Cantex and Headlamp Health partner on azeliragon for multiple sclerosis depression and fatigue

Cantex Pharmaceuticals (Weston, Fla.) and Headlamp Health (San Francisco) announced a collaboration to apply Headlamp’s Lumos AI platform to the clinical development of azeliragon for depression and fatigue in patients with multiple sclerosis, with Headlamp deploying its patient-stratification technology across Cantex’s existing azeliragon program data. The partnership arrangement adds an AI-driven phenotyping layer to a drug candidate that Cantex has been advancing across multiple indications since licensing worldwide rights from vTv Therapeutics in 2021.

Azeliragon is an orally administered, once-daily capsule and the only blood-brain barrier-penetrant RAGE inhibitor — targeting the receptor for advanced glycation endproducts — currently in clinical development. Originally developed by vTv Therapeutics for Alzheimer’s disease, azeliragon was licensed by Cantex to pursue new therapeutic indications. The compound inhibits RAGE interactions with ligands including HMGB1 and S100 proteins. In the MS context, RAGE is expressed on microglia, astrocytes, endothelial cells, and infiltrating immune cells in the brain, where activation amplifies neuroinflammatory signaling. Cantex is positioning azeliragon’s anti-neuroinflammatory mechanism as distinct from existing pharmacologic options for MS-related depression and fatigue, which include SSRIs and SNRIs that do not address inflammatory pathways. Clinical safety data from prior trials involving more than 2,000 individuals dosed for periods of up to 18 months indicate the compound is well tolerated, according to the company.

The target population is substantial. Cantex cites that approximately 40% of patients with progressive MS have clinically significant depression, while fatigue affects 60% to 80% of MS patients over the course of the disease. Both symptom domains are described by the company as pharmacologically underserved, with current treatment options showing limited efficacy beyond placebo.

The Lumos AI platform and phenotyping approach

Headlamp Health’s Lumos AI platform is described by the company as a neuro-symbolic, multi-agent system built for neuropsychiatric drug development. The platform integrates biological, behavioral, biomarker, and clinical data into a unified analytical layer, drawing on a proprietary dataset of more than 100 million longitudinal multi-modal data points. In the context of the Cantex Headlamp partnership azeliragon program, Headlamp will deploy Lumos AI to analyze the full body of data generated across azeliragon’s development history, with the goal of delineating distinct responder and non-responder patient phenotypes.

The AllSci BriefSystematic R&D and deal news. Daily.

The phenotyping approach is intended to move trial design beyond population-level assumptions by identifying multifactorial biomarker signatures that episodic data alone cannot capture. For azeliragon multiple sclerosis development, this means modeling patient trajectories and identifying which subgroups within the MS depression and fatigue population are most likely to benefit from RAGE inhibition. Headlamp states the platform has been validated through active pharmaceutical partnerships and is currently supporting more than 150,000 patients, though no peer-reviewed publication or independent technical validation was cited in the announcement.

The collaboration with Headlamp Health is the latest in a series of transactions Cantex has executed around azeliragon since acquiring worldwide rights from vTv Therapeutics in June 2021. In June 2023, Cantex obtained an exclusive worldwide license from Georgetown University covering intellectual property related to azeliragon as a potential treatment for cancer treatment-related cognitive decline. In October 2023, Cantex partnered with Allegheny Health Network to initiate a Phase 1/2 study of azeliragon in patients with metastatic pancreatic cancer refractory to first-line treatment.


This article was generated with AI assistance and reviewed and edited by the AllSci editorial team Explore more at AllSci News: https://allsci.com/news/