AI Agents in Biomedicine outlines the concept of ‘AI scientists’—advanced collaborative systems that integrate machine learning tools with experimental platforms to bolster biomedical research.

• Skeptical Learning and Reasoning: Approaches that critically evaluate information and data.
• Continual Learning: Employs structured memory and generative models for ongoing adaptation.
• Integrative AI Tools: Harnesses large language models to incorporate robust scientific knowledge.
• Discovery Workflows: Proficient in planning and self-assessment for optimizing research procedures.
• Innovative Impact: Could revolutionize cell simulation, phenotype control, circuit design, and therapy development.

These AI agents may significantly expand the horizons of biomedical discovery by combining human creativity with AI’s analytical prowess. Their ability to analyze vast datasets, navigate complex hypothesis spaces, and perform repetitive tasks efficiently could lead to unprecedented breakthroughs in understanding and treating diseases. Such collaborations between AI agents and researchers could become a cornerstone of future biomedical advancements.