Can AI Really Cure All Diseases?
Yes, it sounds like a moonshot. But the company behind AlphaFold has money, momentum, and a crystal-clear vision. If you're wondering whether AI can really be the key to unlocking cures for humanity’s biggest health problems, we’ve got answers. Let’s break it down.
AI can’t cure all diseases yet, but Alphabet’s Isomorphic Labs is betting big that it can radically accelerate drug discovery. Using AlphaFold’s protein modeling capabilities, they're designing new drugs faster, cheaper, and with higher precision — and human trials are now on the horizon.
Is this the beginning of a new age in medicine? The science, funding, and partnerships suggest so. Let’s explore how Isomorphic Labs plans to turn AI into humanity’s medical miracle machine.
How Is AI Helping Cure Disease?
At its core, drug development is a painfully slow, expensive gamble. Big Pharma can spend $2.6 billion over 10+ years to develop a single drug — and still have only a 10% shot at success once human trials begin. That’s not a business model; that’s roulette in a lab coat.
Now enter AI, specifically AlphaFold.
AlphaFold transformed the world’s understanding of proteins — the LEGO bricks of life. Knowing exactly how a protein folds means researchers can design drugs that fit them like a lock and key, instead of relying on trial and error. AlphaFold 3, released in 2024, went even further, modeling protein interactions with drugs and DNA. That was the launchpad for Isomorphic Labs.
And it’s not all blue-sky dreaming. In 2024, Isomorphic Labs signed deals with Novartis and Eli Lilly, supporting existing programs and creating brand-new drugs from scratch. They're focusing first on oncology and immunology, two massive fields full of unmet need.
🧪 What Makes Isomorphic’s Approach Different?
1. Machine Learning Meets Human Expertise
They’re not handing the reins over to robots. Isomorphic combines ML researchers, pharma vets, and domain experts in one drug design engine. It’s humans and machines, collaborating to outwit disease.
2. Speed & Accuracy
AI can simulate in seconds what used to take weeks — and do it across billions of molecular combinations. This means faster design cycles, fewer dead ends, and more promising compounds entering trials.
3. A New Business Model
Isomorphic isn’t just doing contract work. They’re creating their own drug candidates, running early-stage trials, and licensing the winners to bigger pharmaceutical firms. It’s like being both the garage band and the record label.
💸 What’s the Business Behind the Science?
In April 2025, Isomorphic Labs raised $600 million in external funding, led by Thrive Capital — a massive vote of confidence from venture capital.
They’re building not just a lab, but an AI-powered drug discovery platform, the kind pharma has dreamed about for decades.
Isomorphic plans to use that cash to:
- Expand internal drug programs
- Staff up clinical operations
- Scale partnerships with pharma giants
- Refine their predictive accuracy and modeling tools
As CEO Murdoch puts it:
“We’re trying to speed things up, reduce costs, and really improve the chance that we can be successful.”
🧬 What Diseases Are They Targeting First?
Isomorphic isn’t tackling the entire disease catalog at once. Their first wave of AI-designed drugs focuses on:
- Cancer (Oncology) – where current treatments are costly, toxic, and often ineffective
- Immune disorders (Immunology) – including autoimmune diseases and chronic inflammation
These areas are strategic: they’re scientifically complex, and they represent multi-billion-dollar markets with lots of failed drugs. If AI can crack even a fraction of this, the impact will be massive — financially and medically.
🔮 Is the “One-Click Drug” Future Real?
Murdoch summed it up best:
“One day we hope to be able to say — well, here’s a disease, and then click a button and out pops the design for a drug to address that disease.”
It’s a bold vision — but no longer unimaginable. AlphaFold was once considered impossible, and now it’s a tool used by biologists around the world.
Isomorphic’s ultimate dream is to build a general-purpose AI for drug discovery — one that turns biology into a computational problem. And with human trials about to begin, we may soon find out how close we really are to that goal.
