Haas, Quentin; Borisov, Nikolay; Alvarez, David Vicente; Ferdowsi, Sohrab; von Mayenn, Leonhard; Teodoro, Douglas; Amini, Poorya (2021). Vaccine Development in the Time of COVID-19: The Relevance of the Risklick AI to Assist in Risk Assessment and Optimize Performance [perspective]. Frontiers in digital health, 3, p. 745674. Frontiers Media 10.3389/fdgth.2021.745674
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The 2019 coronavirus (COVID-19) pandemic revealed the urgent need for the acceleration of vaccine development worldwide. Rapid vaccine development poses numerous risks for each category of vaccine technology. By using the Risklick artificial intelligence (AI), we estimated the risks associated with all types of COVID-19 vaccine during the early phase of vaccine development. We then performed a postmortem analysis of the probability and the impact matrix calculations by comparing the 2020 prognosis to the contemporary situation. We used the Risklick AI to evaluate the risks and their incidence associated with vaccine development in the early stage of the COVID-19 pandemic. Our analysis revealed the diversity of risks among vaccine technologies currently used by pharmaceutical companies providing vaccines. This analysis highlighted the current and future potential pitfalls connected to vaccine production during the COVID-19 pandemic. Hence, the Risklick AI appears as an essential tool in vaccine development for the treatment of COVID-19 in order to formally anticipate the risks, and increases the overall performance from the production to the distribution of the vaccines. The Risklick AI could, therefore, be extended to other fields of research and development and represent a novel opportunity in the calculation of production-associated risks.
Item Type: |
Journal Article (Further Contribution) |
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Division/Institute: |
04 Faculty of Medicine > Pre-clinic Human Medicine > Department of Clinical Research (DCR) |
UniBE Contributor: |
Haas, Quentin, Borissov, Nikolay, von Meyenn, Karl-Leonhard, Amini, Poorya |
ISSN: |
2673-253X |
Publisher: |
Frontiers Media |
Funders: |
[198] Innosuisse - Swiss Innovation Agency |
Language: |
English |
Submitter: |
Andrea Flükiger-Flückiger |
Date Deposited: |
23 Nov 2021 15:39 |
Last Modified: |
20 Feb 2024 14:16 |
Publisher DOI: |
10.3389/fdgth.2021.745674 |
PubMed ID: |
34796360 |
Uncontrolled Keywords: |
COVID-19 artificial intelligence pharmacology risk analysis vaccine |
BORIS DOI: |
10.48350/161436 |
URI: |
https://boris.unibe.ch/id/eprint/161436 |
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