£7.5M Prize Backs AI to Crack ALS Drug Target Problem

ALS — amyotrophic lateral sclerosis — remains one of medicine's most stubborn problems. It is progressive, fatal, and biologically diverse, meaning it behaves differently across patients, which is why so many drugs have failed in trials. The Longitude Prize on ALS is a structured attempt to change that, placing £7.5 million behind a new approach that combines artificial intelligence with large-scale human biological data.

Twenty teams have received Discovery Awards totaling £2 million in the prize's first phase. Selected from nearly 100 applicants, these teams span over 70 organizations across 12 countries, blending academic researchers, pharmaceutical companies, and technology firms. Crucially, each team gains access to a rare, harmonized dataset integrating genomic, transcriptomic, proteomic, and clinical information from thousands of ALS patients — the kind of resource that has historically been fragmented and inaccessible.

The prize targets the upstream bottleneck in drug development: identifying which biological targets are genuinely worth pursuing. This is where ALS research has historically collapsed. By focusing competitive funding here — before expensive clinical trials begin — the structure is designed to filter out weak hypotheses early and strengthen the pipeline at its most vulnerable point.

The competition runs in phases. Ten teams will advance in 2027 for deeper development, a smaller group will move to experimental validation, and a final £1 million prize will be awarded in 2031. This staged model mirrors the attrition curve of drug discovery itself, rewarding durability over early promise.

Experts urge measured expectations. Multi-omics integration and AI pattern recognition are powerful tools, but they do not automatically reveal causation. Still, if even partial success emerges — if ALS begins to stratify into subtypes with actionable targets — it would validate a more granular, data-driven approach to neurodegenerative and aging diseases broadly, with implications well beyond ALS itself.