Avalon GloboCare Advances AI-Enhanced Protein Design Technology For Cellular Therapy Development

Avalon and research partner, Massachusetts Institute of Technology (MIT), combine their protein design “QTY Code” technology with Google’s DeepMind artificial intelligence (AI) program, AlphaFold2, to accurately predict the 3D structures of protein receptors that have potential use as cellular therapy targets

A study of the application and capabilities of the dual technology was published in the November 2021 issue of Life, a peer-reviewed life sciences journal

Avalon GloboCare Corp. a clinical-stage global developer of cell-based technologies and therapeutics, announced further advancement of the Company’s sponsored research and licensing agreement with the Massachusetts Institute of Technology (MIT). Avalon and MIT have combined their artificial intelligence (AI)-enhanced protein design “QTY Code” technology with Google’s AlphaFold2, a DeepMind AI program developed to predict 3-dimensional (3D) protein structures of previously difficult to work with drug targets. This new system is designed to accelerate and advance Avalon’s capabilities in developing novel targets for immuno-oncology and cellular medicine.

Recommended AI News: Geojam’s $JAM Token Lifts Off from Lattice Launchpad after $5.9 Million Private Sale

The “QTY Code” breakthrough technology, developed by Avalon and the laboratory of Dr. Shuguang Zhang, Ph.D., of MIT’s Media lab in Boston, MA, is a protein-design platform that can turn water-insoluble transmembrane receptor proteins into water-soluble proteins, enabling their use in many clinical applications, including drug development.   This program has already successfully generated a series of decoy receptors, which function to soak up excess chemokines and cytokines produced in the body during a potentially fatal ‘cytokine storm.’ These cytokine storms can occur in patients with COVID-19 and in cancer patients being treated with CAR T-cell therapy.

The newly published study demonstrated the utility and efficiency of combining the two AI-based technologies. The researchers used the QTY code technology to design water-soluble versions of chemokine receptors—water-insoluble proteins involved in cytokine storms, cancer, autoimmune diseases and important drug targets—and then used AlphaFold to accurately predict the structures of these clinically important proteins.

Recommended AI News: YipitData Raises up to $475 million in Series E Funding from Carlyle

Combining the “QTY code” with AlphaFold2, provides Avalon with a novel, accurate, and efficient in-silico tool to improve knowledge about important potential therapeutic targets such as transmembrane receptors and other proteins to better understand their biology and facilitate the development of novel cellular therapies.

“This new study with our collaborator, Dr. Shuguang Zhang from MIT, has validated the innovative application of the QTY code technology to transform important cellular therapy targets that have been previously difficult to work with in the laboratory,” said David Jin, M.D., Ph.D., President and Chief Executive Officer of Avalon. “This new approach is advancing our capabilities in designing novel immuno-oncology and cellular medicine therapies and we are excited to continue to work with Dr. Zhang to advance these drug development technologies,” added Dr. Jin.

The study of the new dual technology application was published in the November 2021 issue of Life, an international, peer-reviewed, open-access life sciences journal.

Recommended AI News: Oasis Announces Exclusive Partnership with Venio Systems

[To share your insights with us, please write to sghosh@martechseries.com]