[BioEscalator] Congratulations on being selected as an award winner! What can you tell us about the Longitude Prize on ALS and what this enables?
We are honoured to announce that Entelo Bio have officially been named one of the 20 Discovery Award winners in the Longitude Prize on ALS, a £7.5 million global challenge prize. Following a global call to action, our ALS/SPLICE team, in partnership with the University of Sydney, was chosen from almost 100 entries to receive £100,000. We are proud to be part of a winning cohort that represents over 70 organisations across 12 countries. The Longitude Prize on ALS is supported by the leading ALS charities, patient and impact groups, plus other funders. The MND Association is the principal funder with Nesta, the Alan Davidson Foundation, My Name’5 Doddie Foundation, LifeArc, FightMND, The 10,000 Brains Project, Answer ALS and The Packard Center at Johns Hopkins University also involved.
Beyond the financial award, we have gained access to the most comprehensive ALS patient dataset ever compiled, featuring genomic sequences of 9,000 patients and epigenomics, transcriptomics, and proteomics data for over 2,000 cases. We will be enriching this data with our own proprietary isoform datasets to create isoform aware machine learning and foundational models for drug target discovery
[BioEscalator] What does this enable Entelo Bio to do, and why did you decide to enter this competition?
Entelo Bio was spun out of Oxford's Botnar Institute for Musculoskeletal Sciences (NDORMS) on the strength of our isoform-driven omics and machine learning work in chronic disease. The ALS Prize was a natural fit; it sits right at the intersection of our two core capabilities: working in structurally complex tissues to generate insights not seen via other methods, and our expertise in biological machine learning. The one thing we didn't have was ALS disease biology expertise, which is why partnering with the team at the University of Sydney made so much sense. The collaboration also lets us stress-test our model architectures against large existing ALS datasets and generate new proprietary data through access to patient biospecimens, all on an internal infrastructure we already have in place.
[BioEscalator] How does this tie into the plans for Entelo Bio?
We're entering an era of therapeutic abundance, where small AI-native teams, such as Entelo Bio, can win.
What constrains us isn't the molecules anymore, it's our understanding of biology, and specifically of causality within human physiological systems. That's an extraordinarily hard thing to model from an AI perspective and to build the systems to solve it from an operational one. But if we can solve it, with the right substrate, the right data abstractions, the right disease models to validate AI outputs, then the next generation of frontier AI gives us a realistic path to reducing clinical failure rates and developing cures in diseases that currently have none. AI is the connective tissue across all of it.
At Entelo Bio, we’ve built the Frontier Systems Company for Human Physical Resilience, and this remains our core focus both from an internal and external perspective. ALS and other neuromuscular indications are how we extend that capability into spaces where the unmet need is acute and where we think there will be rich fishing grounds for dial moving insights. Same generalisable platform capabilities, pointed at a different problem.
[BioEscalator] Which milestones will the data from the ALS/SPLICE project help you reach?
The Entelo platform was designed to be tissue-agnostic. We started in human physical resilience because that's where our expertise is deepest, and because we think it’s the greatest challenge facing humanity today, but there’s nothing to say we couldn’t apply our capabilities elsewhere.
The prize accelerates us on several fronts. ALS is our first proof point that the platform travels — and the data this collaboration generates feeds directly back into improving our AI models and extending the isoform platform into new disease areas, in-house and with partners. Access to some of the largest ALS datasets in the world lets us stress-test our model architectures at scale on data we didn't generate ourselves, while opening up new proprietary data through patient biospecimens.
We've already started conversations with several of the largest groups in neuromuscular disease off the back of the prize, and the response has given us real confidence that our approach can deliver near-term impact in spaces where almost nothing else is working.
[BioEscalator] What tips do you have for teams entering prestigious and competitive competitions like the Longitude Prize for ALS?
Just apply, but really lean into what you are good at. We are great at insights discovery, especially beyond simple gene expression, but we aren’t a traditional run-of-the-mill drug company, nor are we expert ALS disease biologists. We partnered where we were weak and doubled down where we are strong, and I think this makes for a much more compelling proposition vs trying to be everything (insights, drug discovery, etc.)