BullFrog AI Holdings has announced a partnership agreement with Eleison Pharmaceuticals to apply its artificial intelligence (AI) solutions to Eleison’s pivotal Phase III trial of pancreatic cancer treatment, glufosfamide.
Leveraging its Data Networks AI solution, supported by the bfLEAP platform, BullFrog AI will ‘analyse’ clinical data from Eleison’s ongoing Phase III trial and prior studies involving the therapy.
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According to the terms of the agreement, BullFrog AI will offer access to its AI solution to improve trial efficiency and patient outcomes.
The AI platform will assess safety signals, identify predictive biomarkers, and offer data-driven insights for enhancing Eleison’s inhaled lipid-complexed cisplatin (ILC) and dibromodulcitol (DBD) planned trials.
Eleison anticipates the completion of the ongoing Phase III trial by 2027.
Eleison Pharmaceuticals CEO Edwin Thomas said: “Our collaboration with BullFrog AI underscores our commitment to innovation in drug development.
“By leveraging AI-powered analytics, we aim to generate deeper insights into patient responses and safety trends, which will not only benefit our glufosfamide program but also inform the strategic direction of our broader oncology pipeline.”
A third-generation alkylating agent, glufosfamide, which is designed for ‘greater’ specificity and tumour uptake, is under assessment in an international, randomised trial for second-line treatment of pancreatic cancer patients.
BullFrog AI CEO Vin Singh said: “The integration of AI in clinical trials represents a transformative shift in how pharmaceutical companies can de-risk drug development and optimise patient outcomes.
“We are thrilled to partner with Eleison to apply our bfLEAPAI technology, which has the potential to refine patient selection, improve trial efficiency, and ultimately accelerate the path to market for life-saving therapies.”
The partnership’s financial terms remain undisclosed.
BullFrog AI uses machine learning for progressing the development and discovery of drugs. The company partners with research institutions to use causal AI and its bfLEAP platform to analyse complex biological data, aiming to decrease failure rates and expedite therapeutics development.
