Alexander Gintsburg, the director of the Gamaleya National Research Center for Epidemiology and Microbiology, has announced that the integration of neural network technologies could significantly expedite the development of personalized cancer vaccines, reducing the time required to just 30 to 60 minutes. Currently, the creation of such vaccines takes much longer due to the reliance on traditional matrix methods for mathematical calculations related to mRNA vaccine design.
“At present, developing a personalized vaccine takes a considerable amount of time because the calculations for how the vaccine should look—specifically, the personalized mRNA—are done using matrix methods,” Gintsburg explained. “We are collaborating with the Ivannikov Institute, which will transition this mathematical work to artificial intelligence, specifically neural network computing, where these procedures should take about half an hour to an hour.”
Gintsburg also highlighted the need to establish an experimental database containing approximately 40,000 to 50,000 tumor samples with identified antigen compatibilities. This data will help train AI to determine whether specific combinations can be used for individual patients.
