CAMBRIDGE — MIT researchers developed a new formulation for lipid nanoparticles that allows RNA vaccines to remain stable at room temperature for up to one year. The research paper detailing this advancement was published in Nature Biotechnology on September 28, 2026.

RNA vaccines using the new lipid nanoparticle formulation can withstand temperatures near 100 degrees Fahrenheit (37 degrees Celsius) for two months without degradation. In contrast, conventional RNA-lipid nanoparticle vaccines must be stored between -20 and -80 degrees Celsius. To assess heat resistance, the team applied vacuum drying to dehydrate the lipid nanoparticles prior to testing.

An artificial intelligence algorithm was employed to determine the most effective ratios of excipients for stabilizing the nanoparticles. By analyzing nearly 50 FDA-approved excipients, the AI model narrowed the field to five promising candidates and predicted their optimal combinations. This approach significantly reduced the number of physical experiments needed, enabling the team to complete the development process in just several weeks.

The efficacy of each excipient combination was evaluated by delivering mRNA encoding firefly luciferase into cells and measuring resulting bioluminescence. In animal trials, mice inoculated with the heat-stable formulation mounted immune responses comparable to those elicited by vaccines containing original Moderna-like lipid nanoparticles. Typically, only about 5-10% of mRNA in standard vaccines successfully reaches target cells.

Jinbi Tian is a graduate student and lead author of the paper. Khanh Tran is a postdoc and lead author of the paper. Ana Jaklenec is a principal investigator in MIT’s Koch Institute for Integrative Cancer Research and a senior author of the paper.

Robert Langer is the David H. Koch Institute Professor at MIT and a senior author of the paper. Mina Konaković Luković is an assistant professor of electrical engineering and computer science in MIT’s Computer Science and Artificial Intelligence Laboratory and an author of the paper.

"The real beauty of this algorithm is that we can use it with small data sets," Ana Jaklenec said. "It’s really hard to run thousands of experiments, so this algorithm allows us to more easily achieve formulations with features that we want — in this case, stability."

Mina Konaković Luković noted the novelty of applying their computational tools to this specific challenge. "We’d used our algorithms for various automated experimental design applications before, but never on a biological problem like vaccine stability," she said. "It was surprising to see how quickly the algorithm converged on a stable formulation — getting there in just a handful of iterations, rather than the exhaustive search that would normally be required."

Why It Matters

This innovation tackles the logistical challenges associated with cold-chain storage, which for current RNA vaccines demands freezing conditions from -20 to -80 degrees Celsius. With the ability to remain stable at room temperature for as long as a year while maintaining immunological effectiveness, the new formulation could greatly enhance global vaccine accessibility. Additionally, the rapid development timeline made possible by the AI-driven method sets a precedent for accelerating the optimization of future biomedical therapeutics.