Case study
May 16, 2023

Case study: MesoNet

Authors
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Case study
May 16, 2023

Case study: MesoNet

Authors
No items found.
About Owkin

Owkin is an AI biotechnology company that uses AI to find the right treatment for every patient. We combine the best of human and artificial intelligence to answer the research questions shared by biopharma and academic researchers. By closing the translational gap between complex biology and new treatments, we bring new diagnostics and drugs to patients sooner.

We use AI to identify new treatments, de-risk and accelerate clinical trials and build diagnostic tools. Using federated learning, a pioneering collaborative AI framework, Owkin enables partners to unlock valuable insights from siloed datasets while protecting patient privacy and securing proprietary data.

Owkin was co-founded by Thomas Clozel MD, a former assistant professor in clinical onco-hematology, and Gilles Wainrib, a pioneer in the field of machine learning in biology, in 2016. Owkin has raised over $300 million and became a unicorn through investments from leading biopharma companies (Sanofi and BMS) and venture funds (Fidelity, GV and BPI, among others).

Case study: MesoNet

A biomarker of outcome prediction in Mesothelioma

Prognostic biomarkers
Risk Score Biomarker
Mesothelioma
Histology Data
Prognostic biomarkers
Risk Score Biomarker
Mesothelioma
Histology Data
6-13%
MesoNet prognosis predictions can be used for patient stratification to reduce sample size of phase 3 trials by 6-13%.
Context

Malignant mesothelioma patients are diagnosed and classified by pathologists via tissue biopsy. Only three FDA-approved drugs exist for mesothelioma with varying response. Novel biomarkers are needed to improve clinical care and offer possible targets for new drugs.

Methods

Owkin built MesoNet, a machine learning model that predicts the overall survival of malignant mesothelioma patients from digital pathology images better than existing subtype classification used by pathologists.

Results

MesoNet highlighted new biomarkers predictive of prognosis in collaboration with expert mesothelioma pathologists: stroma, tumor cell localization, inflammation, cellular diversity & vascularization.

Impact

MesoNet can be used in clinical routine to aid patient prognosis, providing important input for patient management.

The novel morphological biomarkers identified in the tumour microenvironment could lead to the discovery of new druggable targets.

Published in Nature medicine Courtiol et al. 2019

Testimonial

"Owkin were able to identify details from the histology slides that we knew about but had never previously recognized as significant prognostic indicators.”
Professor Galateau Salle
Centre Leon Berard