CCA-04: Future of Advanced Bioeconomy Computing
Imagine a world where a young researcher, working from a remote village, contributes to groundbreaking discoveries in biotechnology, thanks to the Future of Advanced Bioeconomy Computing. She uses a modest laptop to access powerful cloud-based AI systems, crunching complex biological data that once required supercomputers. Her work, part of a global collaborative effort, leverages quantum computing and AI to create sustainable agricultural practices, massively improving crop yields while preserving her own local ecosystems. This interconnected web of innovation not only democratizes science, allowing talent from anywhere to contribute in a significant way, but also drives economic growth, creating new jobs and industries. The continuous investment in foundational research in advanced computing has turned what was once a distant dream of global scientific collaboration and sustainable living into a daily reality, showcasing the power of computing to drive the bioeconomy.
The integration of classical computing, quantum computing, and artificial intelligence opens transformative prospects for the bioeconomy. The challenge lies in harnessing this convergence to expedite discovery, scale engineering solutions, and reinforce bioeconomic sectors, while ensuring robust data security. The urgency arises from the need to integrate across a growing amount of multimodal biological datasets generated from ‘omics studies, high throughput phenotyping, biosensors, and outputs from digital labs, digital diagnostics, and self-driving labs. Advances in computing technology now make it practical, not just aspirational, to gain understanding from this diversity of data. New work in this area is crucial for enhancing discovery, scalability, and sustainability.
CASA-Bio stakeholders representing government, industry, and non-profit sectors, identified areas of mutual interest where concerted effort among them may lead more quickly to the realization of the envisioned future. These are a few of their ideas. Advances in this area hinge on identifying technical gaps in current computing capabilities for complex biological systems modeling. Access to diverse, bioeconomy-relevant datasets is critical, as is the tailoring of AI and machine learning for specific biotechnological challenges. Research should focus on leveraging advanced computing for hypothesis generation and discovery at scale, particularly in healthcare and life sciences, where traditional computing falls short. Collaborative 'moonshot' initiatives, such as training large language models for AI in biological sciences, present opportunities for breakthroughs in understanding and applying biological data across multiple domains. These endeavors require interdisciplinary collaboration and a blend of expertise from various agency and industry partners. We emphasize that this list is not comprehensive; we need you to help us think deeper within this subtheme!
As a member of the R&D community, you too are a CASA-Bio stakeholder, and providing your insight on R&D projects that undergird this sub-theme and lead to solutions is critical. Your ideas will matter! Your individual project ideas and those developed as part of the collaborative Town Hall process will be combined to produce an aggregate view. This view will help us understand not only the interests of the R&D community, but also what they are willing to do to advance the bioeconomy. Topics among the R&D project ideas we receive will help government, industry, and non-profit stakeholders see the potential of the US R&D community to address critical future needs and help define topics for future exploration through workshops and roadmapping.