Can artificial intelligence redefine medicine and fast-track new treatments? In this groundbreaking episode of AI Daily, host Harry Kermode explores Isomorphic Labs' announcement of human trials for AI-designed drugs. Backed by DeepMind's AlphaFold breakthroughs, this marks a pivotal moment for AI's role in healthcare and drug discovery. Expect insights into the challenges and promises of such innovations, as well as ethical and workforce implications. Tune in to learn if AI truly signifies a new era for medicine. Don't forget to subscribe, share, and leave a review! 

FULL TRANSCRIPT: It's Monday, July 14th, 2025. I'm Harry Kermode, and this is AI Daily.

For decades, we've imagined artificial intelligence reshaping medicine, promising faster cures, cheaper treatments, and untold leaps in human health. Today, we're stepping closer to that promise becoming reality.

Yesterday, Isomorphic Labs, a spinoff of Google's famous AI research division DeepMind, announced that human trials for drugs exclusively designed by artificial intelligence will soon begin. This news marks an unprecedented milestone: for the first time in history, we will witness human clinical testing of medicines whose molecular structures have been discovered purely by AI algorithms.

To grasp the significance of this moment, let's step back briefly to look at its foundations. Remember, just two years ago DeepMind's AlphaFold won the Nobel Prize in Chemistry for solving one of biology's oldest and toughest challenges—accurately predicting protein structures. That discovery fundamentally transformed how scientists approach disease and treatment. Proteins and their shapes determine nearly every biological process, and knowing those structures enables scientists to precisely design molecules to target diseases.

At the intersection of biology and AI, Isomorphic Labs was born—named for the symmetry between information science and biological systems. The company set out to prove that AI could shorten the slow, costly traditional process of drug discovery, a system notorious for taking up to 15 years and billions of dollars per drug.

Fast forward to July 2025, and the world is about to see if AI can truly deliver. With over $600 million in funding and high-stakes partnerships totaling billions—including pharmaceutical giants like Novartis and Eli Lilly—Isomorphic Labs carries immense expectations on its shoulders. Investors are banking not only on revolutionary medicine, but also on transforming their financial returns. For Alphabet, Google's parent company, success means validation for their massive strategic bet on biotechnology.

Behind the press releases and optimism, there's an important conversation about risk and realism. AlphaFold's capabilities, while groundbreaking, do not yet model the full complexities and uncertainties of human biology. It's one thing to design a molecule in a digital lab; it's another entirely to ensure its safety and effectiveness in real patients. Already, respected voices in the medical community caution against seeing AI as a cure-all shortcut. Margaret Foti, CEO of the American Association for Cancer Research, reminds us that "AI accelerates hypotheses, but it will never replace clinical rigor."

There are ethical questions too: who controls this powerful technology? As breakthrough treatments created by algorithms and big data might one day flood the pharmaceutical market, will the benefits reach the broader global community, or remain out of reach, patented and prohibitively expensive?

Critics also highlight an understated human consequence—labor displacement. If AI designs drugs faster than pharmaceutical chemists, what becomes of their careers? Will the future workforce adapt, or will this technological disruption leave skilled professionals behind?

These trials, set to start within months, are indeed historic. Success might trigger regulatory shifts, new investment waves, and massive transformations in science and healthcare. Failure could lead to immense scrutiny, skepticism, and cautionary tales.

Behind every technological revolution lies a tension between its potential and its unintended consequences. Today, we find ourselves at the dawn of such a moment in medical history—hope tempered by questions, excitement balanced by caution.

AI has promised a revolution in medicine. Now, we hold our breath to see if it can deliver.

This has been AI Daily. We'll see you tomorrow.

The Unstoppable Rise of AI in Medicine: Promise or Peril?

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