This Project Grant award from the National Science Foundation (CFDA 47.070 - Computer and Information Science and Engineering) to the Regents of the University of Minnesota will provide $220,000 to develop advanced generative AI methodologies and computational tools to expedite drug discovery and enhance cost efficiency. The key objectives are to create a holistic generative AI framework capable of generating high-quality drug candidates with multiple desired properties, as well as a direct...
This Project Grant award of $305,000.00 from the National Science Foundation's (NSF) Technology, Innovation, and Partnerships (CFDA 47.084) program aims to revolutionize drug discovery by accelerating molecular dynamics simulations through advanced AI techniques. The project, awarded to Giwotech Inc. in Dorchester, MA, seeks to develop a robust neural network model capable of simulating protein systems up to 500 times faster than current GPU-based classical molecular dynamic simulators while...
The Ohio State University was awarded a $499,995 project grant from the National Science Foundation Division of Information and Intelligent Systems under the Computer and Information Science and Engineering federal grant program (CFDA 47.070). The grant will support the "III:SMALL: INTERPRETABLE DEEP GENERATIVE MODELS FOR DRUG DEVELOPMENT" project from November 1, 2021 through October 31, 2024. The project aims to advance the development of interpretable deep learning models for drug...
This Project Grant award of $500,000 from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program will support research at the University of Michigan to develop extrapolation-aware conditional generative modeling and experimental design methods. The goal is to address the challenge of generating novel molecules with desired properties, which is often hindered by data scarcity and the inability to accurately model rare, exceptional properties that...
This $100,000 Project Grant awarded by the National Science Foundation (NSF) under the Biological Sciences (CFDA 47.074) program aims to accelerate protein engineering through the integration of cutting-edge artificial intelligence (AI) methods and advanced laboratory automation. The primary objectives are to develop new AI techniques tailored to the unique challenges of protein engineering, and to leverage these AI capabilities to guide the design and discovery of functional proteins with...
This $499,742 Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program, with an award date of April 15, 2025 and an ultimate completion date of March 31, 2027, aims to develop a novel AI framework for designing new non-addictive pain relief medications to address the opioid crisis. The primary objectives are to create a generative AI system that integrates scientific knowledge and grammar-based molecular encodings to...
This $400,000 Project Grant awarded by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CFDA 47.070) program supports the development of a new framework and tools for advancing data-centric artificial intelligence (AI) through generative approaches to feature space reconstruction. The project aims to transform the traditional way of constructing feature spaces by using deep generative learning instead of manual or classical discrete search...
This Project Grant award of $233,332 from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program will support collaborative research to accelerate protein engineering using evolution-guided generative AI and an automated biofoundry. The research aims to combine cutting-edge AI methods with advanced laboratory automation to greatly speed up the discovery of new proteins with enhanced properties, offering significant potential impact across...
This Project Grant award of $275,956 from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program aims to develop an engineered cyber-physical system that combines advanced biological models with artificial intelligence methods for predictive, automated screening of anti-cancer drugs and optimization of their dosing. The key products and services to be delivered under this award include: 1) Adoption of 3D bioprinting to generate vascularized ductal...
This Project Grant award, provided by the National Science Foundation (NSF) under the Technology, Innovation, and Partnerships (CFDA 47.084) program, supports the development of an AI-enabled toolkit for optimizing combination drug research and development. The $264,736 award to Duet Biosystems, Inc. in Nashville, TN aims to leverage the Multidimensional Synergies of Combination (MUSYC) algorithm to improve the selection of effective drug combinations across disease areas such as cancer,...
This $280,000 Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program supports the development of comprehensive generative AI methodologies and computational tools to expedite drug discovery, enhance cost efficiency, and improve success rates. The project aims to create a holistic generative AI framework capable of generating high-quality drug candidates with multiple desired properties, with the potential to transform pharmaceutical research. Key research activities include: (1) developing a conditional diffusion model for 3D molecule generation to enable both ligand-based and structure-based drug design, and (2) introducing a direct multi-property optimization framework to optimize drug-specific properties without requiring expensive model retraining. This award reflects NSF's mission to advance scientific knowledge and technological innovation in computing and information science, with the goal of significantly reducing the time, cost, and resources required for drug discovery while increasing its success rates. The project will be conducted by The Ohio State University, a prominent public research university with extensive expertise in delivering complex research and technological solutions to federal agencies.