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PFI-TT: Platform Technology for Bioengineering Applications of Large mRNA

$266,000FY2023TIPNSF

University Of Connecticut, Storrs CT

Investigators

Abstract

The broader impact/commercial potential of this Partnerships for Innovation - Technology Translation (PFI-TT) project will introduce an innovative and more effective option to help large mRNA enter cartilage and joint tissues for a variety of biomedical applications from therapeutics to research reagents. With the recent success of COVID-19 vaccines, mRNA-based vaccines and therapeutics have attracted substantial interest from both academia and the biopharmaceutical industry. However, the delivery of large mRNA is still a major challenge. The proposed platform technology presents many advantages over conventional delivery vehicles. PhD students and undergraduates will receive training in technology development and commercialization. The proposed project will develop a delivery technology based on the innovative DNA-inspired Janus base nanomaterials (JBNs) for large mRNA that addresses a critical market need for applications in “difficult-to-penetrate” cartilage tissue for joint and skeletal diseases. The delivery of large mRNA is still a major challenge. The proposed platform technology presents many advantages over conventional delivery vehicles such as lipid nanoparticles and polymers. This new technology has superior ability to penetrate into cartilage and other joint tissues, has significantly better endosomal escape ability than lipid nanoparticles, and has significant lower cytotoxicity compared to cationic polymers and lipids due to their noncovalent structures and DNA-mimicking chemistry. Furthermore, this new delivery technology has tremendous versatility. Depending on the specific needs of a customer, the technology can be tailored for different joint and skeletal diseases. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

View original record on NSF Award Search →