Texas A&M researchers developing mRNA vaccine platform to boost temperature resistance
COLLEGE STATION, Texas (KBTX) - A team of researchers at Texas A&M are developing a new mRNA vaccine platform in hopes of making them more thermostable and less reliant on extremely low temperatures for storage.
Medical experts say the mRNA vaccines developed by Pfizer and Moderna have been revolutionary in how quickly and effectively they’ve helped us fight the COVID-19 pandemic. But one of the major drawbacks is the below freezing temperatures in which they must be manufactured and stored to preserve them.
The intensely cold temperatures mRNA vaccines need to preserve their effectiveness hinder their use in rural areas and the developing world, places that sometimes don’t have the capabilities to make that possible. It’s one reason why Texas A&M Chemical Engineering Assistant Professor Qing Sun and her team, which includes seven other faculty members from across campus, are developing a new vaccine platform to change that.
“The overarching goal of our project is to develop thermostable and highly efficient mRNA vaccines that will be easier to be stored and distributed, and more highly efficient in the human body,” Sun said.
The vaccines need the ultra cold temperatures to preserve the RNA sequencing that instructs the body how to attack the virus. Sun’s platform will take data from pre-existing mRNA vaccines and use machine deep learning to predict new RNA sequences that are more resistant to higher temperatures.
“We’re not changing the protein sequence. We’re just changing the mRNA sequence, so in the end, the final product is the same,” Sun said. “Our product will be more stable, and our hypothesis is that they are going to be more efficient.”
With the help from a $1.3 million Texas A&M X-Grant, Sun’s team will be able to rapidly create new vaccine prototypes with those new mRNA sequences. She says they can be developed in their lab in about one to two days and will be injected into mice to test their effectiveness.
“We are going to compare our product with their product, and we believe it’s going to be more stable,” Sun said. “We hope we can store it at room temperature, but this really depends on how far we can go and what our final results are. Our goal is to produce more stable ones at room temperature, but we’re not sure yet.”
Sun says her team has already collected data sets from various universities across the country. The data they collect from their own prototypes they test in their lab will be fed back into the platform, which will make their deep learning model even more precise in predicting mRNA sequence stability.
“This deep learning model is brand new, so it’s very efficient in its predictions,” Sun said. “Before, the traditional model was low efficiency, and the results were not as good as ours. Our platform is novel, and it’s efficient enough to predict the longer RNA sequences.”
Their work will initially focus on the COVID-19 mRNA vaccines, but Sun says they also hope to test other mRNA vaccines that work against other infectious diseases, viruses, and even cancers. Their platform is universal, meaning that if it’s successful, anyone can use it to redesign their mRNA vaccine with the same efficacy but a higher level of stability.
“There are many ongoing efforts to develop mRNA vaccines towards cancers, including breast cancer, colon cancer, and skin cancer. A lot of them are under clinical trials,” Sun said. “We have many other candidates that we want to test, including ones towards other infectious diseases, like Zika, Ebola, and the flu.”
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