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English(EN) MoLRSI: A Recursive Self-Improving AI agent for Molecular Discovery

AI代理实现药物发现自动化,超越专家水平

两种新的AI代理El Agente Fármaco和MoLRSI已被开发出来,通过自动化复杂的计算工作流程来加速药物发现。El Agente Fármaco在arXiv论文中进行了详细介绍,它使用LLM技术将自然语言目标转化为可扩展的筛选流程,并整合了一个名为Fármaco Atlas的共享科学记忆以进行溯源跟踪。MoLRSI由Hugging Face Daily Papers提出,它是一个递归自改进代理,可以优化分子设计工作流程并保留跨任务记忆以增强搜索策略,在抗生素和肽结合物发现方面超越了专家主导的方法。 AI

影响 这些AI代理通过自动化复杂任务和提高实验命中率,展示了加速药物发现的巨大潜力,有可能降低新疗法的成本和上市时间。

排序理由 两篇研究论文介绍了用于药物发现的新型AI代理,并详细介绍了它们的方法论和性能基准。

在 Hugging Face Daily Papers 阅读 →

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AI代理实现药物发现自动化,超越专家水平

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两篇研究论文介绍了用于药物发现的新型AI代理,并详细介绍了它们的方法论和性能基准。
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报道来源 [2]

  1. arXiv cs.MA (Multiagent) TIER_1 English(EN) · Alán Aspuru-Guzik ·

    El Agente Fármaco:用于药物发现的可扩展人工智能科学家

    Computational drug discovery offers a growing range of tools for proposing and evaluating molecules, but combining them and deciding what to do next still requires substantial expert effort. Here, we introduce El Agente Fármaco, an AI scientist that uses modern large language mod…

  2. Hugging Face Daily Papers TIER_1 English(EN) ·

    MoLRSI:用于分子发现的递归自改进AI代理

    MoLRSI is an AI agent that optimizes molecular design workflows and retains cross-task memory to improve search policies, achieving higher experimental hit rates in antibiotic and peptide binder discovery than expert-led methods.