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| Funder | National Science Foundation (US) |
|---|---|
| Recipient Organization | Cornell University |
| Country | United States |
| Start Date | Sep 01, 2021 |
| End Date | Aug 31, 2025 |
| Duration | 1,460 days |
| Number of Grantees | 5 |
| Roles | Co-Principal Investigator; Principal Investigator |
| Data Source | National Science Foundation (US) |
| Grant ID | 2124244 |
Vaccines, paint, fuels, cosmetics, dyes, plastic packaging, and many other products are formulations: one or more active ingredients mixed or chemically packaged with other supporting ingredients. Successful products depend on carefully crafted formulations to meet multiple design requirements: stability during storage and transportation, cost, safety, environmental impact, and others.
A range of factors, such as adoption of sustainably sourced ingredients or emergence of new diseases, create a constant need for new formulations. Such formulations are hard to develop. Ingredients can interact in a complex way and datasets are often limited, making it difficult to know a formulations’ properties without trial and error.
Compounding the challenge, the number of ways that ingredients can be combined becomes enormous as the ingredient list grows. This makes formulation development one of the most vexing, time-consuming, and costly steps in bringing a new product to market. Overcoming this challenge to create a paradigm for faster and more reliable formulation development would lead to new products and accelerate US manufacturing.
We see a path toward radically transforming formulation development, supported by a new effort, the Center for Accelerated Formulation Engineering (CAFE). This would nurture and build on recent convergence research at the intersection of artificial intelligence (AI) and the chemical sciences, while being responsive to societal need for new formulations, regulation, manufacturing and business development.
Here, we propose a series of workshops devoted to advancing along this path. The central idea is to engage stakeholders from academia, industry, consultancies, and regulatory agencies into considering how recent advances in machine learning, AI, and high-throughput synthesis and characterization can all be leveraged to mitigate the formulation-development burden.
Workshops with diverse and broadly representative speakers and attendees will be organized around the three central themes of Public and Personal Health, Agriculture and Food. This would bring together an interdisciplinary team of researchers to begin teambuilding for a full Engineering Research Center proposal to be submitted in 2022.
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.
Cornell University
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