AI makes headlines again as Insilico signs another major licensing deal

#AI has been making the headlines again this week, with a bold announcement from the UK government that it could be used to fix the many potholes that pepper Britain’s roads. 

But beyond politics, there’s an ongoing narrative in life sciences about the growing role of AI across the clinical development process. 

Perhaps the most intriguing use is the idea of an AI-designed drug, which is exactly what Insilico Medicine Inc. is trying to develop. 

Vaunted as one of the leaders in AI and deep learning-based drug design, Insilico burst onto the scene in 2019 with a scientific paper showing it could use AI to design, synthesise and validate a novel drug candidate in 46 days – 15 times faster than the best pharma companies. 

Since then, Insilico has been busy making good on the early promise demonstrated by its technology – this week it signed a second major drug development deal with Stemline Therapeutics Inc., part of The Menarini Group. 

The $550-million plus licensing deal for the unnamed preclinical small-molecule drug targeting solid tumours adds to the $500 million deal the companies signed in January 2024. 

Stemline is paying $20 million up front to gain global rights to develop and market the drug discovered by generative AI technology. The rest of the money will come from development, regulatory, and commercial milestones, plus unspecified tiered royalties. 

The news also coincides with the pioneering AI foundation model company, Bioptimus, receiving a significant funding milestone of $76 million. Including a cash injection from Optimum’s client Sofinnova Partners, the funding will accelerate Bioptimus’s mission to build the world’s first universal AI foundation model for biology to revolutionise research across life sciences and beyond. 

It is further evidence that AI is becoming a “must have” in the drug development process, as developers seek to cut admin costs during the recruitment process. 

As Insilico’s AI-designed medicines progress through the clinic, they will be closely watched. The hope is that AI could reduce the attrition rate in clinical development that remains stubbornly high – and extremely costly. 

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