News
What have we been up to?

From partnership and fundraising announcements to co-founders interviews and AI in pharma news, discover in this news section what we have been up to.

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Press Release
November 2020

Owkin announces a new collaboration to identify High Immunogenic Epitopes and Candidates for COVID-19 and Coronaviruses Future Vaccines.

Press Release
October 2020

Owkin and Nantes University Hospital (CHU Nantes) to Advance Cancer Research with

Partnership
Press Release
September 2020

Owkin and Institut Carnot CALYM Launch a Collaboration to Advance Lymphoma Research with Artificial Intelligence

Partnership
Press Release
September 2020

Owkin and NYU Langone Health to Advance Non-Small Cell Lung Cancer Research with Artificial Intelligence

Partnership
Press Release
September 2020

MELLODDY Project Meets its Year One Objective: Deployment of t​he world’s first secure platform for multi-task federated learning in drug discovery​ Among 10 Pharmaceutical Companies

Federated Learning
Press Release
August 2020

Owkin published in Nature Communications – A deep learning model to predict RNA-Seq expression of tumors from whole slide images

Machine Learning
Press Release
May 2020

Owkin and The Bergonié Institute Sign a Partnership Agreement to Further Collaborations with Cancer Research Centers in Immuno-Oncology and Sarcoma.

Partnership
Press Release
March 2020

Owkin and The University of Pittsburgh Launch a Collaboration to Advance Cancer Research with Artificial Intelligence and Federated Learning

Partnership
Press Release
March 2020

The FFCD and Owkin Join Forces to Apply Machine Learning to Digestive Oncology

Partnership
Press Release
January 2020

Artificial Intelligence in Oncology Strategic Alliance Between Owkin and Gustave Roussy Formed to Accelerate Clinical Research

Partnership
Press Release
October 2019

AP-HP and Owkin Launch a Series of Data Research Projects Based on Machine Learning

Partnership
Press Release
October 2019

Owkin publishes breakthrough research in Nature Medicine: Novel deep-learning approach for predicting and explaining the key prognostic factors in Mesothelioma

Machine Learning