DMS/NIGMS 1: Challenges in Stochastic Modeling and Computation for Sequential Vaccine Desi — NSF Award to Duke University (NC, $59
Vaccine effectiveness relies on inducing the immune system to generate protective antibodies. Because antibodies are generated by random processes coupled to positive selection, the ability to induce certain rare but desirable antibodies can be limited by the inherent probability of occurrence. This project uses comput
| Award title | DMS/NIGMS 1: Challenges in Stochastic Modeling and Computation for Sequential Vaccine Desi |
|---|---|
| Award ID | 2347859 |
| Awardee | Duke University |
| City | DURHAM |
| State | NC |
| Amount obligated | $599,999 |
| Principal investigator | Scott Schmidler |
| Program | NIGMS |
| Start date | 06/01/2024 |
| Abstract | Vaccine effectiveness relies on inducing the immune system to generate protective antibodies. Because antibodies are generated by random processes coupled to positive selection, the ability to induce certain rare but desirable antibodies can be limited by the inherent probability of occurrence. This project uses computational modeling to estimate the probability of antibody occurrence, and to infer pathways for the generation of desired antibodies, in order to help design vaccine regimens that m |
| Source | NSF Awards |
$799/mo
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