29 September 2023 | Friday | News
Image Source : Public Domain
HitGen will utilize its DNA-encoded library (DEL) technology platform, specifically OpenDEL™, to screen under-represented targets chosen by SGC. The screening datasets, curated in a ML-ready format, will be posted to a publicly accessible portal to facilitate drug discovery and ML experts from around the world to model the data and make predictions about new active molecules that would be experimentally tested at SGC as part of the Target 2035 initiative.
HitGen is a world leader in the development of DEL technology and applications to early-stage small molecule drug discovery. Its platform includes over 1.2 trillion small molecules generated by the DEL technology, and the efficiency of the screening process has made it possible for HitGen to enable drug discovery projects for many organizations around the world.
OpenDEL™ is a self-service DEL kit with over 3 billion compounds, which enables users to explore DEL selection campaigns without revealing the target identity. Under the guidance of the manual and operating instructions, users can utilize OpenDEL™ to conduct affinity screening experiments against protein targets in their own laboratories. HitGen can provide upstream and downstream technical support.
"We look forward to working with the research teams at SGC to generate novel starting points for under-studied proteins and to place ML-ready representations of the data into the public domain on an open access basis. As one of HitGen's four core technology platforms, our world-leading DEL platform is an efficient 'engine' to advance drug discovery and has enabled hit identification and lead generation for many innovative discovery programs by our customers and partners. We look forward to delivering useful starting points for targets chosen by SGC," said Dr. Jin Li, Chairman of the Board and Chief Executive Officer of HitGen Inc.
"I am confident that this partnership has the potential to be transformative," said Aled Edwards, Chief Executive of the SGC, "We look forward to providing the ML community with high-quality, well-curated data so they can contribute to our global effort to find drug starting points for all human proteins."