Owkin was founded in 2016, by Thomas Clozel, a clinical research doctor and son of Jean-Paul and Martine Clozel founders of Swiss biotech Actelion, and Gilles Wainrib, a professor of Artificial Intelligence.^[4]

Owkin has raised over $255 million and became a ‘unicorn’ – a startup valued at more than $1 billion – in November 2021 through a $180 million investment from French biopharma company Sanofi.^[5]

Federated learning edit

Owkin uses federated learning, a decentralized machine learning technique, to train machine learning models with multiple data providers.^[6][7][8] Federated learning allows data providers to collaborate without moving or sharing their data.^[8][7]

The MELLODDY project, an initiative that included Owkin, 10 pharmaceutical companies, and six other partners, applied federated learning to train AI on datasets without having to share proprietary data.^[9][8][10] The aim was to improve drug discovery and they built a shared platform called MELLODDY (Machine Learning Ledger Orchestration for Drug Discovery).^[9][10][8] The first results of the project were published in July 2022.^[8]

Transfer learning edit

Transfer learning is a machine learning technique that allows a model pre-trained on one task to be used on another related task.^[11] Owkin uses transfer learning to work on very small datasets.^[11] Owkin's model (CHOWDER) is able to understand high-level graphic patterns, such as tumors, that are themselves relying on very low-level visual patterns, in order to fully learn the tumor's visual pattern.^[12]

MSIntuit CRC edit

MSIntuit CRC is an AI-powered digital pre-screening diagnostic tool to improve colorectal cancer diagnosis and treatment.^[13] It screens patients for microsatellite instability (MSI), which is a key genomic biomarker in colorectal cancer.^[13] MSIntuit CRC is approved for use across the European Union.^[14] It underwent a blind validation in 2023, made possibly partly by its availability within Medipath, the largest pathology lab network in France.^[1]

Dx RlapsRisk BC edit

Dx RlapsRisk BC uses AI to predict if breast cancer patients will relapse within a few years of initial treatment.^[14] It is used by pathologists and oncologists to help determine the right treatment pathway for breast cancer patients.^[14]

Amgen edit

Owkin collaborated with Amgen to test the ability of AI to improve cardiovascular prediction.^[3]

Sanofi edit

In November 2021 Owkin entered a strategic alliance with Sanofi.^[15] The alliance included a $180 million equity investment, and a $90 million discovery and development partnership focused on Sanofi’s oncology efforts in four different cancers.^[16] Sanofi used Owkin’s technology to find new biomarkers and therapeutic targets, build prognostic models, and predict response to treatment.^[17]

Bristol-Myers Squibb edit

In June 2022, Owkin entered a strategic alliance with Bristol-Myers Squibb to help them design potentially more precise and efficient clinical trials.^[17] The collaboration initially focused on cardiovascular disease, and has the potential to expand into projects in other therapeutic areas.^[18]

MSD edit

In December 2023, Owkin entered a strategic alliance with MSD to develop and commercialize AI-powered digital pathology diagnostics for the EU market that could be used to identify patients suitable for immunotherapies.^[19]

Servier edit

In October 2023, Owkin and Servier started a multi-year partnership focused on developing “better-targeted therapies” in oncology and other disease areas.^[20] The partnership’s first two projects were in translational medicine and digital pathology.^[20]

MOSAIC edit

MOSAIC (Multi Omic Spatial Atlas in Cancer) was formed by Owkin, Nanostring Technologies, the University of Pittsburgh, Gustave Roussy, Lausanne University Hospital, Uniklinikum Erlangen/Friedrich-Alexander-Universität Erlangen-Nürnberg, and Charité-Universitätsmedizin Berlin.^[21][22] It uses spatial omics, multimodal patient data, and artificial intelligence, and aims to “offer unprecedented information on the structure of tumors” and guide new treatments.^[22][21]

Owkin’s research on AI/ML has led to a number of publications that focus on machine learning methodologies and the development of predictive models for different disease areas, mainly oncology.

1. Courtiol, Pierre et al. “Deep learning-based classification of mesothelioma improves prediction of patient outcome”, Nat Med 25, 1519–1525 (2019)^[23]
2. Schmauch, Benoît et al. “A deep learning model to predict RNA-Seq expression of tumours from whole slide images”, Nature Communications volume 11, Article number: 3877 (2020)^[24]
3. Jean Ogier du Terrail et al. “Federated learning for predicting histological response to neoadjuvant chemotherapy in triple-negative breast cancer" Nat Med (2023). 10.1038/s41591-022-02155^[25]
4. Saiilard et al., “Pacpaint: a histology-based deep learning model uncovers the extensive intratumor molecular heterogeneity of pancreatic adenocarcinoma” Nat Commun 14, 3459 (2023)^[26]
5. Saillard et al., “Validation of MSIntuit as an AI-based pre-screening tool for MSI detection from colorectal cancer histology slides” Nature Communications 14, 6695 (2023)^[27]
6. Saillard et al., "Predicting Survival After Hepatocellular Carcinoma Resection Using Deep Learning on Histological Slides" Hepatology 72 (2020)^[28]

• 2019 AI For Health challenge^[29]
• 2020 Galien Foundation Best Digital Health Product Nominee^[30]
• 2021 Tech For Good Awards - “Health” category^[31]
• 2021 Member Recognition Awards from the French American Chamber of Commerce - Technology, Startups & Entrepreneurs Committee Awards^[32]