Bottom Line: Researchers at the University of Edinburgh use the AI system Co-Scientist to achieve breakthroughs in treating MASH, a liver disease, with the system identifying the NLRP3 inflammasome as a key mechanism and significantly accelerating the development of new combination therapies.
At the University of Edinburgh, bioengineering researcher Filippo Menolascina uses the AI system Co-Scientist to uncover hidden connections in the medical literature and develop new hypotheses for treating liver diseases.
Biomedical research generates a flood of information daily that no individual scientist can realistically manage. Menolascina’s team focuses on metabolic dysfunction-associated steatohepatitis (MASH), a widespread liver disease. Developing treatments is particularly complex because MASH involves numerous interconnected biological processes – including liver inflammation and metabolism – which is why single-target drugs are not sufficiently effective.nnThis leads researchers to combination therapies, but the number of possible drug pairings is overwhelming. With Co-Scientist, Menolascina’s team was able to drastically narrow the search. The system synthesized insights from liver biology and pharmacology, identified promising mechanisms, and presented candidates for combination therapies that could subsequently be tested.nnIn a particularly revealing case, Co-Scientist answered a practical question: why does the drug resmetirom – a recently approved treatment for a specific MASH stage – help only a small portion of eligible patients? The system developed a hypothesis identifying the NLRP3 inflammasome as the molecular bridge linking inflammation and metabolism in the disease – a connection that had never before been synthesized into a single, actionable explanation. The hypothesis, later confirmed experimentally, could pave the way for targeted dual therapies.