Unlearn and Structure Therapeutics Collaborate to Apply AI-Generated Digital Twins in Obesity Research

By ACCESS Newswire

SAN FRANCISCO, CA / ACCESS Newswire / November 12, 2026 / Unlearn today announced a collaboration with Structure Therapeutics Inc., a clinical-stage biopharmaceutical company developing oral small molecule therapeutics for metabolic diseases, with a focus on chronic weight management, to explore the application of AI-generated digital twins in obesity research. The collaboration will analyze existing data from Structure's completed ACCESS open-label extension (OLE) study of aleniglipron, an investigational, once-daily, orally available small molecule agonist of the glucagon-like peptide-1 (GLP-1) receptor.

Using anonymized patient data collected in the completed OLE study, the retrospective analysis will use Unlearn's AI-based modeling to estimate what participant outcomes might have been without the investigational treatment. Unlearn refers to these model-generated estimates as "digital twins." Comparing AI-based estimates with an observed study outcome may provide additional context for interpreting a study's longer-term findings.

"This collaboration is an opportunity to explore how AI-generated digital twins can support the interpretation of longer-term obesity study data," said Steve Herne, CEO of Unlearn. "By comparing model-generated estimates with observed outcomes, we aim to explore how this approach may contribute to obesity research."

"We appreciate Unlearn's interest in the ACCESS OLE findings and its efforts to further explore the data," said Blai Coll, M.D., Ph.D., Chief Medical Officer of Structure Therapeutics. "While separate from our clinical development program, this analysis may provide additional context for our comprehensive evaluation of the clinical profile of aleniglipron."

Data from Unlearn's analysis will be included in a poster titled "Aleniglipron in Participants Living with Overweight or Obesity: ACCESS Trial Open-Label Extension" to be presented at ObesityWeek, The Obesity Society's annual meeting, November 14-17, 2026, in National Harbor, Maryland.

About Unlearn

Unlearn exists to transform clinical development by making every trial smarter. Partnering with pharmaceutical and biotechnology companies, Unlearn harnesses data, AI, and digital twins to enable faster, more robust studies and clearer decision-making across clinical development. With a science-first approach and deep regulatory engagement-including EMA qualification and FDA support-Unlearn brings unmatched scientific credibility to applying AI in clinical trials.

For more information, visit www.unlearn.ai or follow us on LinkedIn and X/Twitter.

Media Contacts:

Heather D'Angelo, Unlearn
heather@unlearn.ai

SOURCE: Unlearn AI



View the original press release on ACCESS Newswire

Capital.com is an execution-only brokerage platform and the content provided on the Capital.com website is intended for informational purposes only and should not be regarded as an offer to sell or a solicitation of an offer to buy the products or securities to which it applies. No representation or warranty is given as to the accuracy or completeness of the information provided.

The information provided does not constitute investment advice nor take into account the individual financial circumstances or objectives of any investor. Any information that may be provided relating to past performance is not a reliable indicator of future results or performance.

To the extent permitted by law, in no event shall Capital.com (or any affiliate or employee) have any liability for any loss arising from the use of the information provided. Any person acting on the information does so entirely at their own risk.

Any information which could be construed as “investment research” has not been prepared in accordance with legal requirements designed to promote the independence of investment research and as such is considered to be a marketing communication.