Repurposing approved drugs offers a time-efficient and cost-effective alternative to traditional drug development. However, in silico prediction of repurposing candidates is challenging and requires the effective collaboration of specialists in various fields, including pharmacology, medicine, biology, and bioinformatics. Fragmented, specialized algorithms and tools often address only narrow aspects of the overall problem. Heterogeneous, unstructured data landscapes require the expertise of specialized users. Hence, these data services do not integrate smoothly across workflows. With ChatDRex, we present a conversation-based, multi-agent system that facilitates the execution of complex bioinformatic analyses aiming for network-based drug repurposing prediction. It builds on the integrated systems medicine knowledge graph (NeDRex KG). ChatDRex provides natural language access to its extensive biomedical knowledge base. It integrates bioinformatics agents for network analysis, literature mining, and drug repurposing. These are complemented by agents that evaluate functional coherence for in silico validation. Its flexible multi-agent design assigns specific tasks to specialized agents, including query routing, data retrieval, algorithm execution, and result visualization. A dedicated reasoning module keeps the user in the loop and allows for hallucination detection. By enabling physicians and researchers without computer science expertise to control complex analyses with natural language, ChatDRex democratizes access to bioinformatics as an important resource for drug repurposing. It enables clinical experts to generate hypotheses and explore drug repurposing opportunities, ultimately accelerating the discovery of novel therapies and advancing personalized medicine and translational research. ChatDRex is publicly available at apps.cosy.bio/chatdrex.

翻译：已批准药物的重定位为传统药物开发提供了一种省时且经济高效的替代方案。然而，药物重定位候选者的计算机预测具有挑战性，需要药理学、医学、生物学和生物信息学等多个领域的专家有效协作。零散的专业算法和工具通常仅解决整体问题的狭窄方面。异构、非结构化的数据环境需要专业用户的知识。因此，这些数据服务无法在工作流程中顺畅集成。我们提出了ChatDRex，这是一个基于对话的多智能体系统，旨在促进执行复杂的生物信息学分析，以实现基于网络的药物重定位预测。它建立在集成的系统医学知识图谱（NeDRex KG）之上。ChatDRex为其广泛的生物医学知识库提供自然语言访问。它集成了用于网络分析、文献挖掘和药物重定位的生物信息学智能体。这些智能体辅以评估功能一致性以进行计算机验证的智能体。其灵活的多智能体设计将特定任务分配给专门的智能体，包括查询路由、数据检索、算法执行和结果可视化。一个专用的推理模块使用户保持在循环中，并允许进行幻觉检测。通过使不具备计算机科学专业知识的医生和研究人员能够用自然语言控制复杂分析，ChatDRex将生物信息学作为药物重定位的重要资源进行了普及。它使临床专家能够生成假设并探索药物重定位机会，最终加速新疗法的发现，并推动个性化医疗和转化研究。ChatDRex可在apps.cosy.bio/chatdrex公开获取。