Empowering biomedical discovery with AI agents
Year: 2024
Type: review
Abstract: We envision "AI scientists" as systems capable of skeptical learning and reasoning that empower biomedical research through collaborative agents that integrate AI models and biomedical tools with experimental platforms. Rather than taking humans out of the discovery process, biomedical AI agents combine human creativity and expertise with AI's ability to analyze large datasets, navigate hypothesis spaces, and execute repetitive tasks. AI agents are poised to be proficient in various tasks, planning discovery workflows and performing self-assessment to identify and mitigate gaps in their knowledge. These agents use large language models and generative models to feature structured memory for continual learning and use machine learning tools to incorporate scientific knowledge, biological principles, and theories. AI agents can impact areas ranging from virtual cell simulation, programmable control of phenotypes, and the design of cellular circuits to developing new therapies.
Source: Cell
Language: English
Subfield: Health Informatics
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
Estimated APC paid: $10,400
Funders: Milken Institute, National Science Foundation, Harvard Medical School, Google, Chan Zuckerberg Initiative, Aligning Science Across Parkinson’s, National Institutes of Health, Harvard Data Science Initiative, Harvard University, Medical Research Council, National Human Genome Research Institute, Eunice Kennedy Shriver National Institute of Child Health and Human Development
OpenAlex ID: W4403925918