Axios Pro Exclusive Content

Unlearn snags $50M for digital twins in clinical trials

headshot
Feb 8, 2024
Illustration of ones and zeroes coming out of a head.

Illustration: Rebecca Zisser/Axios

Unlearn, an AI-powered tech platform creating "digital twins" of clinical trial participants to accelerate drug development, raised a $50 million Series C.

Why it matters: On average, development costs now exceed $2 billion per new drug.

Details: The round was led by by Altimeter Capital. New investors Insight Partners, 8VC, DCVC and DCVC Bio also joined.

  • Insiders Radical Ventures, Wittington Ventures, Mubadala Capital, Epic Ventures and Necessary Ventures participated as well.

What's next: The round should get San Francisco-based Unlearn to profitability, CEO Charles Fisher tells Axios.

  • "Our goal is that this will be the last time we raise capital," he says. Founded in 2017, Unlearn has raised more than $130 million in total.
  • He declined to disclose Unlearn's revenue.

How it works: Unlearn's AI and machine learning models create individual digital "twins" for participants in clinical trials, before the patients are randomized into experimental or control arms.

  • The digital twin helps forecast health outcomes under placebo, regardless of their actual assignment.
  • This results in clinical trials with smaller control groups, allowing more patients to receive experimental treatment and reducing the time it takes to bring new drugs and therapies to market.
  • "Our mission is to advance AI to eliminate trial and error in medicine," he says.

Of note: Unlearn's approach has been qualified by the European Medicines Agency (EMA) for use. The company recently announced the FDA's Center for Drug Evaluation and Research (CDER) concurred with EMA's judgment.

What they're saying: "Unlearn has assembled a strong team using AI to tackle a key and urgent need in the massive clinical trials market in a differentiated way," says Altimeter partner Pauline Yang.

  • "This digital twin technology allows pharma and biotech companies to reduce meaningfully the control arm to reduce both time and cost of patient recruitment," she says.
Go deeper