Artelo Biosciences
SOLANA BEACH, Calif., April 28, 2026 (GLOBE NEWSWIRE) — Artelo Biosciences, Inc. (Nasdaq: ARTL), a clinical-stage pharmaceutical company focused on modulating lipid-signaling pathways to develop treatments for people living with cancer, pain, dermatological, or neurological conditions, today announced details of a strategic partnership with BioAI company ScienceMachine to accelerate the development of its fatty acid-binding protein 5 (FABP5) inhibitor platform. ScienceMachine’s platform, which leverages cutting-edge AI agent technology, is built to interrogate large biological datasets in a fraction of the time and cost of traditional methods.
The partnership is harnessing ScienceMachine’s proprietary AI technology to analyze Artelo’s large internal FABP datasets and identify novel biological insights, including new mechanisms and therapeutic opportunities for FABP5 inhibitors, particularly ART26.12, the Company’s first FABP5 inhibitor to begin clinical studies. By using data from the previously reported Phase 1 single ascending dose study (ART26.12-100), ScienceMachine has been instrumental in identifying potential proteins indicative of FABP5 target engagement in ART26.12-treated healthy volunteers.
“This collaboration expands our pipeline potential and enhances our R&D precision,” said Andrew Yates, Ph.D., Senior Vice President and Chief Scientific Officer at Artelo. “We believe this partnership has the potential to accelerate the identification of novel mechanisms of action and clinical biomarkers, as well as prioritizing follow-on compounds from our FABP5 library with greater confidence and speed. In short, it’s a powerful force multiplier for our drug development strategy, enabling smarter investment of resources and potentially shortening our path to value creation.”
Since the start of the collaboration in 2025, the partnership has used the power of machine learning to interrogate disease-model multi-omic data. These efforts have revealed latent biological networks associated with disease severity and FABP signaling, while providing mechanistic insight into these novel targets. Preliminary results, conducted in a psoriasis model, are slated for publication later this year. In addition, the collaboration identified novel protein and lipid signatures correlated with ART26.12’s dose responsive analgesic effect. These results are providing insight into the design of future research with ART26.12 and other FABP inhibitors from Artelo’s library.
“Our work with Artelo’s data shows how AI agents can augment modern drug discovery and development,” said Lorenzo Sani, CEO and co-founder of ScienceMachine. “Together with Artelo, we are turning complex biological datasets into testable hypotheses that may help inform biomarker strategy, mechanism-of-action work, and future FABP5 inhibitor development.”
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