A Machine Learning Algorithm to Accelerate Development of in vivo DNA-vectored Antibody Countermeasures for the Warfighter
Abstract
Research under this effort is for the generation of a substantial in vivo expression dataset and a computational decision making algorithm that will dramatically accelerate development for field delivery of DNA-vectored antibody MCMs. If successful, this research would establish predictive analytic tools capable of predicting antibodies at therapeutic ranges for lifesaving use enabling rapid response efforts for combating emerging infectious disease of pandemic potential.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Sep 16, 2020
- Source ID
- N660012014049
Entities
People
- Daniel W Kulp
Organizations
- Defense Advanced Research Projects Agency
- Naval Information Warfare Center Pacific
- Wistar Institute