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| Funder | National Science Foundation (US) |
|---|---|
| Recipient Organization | University of Pennsylvania |
| Country | United States |
| Start Date | Sep 01, 2024 |
| End Date | Aug 31, 2030 |
| Duration | 2,190 days |
| Number of Grantees | 5 |
| Roles | Principal Investigator; Co-Principal Investigator |
| Data Source | National Science Foundation (US) |
| Grant ID | 2400135 |
The Artificial Intelligence-driven RNA BioFoundry (AIRFoundry) addresses critical challenges in RNA technology research by establishing a user-friendly, open-access platform. This initiative integrates cutting-edge AI for RNA design, synthesis, and delivery, while also promoting knowledge sharing and reproducibility. AIRFoundry harnesses the potential of RNA by extending its impact beyond healthcare to fields such as agriculture, biotechnology, and environmental remediation.
AIRFoundry combines AI tools, automation, and microfluidics to uncover fundamental design principles that will accelerate RNA-based innovations. AIRFoundry serves three key functions: 1) optimizing RNA design, synthesis, and efficiency; 2) guiding and assisting researchers in developing effective delivery vehicles, like lipid nanoparticles, to transport RNA to intended targets; and 3) generating new knowledge towards establishing relationships between RNA design, delivery vehicles, and their activity in biological systems.
Furthermore, AIRFoundry emphasizes education and seeks to broaden participation in RNA research by training the next generation of scientists from diverse technical and geographical backgrounds while ensuring that its advanced technologies are accessible to a wide range of users, from academic researchers to small businesses. This collaborative, multidisciplinary environment fosters innovation, accelerates advancements in RNA research, and democratizes RNA technology, ultimately empowering a diverse workforce to address global challenges like climate change and food security.
The Artificial Intelligence-driven RNA BioFoundry (AIRFoundry) directly addresses critical roadblocks in RNA research by establishing a comprehensive framework that integrates cutting-edge artificial intelligence (AI) to uncover, share, and apply fundamental design principles of RNA and delivery vehicles. AIRFoundry operates through three distinct multidisciplinary research groups (MRGs) working in tandem with technology innovation groups (TIGs) that serve a wide range of users, from academic researchers to small businesses.
MRG-1 optimizes RNA design and synthesis through integration of cutting-edge biochemical methods and Bayesian optimization models to efficiently navigate the vast design space of RNA molecules, rapidly identifying optimal sequences for desired functionalities. MRG-2 advances the field of delivery vehicles by employing AI-refined design rules for lipid nanoparticles (LNPs).
By establishing the fundamental structure-activity relationships for LNPs, researchers can tailor these delivery systems for specific RNA cargos and target cells, ensuring efficient cellular uptake and maximizing performance across a broad set of applications. MRG-3 leverages AI to augment human expertise and decision-making across the entire RNA design, synthesis, and delivery workflow.
AI algorithms will be trained on large datasets that comprise RNA sequences, LNP compositions, and biological responses. This knowledge base will empower researchers to make informed decisions at every stage of development, accelerating discovery and optimizing RNA-based technologies. Complementing these MRGs, a set of TIGs focuses on translating fundamental research into technologies to support the AIRFoundry and its users.
TIG-1 focuses on automating RNA production, integrating robotics and chromatography to enhance the high-throughput synthesis and scalability of diverse RNA molecules for research and application. TIG-2 tackles the development of robust and rapid production of multiple LNPs with precisely controlled structures, enabling high-throughput screening and optimization of LNP properties for targeted RNA delivery.
TIG-3 focuses on developing cross-cutting tools that integrate knowledge sharing, simulations, data management and in-line sensing for seamless collaboration within the AIRFoundry platform. By harnessing the collective expertise of scientists and engineers from diverse fields such as RNA biology, AI, microfluidics, process engineering, and data management, AIRFoundry aims to establish a preeminent platform for RNA technology advancement and democratization.
Integrating AI-driven discovery and optimization with cutting-edge microfluidics and automation, AIRFoundry promises to revolutionize RNA research and to open a wide variety of new applications.
This project is jointly supported by Divisions of Emerging Frontiers (EF), Biological Infrastructure (DBI), and Molecular and Cellular Biosciences (MCB) in the Directorate for Biological Sciences (BIO), Division of Chemistry (CHE) in the Directorate for Mathematical and Physical Sciences (MPS), and the Directorate for Technology, Innovation and Partnerships (TIP).
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
University of Pennsylvania
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