NSF Org: |
DMR Division Of Materials Research |
Recipient: |
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Initial Amendment Date: | September 3, 2021 |
Latest Amendment Date: | September 3, 2021 |
Award Number: | 2118788 |
Award Instrument: | Standard Grant |
Program Manager: |
Eugenia Kharlampieva
ekharlam@nsf.gov (703)292-4520 DMR Division Of Materials Research MPS Direct For Mathematical & Physical Scien |
Start Date: | October 1, 2021 |
End Date: | September 30, 2025 (Estimated) |
Total Intended Award Amount: | $649,767.00 |
Total Awarded Amount to Date: | $649,767.00 |
Funds Obligated to Date: |
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History of Investigator: |
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Recipient Sponsored Research Office: |
101 COMMONWEALTH AVE AMHERST MA US 01003-9252 (413)545-0698 |
Sponsor Congressional District: |
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Primary Place of Performance: |
100 Venture Way, Suite 201 Hadley MA US 01035-9450 |
Primary Place of Performance Congressional District: |
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Unique Entity Identifier (UEI): |
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Parent UEI: |
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NSF Program(s): |
Special Initiatives, DMREF |
Primary Program Source: |
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Program Reference Code(s): |
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Program Element Code(s): |
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Award Agency Code: | 4900 |
Fund Agency Code: | 4900 |
Assistance Listing Number(s): | 47.049 |
ABSTRACT
Non-technical Description: Many vaccine production and delivery systems remain dependent on a cold chain requirement, which prevents millions of people from receiving vaccines annually. To increase the availability of current and future vaccines, the vaccine cold chain needs to be eliminated. While sugars and bulking agents are being explored to increase the thermal stability of viral vaccines, the cold chain is still the main method to stabilize viral vaccines. This is not only an issue for developing countries; proper temperature storage of vaccines is also a challenge in the US, with an outbreak of influenza having been potentially linked to improper vaccine refrigeration. A more standard and promising method to stabilize vaccine formulations is to add stabilizing excipients. With excipients, vaccines can be stored under refrigeration conditions. However, this approach has suffered from both a lack of generalizability and the absence of a fundamental understanding of the mechanism whereby stabilization is achieved. Empirical evidence has identified several excipients such as sugars, amino acids, and bulking agents like gelatin, dextran, and cellulose that help to stabilize proteins/viruses in both wet and dry formulations. In addition, it has been demonstrated that complex combinations of excipients (mixtures) are often used in final formulations. Experimental observations suggest that many of the excipients help to structure water and/or replace hydrogen-bonding interactions with the surface of the protein/virus to provide stability. However, most of the work published in this area has been empirical and experimental in nature and would be difficult to perform at the scale needed to elucidate the subtle ways in which molecular structure affects water structure and thus stability. In this project, a combination of experiments, modeling, and machine learning will be used to identify molecular features/motifs that impart this stability and use this framework to discover excipient mixtures for vaccine formulations. This approach has the potential to shift the paradigm for vaccine formulation ? allowing for tailoring of formulations based on knowledge of the virus itself, rather than through an iterative, Edisonian process.
Technical Description: In this research, the team will use molecular dynamics simulations and machine learning in concert with a panel of experimental techniques to identify and understand the key molecular motifs needed for excipient molecules to create a stable virus-containing formulation. The interactions of both viruses and excipients with water is a critical design parameter for the creation of stable formulations; however, the complexity of these interactions represents a vast parameter space that is difficult to deconvolute and not suited to traditional materials design. This DMREF program will combine experimental measurements of excipient-virus interactions with a rapid computational scheme to design stabilizing formulations to enable the minimization of cold chain requirements for viral vaccines. The stability of viruses and other proteins is directly connected to interactions with water. However, the complexity of the available interactions has prevented bottom-up prediction. A materials design protocol will be developed that predicts how molecular motifs such as hydrogen bonding and electrostatic interactions give rise to the structuring of water and correlate with changes in virus stability. During the project, high school and community college student will be exposed to graduate level science and their interest piqued towards future careers in science and engineering. The goals of this project will be to (1) attain a comprehensive protocol for testing the potential effects of a new excipient molecule on virus stability and (2) use the resulting data to develop a machine-learning algorithm to enable the predictive design of more complex excipient formations.
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.
PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH
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