Sanofi taps Owkin's AI platform for cancer drug development

Sanofi said Thursday that it will invest $180 million in Owkin as part of a collaboration with the artificial intelligence (AI) startup focused on developing treatments across four types of cancer. The agreement includes a total payment of $90 million for three years, plus additional research milestone-based payments.

Owkin's platform connects life science companies with academic researchers and hospitals to share medical insights for drug discovery and development. The AI company's research network, which is powered by federated learning, is designed to allow data scientists to securely connect to decentralised, multi-party data sets and train AI models without having to pool data.

The two companies have previously worked together on discreet projects in oncology, FirstWord HealthTech is told. Under this partnership, Sanofi will use Owkin's platform to find new biomarkers and therapeutic targets, building prognostic models, and predicting response to treatment from multimodal patient data. John Reed, global head of R&D at Sanofi, explained that the collaboration will focus on new treatments will be for non-small-cell lung cancer, triple-negative breast cancer, mesothelioma and multiple myeloma.

Stake of 10% to 15%

Meanwhile, Owkin CEO Thomas Clozel noted that the deal gives Sanofi a stake of between 10% and 15%, valuing the company at more than $1 billion. "It's our biggest deal," Clozel said, adding "it shows the confidence of a pharma in our technology and platform: They understand their importance for drug discovery and clinical trials."

When asked the rationale behind wanting a stake in Owkin, rather than staying partners, a Sanofi spokeperson told FirstWord HealthTech that the equity investment allows the company "to engage Owkin at a corporate level, to support their company journey in advancing federated learning both from a technology and capability perspective."

In September, Owkin partnered with Johnson & Johnson's Actelion Pharmaceuticals unit to investigate machine learning-based methods for the estimation of treatment effect in clinical trials involving real-world data sources. More recently, the company entered a research collaboration with the Memorial Sloan Kettering Cancer Center to use machine learning to identify patients with some of the most aggressive forms of bile duct cancer so that they can be treated earlier in the disease course.