MIT researchers have created a novel technique that uses artificial intelligence to create nanoparticles that can more effectively distribute RNA vaccines and other RNA-based therapies.
The researchers created a machine-learning model to evaluate thousands of delivery particles now in use in order to forecast novel materials that will perform even better. Additionally, the model helped the researchers determine how to incorporate new sorts of elements into the particles and identify particles that would work well in different types of cells. “Exactly what we did was use machine-learning tools to help improve the identification of effective ingredient compounds in lipid nanoparticles to help target a different cell type or help include various compounds, more quickly than historically was possible,” says Giovanni Traverso, an associate professor of mechanical engineering at MIT and gastroenterologist at Brigham and Women’s Hospital.
According to the researchers, this approach could greatly speed up the creation of innovative RNA vaccines and therapies for metabolic illnesses including diabetes and obesity. The lead authors of the new open-access work, the publication of Nature Nanotechnology, are Ameya Kirtane, an assistant professor at the University of Minnesota, and Alvin Chan, a former MIT postdoc who is currently an assistant professor at Nanyang Technological University. The method of giving RNA vaccines as lipid nanoparticles (LNPs) is similar to the SARS-CoV-2 vaccinations. After injection, these particles facilitate mRNA’s entrance into
