AI-driven project aims to identify drug targets in ALS subtypes – and enable new treatments
The Longitude Prize was created to accelerate the discovery of treatments for amyotrophic lateral sclerosis (ALS), a devastating and currently incurable neurodegenerative disease.
Researchers from the University of Melbourne’s School of Biomedical Sciences have secured international funding to accelerate the search for new treatments for amyotrophic lateral sclerosis (ALS), a devastating neurodegenerative disease with few effective therapies.
Associate Professor Michael P. Menden, Professor Danny Hatters and Professor Peter Crack (Department of Biochemistry and Pharmacology) are leading the Australian contribution to a global research effort, working with international collaborators across Europe and industry partners.
Their team is part of the TUM ALIGN ALS consortium, which has just been awarded the Longitude Prize on ALS, worth £100,000 (A$189,000). Beyond funding, the prize provides access to critical datasets and computational resources, enabling faster and more powerful analysis of ALS biology.
ALS, the most common form of Motor Neurone Disease, destroys motor neurons in the brain and spinal cord, leading to progressive paralysis. Most patients survive only three to five years after diagnosis, and treatment options remain extremely limited.
The project will develop advanced artificial intelligence models to identify new drug targets across different forms of ALS, with the aim of enabling more effective and personalised treatments. The consortium is one of 20 international teams competing in a multi-stage process that will ultimately identify a single winner, while building a global network to accelerate progress against the disease.
The research will analyse large-scale genomic, transcriptomic, proteomic and clinical datasets from international cohorts. Using artificial intelligence and digital twin simulations, the team aims to model how ALS progresses in individual patients and uncover the biological mechanisms driving the disease.
This approach will help identify the most promising therapeutic targets and could also support the development of new drugs or the repurposing of existing ones. The project is among the first globally to combine large-scale ALS data with generative artificial intelligence and digital twin technology in this way.
The findings may also have broader implications for related conditions, including frontotemporal dementia and Parkinson’s disease, which share underlying biological mechanisms such as protein misfolding and neuroinflammation.
“This work will demonstrate the transformative potential of artificial intelligence in biomedical discovery,” Associate Professor Menden said. “It also strengthens international collaboration and offers renewed hope to patients and families affected by this devastating disease.”