Challenge
The United States has cataloged life in extraordinary detail, but it lacks the ability to confidently predict the behavior of complex living systems from smaller, simpler building blocks, such as proteins or genes. We intend to change that by building a foundation for biology as predictable as the physical sciences by measuring and understanding the natural laws and causal mechanisms governing genomes, proteins, cells, tissues, systems, and eventually whole organisms.
AI Solution
By linking and integrating multiple inputs, such as nucleic acid sequences, protein structures, multi-omics analyses, imaging, and perturbation data into models and pipelines that connect molecular-scale components to broader system behavior and model biological features, functions, processes, pathways, and regulation at multiple size and temporal scales to better model and understand the complexity of biology. Mechanism-, biology- and physics-constrained AI models will improve our understanding of the fundamental rules of life. Automated, biological data-focused cloud labs will identify and gather data to fill critical gaps and compress the cycle of discovery, including bridging the genotype-to-phenotype gap.
Justification
The United States has built a vast corpus of biological data that spans the full range of biological complexity, from genomes and proteins, to cells, tissues, and whole organisms, positioning it to lead the development of AI-enabled solutions with enormous benefits for health, energy, agriculture, and the economy. The Department of Health and Human Services serves as the hub for some of the most comprehensive repositories for DNA, RNA, protein-sequence, and protein-structure data; the Department of Energy contributes microbial, plant, and environmental genomics paired with national-scale computing capabilities; the National Science Foundation brings foundational research in AI and biology, a National Ecological Observatory Network and Ocean Observatories, and shared data and computing resources; the Department of War provides applied research in AI, extensive computing resources and molecular biological data from model microbial systems and environmental matrices; and the Department of Agriculture brings plant, animal, and microbial datasets spanning decades. United through a common platform and connected with autonomous laboratories capabilities that will generate massive volumes of low and high-resolution biological data, these assets will transform the field of biology.
National Impact
A predictive foundation drives the bioeconomy’s flywheel by accelerating every step of discovery. When progress becomes incremental and predictable rather than trial and error, achieving ambitious goals become a matter of direction and intent, not technical feasibility, turning 70 years of fragmented genomic, cellular, proteomic, imaging, and clinical data into one secure, integrated platform to accelerate scientific advancement.
This was last updated .