
An estimated five per cent of the global adult population suffers from metabolic dysfunction-associated steatohepatitis (MASH), a progressive form of fatty liver disease that often goes undetected until it’s too late. MASH (formerly known as nonalcoholic steatohepatitis or NASH), is the advanced stage of what used to be known as metabolic dysfunction-associated steatotic liver disease (MASLD, formerly known as non-alcoholic fatty liver disease), which is caused by fat buildup in the liver that leads to inflammation and scarring — and if left untreated, it can quietly progress to cirrhosis, liver failure, or even cancer.
Despite its severity, over 90 per cent of MASH cases are undiagnosed. Not because the condition is rare, but because it rarely causes symptoms early on. As a result, MASH has become one of the largest undetected health burdens, costing over US$125 billion in the United States alone annually, with that figure projected to double by 2040.
This is not just a clinical issue. It’s an infrastructure issue. We’ve lacked the tools to screen early, easily, and at scale. But that’s beginning to change.
You can’t treat what you can’t find
For years, the field of liver disease faced a frustrating paradox: growing prevalence, but limited treatment options. That’s no longer the case. After decades of stalled progress, the first FDA-approved drug for MASH arrived in 2024. Five more therapies are expected within the next three years.
This is a watershed moment — but it comes with a new challenge. Treatment is no longer the bottleneck. Diagnostics is.
You can’t prescribe these new therapies if you don’t know who needs them. Yet today, MASH is diagnosed through inaccurate tests, costly imaging, or worse, liver biopsies — invasive procedures that are painful, expensive, and inaccessible for routine use. More than 50 million Americans already meet the criteria for screening, yet there’s no scalable way to identify them.
To unlock the potential of these new treatments, we need to reimagine how — and where — diagnosis happens.
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The AI opportunity in diagnostics
Recent advances in AI and genomics are finally giving us the tools to tackle MASH detection at scale. One of the most promising approaches is liquid biopsy — analysing biomarkers in blood to identify early molecular signs of disease. When paired with machine learning models, this allows us to capture complex biological signals without relying on invasive or expensive procedures like liver biopsies or MR elastography.
This kind of AI-powered screening could fundamentally shift how we approach chronic liver disease — making detection earlier, more accurate, and more affordable. If we want to intervene before irreversible damage occurs, tools like these need to become part of routine clinical workflows.
Why teams matter in diagnostic innovation
Progress in diagnostics doesn’t happen in isolation. It builds on decades of work in genomics, clinical research, and computational biology. Some of the most meaningful advances in this space have come from cross-disciplinary teams — researchers, engineers, and clinicians working side by side to ensure new technologies serve real-world needs.
This collaboration is especially critical in liver disease, where the biology is nuanced and early signals are often subtle. Partnering closely with hepatologists and researchers ensures that emerging diagnostic tools are not just accurate in the lab, but useful in the clinic.
Why early-stage capital matters
Breakthroughs in diagnostics often come from new entrants — startups willing to take on high technical risk in exchange for meaningful clinical impact. But getting from concept to clinic requires more than science. It requires conviction from investors who understand the long timelines and regulatory hurdles in healthcare innovation.
Early-stage funds with a focus on deep tech and biotech can play a catalytic role here — helping young companies refine their direction, access expert networks, and stay focused on patient outcomes over short-term optics. In fields like liver disease, where diagnostic innovation is urgently needed, this kind of early backing isn’t just helpful. It’s essential.
From detection to full care pathway
While the current focus is on screening, the opportunity in diagnostics doesn’t stop there. The same technologies that flag patients early could also help tailor treatments — supporting therapy selection, monitoring disease progression, and eventually enabling companion diagnostics (CDx) that match the right patient to the right therapy.
Building high-quality, deeply annotated datasets will also be critical. With better data, we can accelerate drug development not only for MASH, but for other diseases with similar diagnostic challenges.
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It’s the same strategy we’ve seen transform oncology: precision diagnostics fuelling targeted therapies. Now, that same precision is coming to liver disease — deliberately, from day one.
A future where diagnostics are foundational
At its core, the mission is simple: make preventative diagnostics as routine and reliable as getting your blood pressure checked.
Because the truth is, the science is here. The therapies are here. But until we make early detection easy, accessible, and scalable, most patients won’t benefit.
AI won’t replace doctors. But it can help them find disease earlier and provide clinically actionable insights — and give patients a fighting chance before symptoms ever show up.
That’s not a moonshot. That’s just good medicine.
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