 (JSON)
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