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Why Sofinnova is Betting on the Confluence of Digital Technology and the Life Sciences

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In other words, the fund appears to be at least 100 million euros.

“This is as far as I can go,” he demurred, declining to clarify whether the math was correct.

He explained that 70% of the fund will be invested in European companies that fit the bill.

The three startup that have won investment from this new strategic fund are – Munich, Germany-based deepc that drives greater adoption of AI tools by helping them integrate within radiology workflows. The company raised €12 million in a Series A round led by Sofinnova Partners.

Radiology is an area that has actually seen early success with the use of AI in improving detection and efficiency but still adoption is not widespread. So the obvious question is why not?

Turns out the answer is, it is very cumbersome to have 10 different agreements with 10 different startups on the [U.S.] West coast with 10 different payment terms with 10 different data compliance regulations,” Kliphuis said. 

And so what deepc does is to be the platform through which hospital radiology departments can adopt AI.

“Deepc is an aggregator; it’s the app store of radiology,” Kliphuis explained. “They have agreements with 10 to 20 radiology providers. They embed themselves into the hospital, and therefore they’re the only sort of counterpart that the hospital has to deal with. They are the operating system for radiology.”

The second firm that Sofinnova has sunk its money in as lead investor is Paris-based Kiro, which raised 13.8 million to leverage AI both in clinical decision-making and in patient engagement — specifically as it pertains to lab results. Kiro aids the communication of lab test reports among clinical laboratories, health professionals and patients.

Now, what these guys do is they basically have a simple natural language processing tool and they test that information and, and interpret it. And thereby provide enormous value to patients and physicians,” he said. 

The third company Sofinnova invested in is London-based BioCorteX, which raised a 5 million seed round last week. The company enables precision by using simulation and modeling to understand the interaction between drugs and bacteria in the body with the aim of improving a patient’s response to treatments.

“Now, these guys have built for the first time a tool called, Carbon Mirror, which is basically a simulation engine that allows you to simulate the way bacteria and human health interact,” Kliphuis explained. “They basically commit themselves at this point to actually understanding the response and non-response in therapies.  And this was the prime example of being able to use computation and data to understand something that we simply haven’t been able to comprehend before.”

For Kliphuis, the strategy that Sofinnova is pursuing goes beyond investing in digital therapeutics, which has struggled to gain traction in healthcare. Pear Therapeutics, one of the early and promising crop of digital therapeutics companies recently announced another round of layoffs and is considering “strategic alternatives” – in other words, a sale. Better Therapeutics is also laying off workers. And Proteus Digital Health filed for bankruptcy in 2020 despite raising millions of dollars and having a FDA-cleared product on the market. Otsuka, Japanese pharma maker with which it had a partnership bought it for scraps in August 2020. Large pharma like Novartis have also stepped back from their embrace of digital therapeutics. Though the sector is a smaller subset of the data+biology umbrella that Sofinnova is investing it, does the history of pharma+digital combinations give Kliphuis pause?

It actually doesn’t given the experience he has in the space, he said. Kliphuis sits on the board of Akili Labs, which has won distinction as the world’s first FDA-cleared prescription digital therapy – a video game treatment for ADHD. Now Akili has not been immune to layoffs and its stock price has plummeted but there appear to be no signs (yet) of a financial meltdown.

He attributed the failure of digital therapeutics as a category and the fits and starts that these startups have had in commercialization to the idea that “new technology” was forced to work within an existing model for commercialization.

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