Enlisting machine learning to pick the perfect vaccine

In an op-ed that appeared Jan. 10 in the Santa Fe Reporter, molecular biologist Jessica Kubicek-Sutherland describes a team effort at the Lab to develop a tool to predict which vaccine technologies are the best match for a given pathogen.

“This will increase the rate of success and reduce the number of initial vaccine candidates required. That’s millions of potentially wasted dollars put instead toward more likely candidate projects,” she wrote.

Read the full story as it appeared in the Santa Fe Reporter.