Alphabet's Isomorphic Labs to Launch Human Trials for AI-Designed Drugs

Alphabet’s Isomorphic Labs, a subsidiary of Google DeepMind, is on the verge of a significant breakthrough as it prepares to launch human trials for its AI-designed drugs. This development is a major step in the company's ambitious goal to revolutionize disease treatment and potentially cure all diseases using artificial intelligence. The announcement was made by Colin Murdoch, the president of Isomorphic Labs and Google DeepMind’s chief business officer, who emphasized the transformative potential of AI in pharmaceutical research.

Isomorphic Labs, which was spun out of DeepMind in 2021, has been at the forefront of integrating AI into drug discovery. The company leverages advanced machine learning algorithms to analyze vast amounts of biological data, identify potential drug targets, and design new compounds that can effectively treat a wide range of diseases. This approach not only accelerates the drug discovery process but also enhances the precision and efficacy of the treatments developed.

The decision to move forward with human trials is a testament to the confidence Isomorphic Labs has in its AI-driven research. These trials will provide crucial insights into the safety and effectiveness of the AI-designed drugs, paving the way for potential regulatory approval and widespread use. This step is particularly significant given the high failure rates and lengthy timelines typically associated with traditional drug development processes.

The implications of this development are far-reaching. If successful, AI-designed drugs could transform the landscape of healthcare by offering more targeted and effective treatments for a variety of conditions. This could lead to improved patient outcomes, reduced healthcare costs, and a more efficient use of resources in the pharmaceutical industry. Moreover, the success of Isomorphic Labs could inspire other companies to invest in AI-driven drug discovery, further accelerating innovation in the field.

However, the journey from AI-designed drugs to approved treatments is fraught with challenges. Human trials are a critical phase in the drug development process, and the outcomes are uncertain. Isomorphic Labs will need to navigate regulatory hurdles, address potential safety concerns, and demonstrate the superiority of its AI-designed drugs over existing treatments. Despite these challenges, the company's progress represents a significant step forward in the quest to harness the power of AI for medical breakthroughs.

In 2024, the same year it released AlphaFold 3, Isomorphic signed major research collaborations with pharma companies Novartis and Eli Lilly. A year later, in April 2025, Isomorphic Labs raised $600 million in its first-ever external funding round, led by Thrive Capital. These deals are part of Isomorphic’s plan to build a “world-class drug design engine,” a system that combines machine learning researchers with pharma veterans to design new medicines faster, more cheaply, and with a higher chance of success.

As part of the deals with major pharma players, Isomorphic supports existing drug programs, but it also designs its own internal drug candidates in areas such as oncology and immunology, with the aim of eventually licensing them out after early-stage trials. “We identify an unmet need, and we start our own drug design programs. We develop those, put them into human clinical trials… we haven’t got that yet, but we’re making good progress,” Murdoch said.

Today, pharma companies often spend millions attempting to bring a single drug to market, sometimes with just a 10% chance of success once trials begin. Murdoch believes Isomorphic’s tech could radically improve those odds. “We’re trying to do all these things: speed them up, reduce the cost, but also really improve the chance that we can be successful,” he says. He wants to harness AlphaFold’s technology to get to a point where researchers have 100% conviction that the drugs they are developing are going to work in human trials. “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,” Murdoch said. “All powered by these amazing AI tools.”