Scripps to collaborate with Pfizer to advance DNA-encoded library technology

Share on facebook
Share on twitter
Share on linkedin
Share on email
Share on print

The Scripps Research Institute announced a research collaboration and license agreement with Pfizer Inc. to pioneer new DNA-encoded library technology, including new synthetic chemistry for the creation of next-generation DELs, a potentially transformative technology for early stage drug discovery research.

Under the collaboration, Pfizer will pay a technology access fee and thereby gain access to innovative chemical synthesis technology developed at TSRI.

Members of the TSRI chemistry department—Professors Phil Baran, Dale Boger, Jin-Quan Yu, K. Barry Sharpless, and others—will work alongside Pfizer scientists to adapt these chemical methods for use in creating DELs, which require stringent processes that are tolerant of the delicate DNA backbone.

TSRI and Pfizer may choose to expand the scope of the joint research to include other technologies relevant for enabling DEL-based drug discovery. Financial terms of the agreement are not disclosed.

In contrast to conventional drug screening where a few million small molecules are evaluated in biological systems, DEL screening uses DNA-based “barcodes” to survey billions of small molecules, potentially increasing the ability of researchers to identify promising chemical leads.

While this technology was originally conceived at TSRI by Richard Lerner and Sydney Brenner in the early 1990s, the reduction to practice has taken decades and required technological advances in DNA sequencing and informatics in order to be more fully realized.

Table of Contents

YOU MAY BE INTERESTED IN

When our hematological malignancy testing pilot project began in Eldoret, Kenya, there seemed to be a mismatch in relation to progress in healthcare. The region, like much of sub-Saharan Africa, had been focusing on combatting infectious diseases such as HIV and malaria—which was much-needed—yet cancer care was under-resourced. 
Artificial intelligence is rapidly transforming biomedical research and healthcare. Large language models, foundation models, and AI agents are increasingly being deployed to assist with data interpretation, literature review, clinical decision support, and translational research. 
In modern oncology, important insights from clinical trials often emerge years after initial publication. As new therapies extend survival and transition more patients into long-term remissions, clinicians and researchers are increasingly looking beyond initial response rates to understand durability, long-term safety, and even the possibility of a cure. 

Never miss an issue!

Get alerts for our award-winning coverage in your inbox.

Login