Version 1
: Received: 9 October 2022 / Approved: 17 October 2022 / Online: 17 October 2022 (02:03:36 CEST)
How to cite:
Ezra, S.; Danter, W. R. Nipah Pandemic Preparedness: Machine Leaning-Derived Whole Brain Organoid Simulations for Identifying Optimal Vaccine Candidates against the Nipah Virus. Preprints2022, 2022100217. https://doi.org/10.20944/preprints202210.0217.v1
Ezra, S.; Danter, W. R. Nipah Pandemic Preparedness: Machine Leaning-Derived Whole Brain Organoid Simulations for Identifying Optimal Vaccine Candidates against the Nipah Virus. Preprints 2022, 2022100217. https://doi.org/10.20944/preprints202210.0217.v1
Ezra, S.; Danter, W. R. Nipah Pandemic Preparedness: Machine Leaning-Derived Whole Brain Organoid Simulations for Identifying Optimal Vaccine Candidates against the Nipah Virus. Preprints2022, 2022100217. https://doi.org/10.20944/preprints202210.0217.v1
APA Style
Ezra, S., & Danter, W. R. (2022). Nipah Pandemic Preparedness: Machine Leaning-Derived Whole Brain Organoid Simulations for Identifying Optimal Vaccine Candidates against the Nipah Virus. Preprints. https://doi.org/10.20944/preprints202210.0217.v1
Chicago/Turabian Style
Ezra, S. and Wayne R. Danter. 2022 "Nipah Pandemic Preparedness: Machine Leaning-Derived Whole Brain Organoid Simulations for Identifying Optimal Vaccine Candidates against the Nipah Virus" Preprints. https://doi.org/10.20944/preprints202210.0217.v1
Abstract
The evolving global SARS-CoV-2 pandemic emphasizes how unprepared we are for the emergence of the next lethal viral pathogen. A list of potential candidates was created by the World Health Organization which named Nipah virus infection as the highly lethal prototypic member of that list. Building on our earlier viral pandemic preparedness research into SARS-CoV-2 we have created computer simulations of Nipah virus infection complicated by encephalitis, the most common cause of Nipah-associated mortality. In the current experiments, we first created updated simulations of wild-type whole-brain organoids (aiWBO). Upon validation, the aiWBO were infected with the simulated Nipah virus genome. The Nipah encephalitis simulations (aiWBO-NiV) were then used to find optimal single, double, and triple protein combinations for candidates as potential targets for vaccine development. Our data suggest that the use of multi-viral proteins/epitopes chimera is the most promising approach to Nipah vaccine development and that employing artificial intelligence to guide the identification of promising vaccine candidates is an efficient and cost-effective strategy for future viral pandemic preparedness.
Medicine and Pharmacology, Epidemiology and Infectious Diseases
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
