GAITHERSBURG, Md., Jan. 06, 2026 (GLOBE NEWSWIRE) — BullFrog AI Holdings, Inc. (NASDAQ: BFRG; BFRGW) (“BullFrog AI” or the “Company”), a technology company using artificial intelligence (“AI”) and machine learning to turn complex biomedical data into actionable insights, highlights the presentation of data derived from the use of the Company’s proprietary platform bfLEAP® with pancreatic cancer trial data to identify an almost three times increase in mean survival from the control to treatment arms. The data will be presented at the 2026 American Society of Clinical Oncology Gastrointestinal Cancers Symposium (ASCO GI) on Jan. 9 at poster session B.
The presentation, in collaboration with Eleison Pharmaceuticals and the Moffitt Cancer Center, is titled, “Data-driven subtyping and differential glufosfamide benefit in pancreatic adenocarcinoma,” and will subsequently appear in the Journal of Clinical Oncology (JCO) supplement corresponding to the symposium.
“The glufosfamide case study in pancreatic cancer successfully showcased the utility of our platform to provide drug developers with an end-to-end analytical tool engineered to resolve multimodal biological complexity at scale,” said BullFrog AI Founder and CEO Vin Singh. “Too much time and capital are wasted in drug development traveling down incorrect pathways, ultimately leaving patients without effective treatments. The power of bfLEAP® and bfPREP™ is their ability to give drug developers a clear path forward based on previous data and indicators to focus on key benchmarks, limiting the amount of wasteful spending on less-than-ideal targets.”
The study explored data-driven precision-oncology approaches leveraging BullFrog AI’s bfLEAP® and bfPREP™ platforms to analyze complex clinical datasets, uncover biologically meaningful patient clusters, and identify patient subtypes that may demonstrate enhanced response to glufosfamide, an investigational chemotherapeutic agent for pancreatic cancer. In the post-hoc analysis of TH-CR-302, a randomized phase 3 clinical trial evaluating glufosfamide against the best supportive care (BSC), the analysis discovered key biomarkers that influenced an almost threefold increase in mean survival from the control to treatment arms.
The research group concluded that ensemble approaches like bfLEAP® can successfully identify patient subgroups within existing glufosfamide clinical trial data. Treatment effect heterogeneity was identified among clusters, identifying possible early predictors of outcomes, and highlighting the effectiveness of data-driven clustering approaches to refine patient stratification and guide the development of personalized treatment strategies.
The study was co-authored by Richard Kim, M.D., Service Chief of Medical Gastrointestinal Oncology and Senior Member in the Gastrointestinal Oncology Department at Moffitt Cancer Center, Nikolas Naleid, M.D., Pharm.D., Hematology/Oncology Fellow at Moffitt Cancer Center, Eleison Pharmaceuticals, and BullFrog AI.
About BullFrog AI
BullFrog AI leverages artificial intelligence and machine learning to advance drug discovery and development. Through collaborations with leading research institutions, BullFrog AI uses causal AI in combination with its proprietary bfLEAP® platform to analyze complex biological data, aiming to streamline therapeutics development and reduce failure rates in clinical trials. For more information visit BullFrog AI at: https://bullfrogai.com.
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