4D Molecular Therapeutics Collaborates with Leading Machine Learning Technology Experts

The partnership with Drs. Listgarten and Schaffer empower 4DMT to expand its bioinformatics capabilities, enabling it to find promising vectors both within and beyond existing libraries.

FREMONT, CA: 4D Molecular Therapeutics, a clinical-stage gene therapy firm harnessing the power of directed evolution for targeted gene therapies, collaborates with investigators at the University of California, Berkeley focused on widening the vector invention power of 4DMTs Therapeutic Vector Evolution platform by applying machine learning to the AAV vector capsid datasets created from 4DMTs platform. This research will be performed with Jennifer Listgarten, Ph.D., a leader in machine learning and computational biology, and David Schaffer, Ph.D., a global leader in AAV-directed evolution and gene therapy.

This cross-functional partnership with world leaders in machine learning and AAV gene therapy technologies offers the potential to dramatically expand the depth and breadth of targeted and evolved vectors invented through the Therapeutic Vector Evolution platform, expanding the company’s vector patent and product portfolios. 4DMTs industry-leading AAV capsid libraries encompass over one billion synthetic capsid sequences. 

The company has the largest capsid biodistribution datasets in the world due to the over 15 vector selection programs conducted in non-human primates. This partnership reaffirms its commitment to relentless innovation to bring cures to patients.

Therapeutic Vector Evolution combines the power of directed evolution with approximately one billion synthetic capsid sequences to find evolved vectors for use in targeted gene therapy products. Using its proprietary Therapeutic Vector Evolution platform, to date, 4DMT has produced an industry-leading 40 distinct capsid libraries, conducted more than 15 vector selections in non-human primates, and has filed patent applications on over 300 new AAV vectors. The application of machine learning to 4DMTs Therapeutic Vector Evolution and its datasets illustrates an opportunity to enable technology to invent new vectors for targeted gene therapy products.