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MIT researchers utilized an AI algorithm to optimize lipid nanoparticle formulations, enabling RNA vaccines to remain stable at room temperature for up to a year. This application of machine learning significantly reduced the experimental iterations required to achieve thermal stability, addressing a critical logistical barrier for mRNA therapies like cancer vaccines. The study demonstrates how AI can accelerate biotech development by predicting optimal material properties from limited data sets.
New formulation helps RNA vaccines withstand high temperatures
MIT engineers have found a way to stabilize the lipid nanoparticles used to deliver RNA vaccines, which could allow the vaccines to be more widely distributed.
RNA vaccines, which have been proven effective against Covid-19, are now being developed for many other diseases, including cancer. One of the drawbacks to these vaccines is that they require ultracold storage, but researchers from MIT have found a promising way to overcome that limitation. With help from an AI algorithm, the researchers tweaked the formulation surrounding the lipid nanoparticles that are typically used to deliver mRNA vaccines, making the vaccines more heat-resistant. Using this approach, they formulated vaccines that could remain stable even when stored at room temperature for up to a year, or at nearly 100 degrees Fahrenheit for two months. When Covid-19 vaccines…
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