There’s a new generative AI startup based in Paris. But what makes Bioptimus interesting is that it plans to apply everything we’ve collectively learned about AI models over the past few years with a narrow, exclusive focus on biology.
The reason it makes sense to create a startup focused exclusively on biology is that access to training data isn’t as simple in this field. While OpenAI is slowly moving away from web crawling in favor of licensing deals with content publishers, Bioptimus is facing different data challenges as it will have to deal with sensitive clinical data that isn’t publicly available at all.
And just like other AI startups, Bioptimus is going to be a capital-intensive startup as it will train its models on expensive GPUs and hire talented researchers. That’s why the startup is raising a $35 million seed round led by Sofinnova Partners. Bpifrance’s Large Venture fund, Frst, Cathay Innovation, Headline, Hummingbird, NJF Capital, Owkin, Top Harvest Capital and Xavier Niel also participated in this funding round.
Bioptimus isn’t coming out of nowhere. At the helm of the company, Jean-Philippe Vert will act as co-founder and executive chairman in a non-operational role. At his day job, he is the chief R&D officer at Owkin, the French biotech unicorn that tries to discover new drugs and improve diagnostics through AI.
Rodolphe Jenatton, the CTO of Bioptimus, has more experience in artificial intelligence, as he was a senior research scientist at Google. Several co-founders are also former researchers at Google DeepMind.
As part of Owkin’s work for top biopharmas, Owkin has amassed multimodal patient data through partnerships with leading academic hospitals around the world. Bioptimus will leverage this unique dataset to train its foundational model.
A moonshot project from Owkin
Bioptimus could even be considered as a sort of spin-off company from Owkin — or a so-called moonshot project. But why didn’t Owkin decide to work on a foundational model in house? Creating new AI models is such a daunting task that creating a separate entity made more sense.
“Building biology [foundational models] is not a part of Owkin’s roadmap, but Owkin supports and is keen to partner with a company like Bioptimus. Training very large-scale [foundational models] requires important resources in terms of data volume, computing power and breadth of data modalities that are easier to unlock as a specific entity,” Vert told TechCrunch. “As a ‘pure player’ in foundational models, Bioptimus is better set up to do this.���
The startup has also signed a partnership with Amazon Web Services. It sounds like the company’s model will be trained in Amazon’s data centers. Now that Bioptimus is well funded, it’s time to work on the AI model and see what the biotech research community can do with it.
“Eventually, the AI we build will improve disease diagnosis, precision medicine, and will help create new biomolecules for medical or environmental use,” Vert said.
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