New effort underway to help revolutionize future of vaccine development

A new multilaboratory effort funded by the Defense Threat Reduction Agency is underway, creating a machine-learning tool to revolutionize the future of vaccine development, rapidly choosing a suitable vaccine platform for any viral and bacterial pathogen. Led by Los Alamos National Laboratory, the Rapid Assessment of Platform Technologies to Expedite Response (RAPTER) tool will quantify to what degree the immunological correlates of protection match between what can be generated by each vaccine platform and what is required to resist an infection by that class of pathogen.

“Developing safe and effective vaccines is a critical component to establishing a robust response to combat any current, emerging or future biological threat. However, vaccine design, testing, and manufacturing are time-consuming and expensive activities,” said project lead Jessica Kubicek-Sutherland of Los Alamos. To streamline this process, the team proposes the development of a machine-learning tool to predict the most suitable vaccine technologies for a given pathogen to increase the rate of success and reduce the number of initial vaccine candidates required.

The cost of developing a single vaccine can be up to $68 million, with failure rates as high as 94%, so vaccine development typically starts with multiple candidates following a lengthy linear workflow to mitigate these costs and risks. Each vaccine platform generates a defined immune response based on its mechanism of presenting antigens to the host. Similarly, the host immune system is required to generate a distinct immune response to survive an infection by a pathogen.

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