CORDIS - EU research results
CORDIS

MachinE Learning Ledger Orchestration for Drug DiscoverY

Project description

Teaching machines to help with drug discovery

The pharmaceutical industry faces increasing challenges due to rapid advancement of technology coupled with increasingly stricter regulations. But the need for a proven, reliable and privacy-securing platform to enable industries to obtain information from competitive data is indispensable. The EU-funded MELLODDY project will demonstrate how the pharmaceutical industry can further exploit its data assets by using machine learning technologies to achieve drug discovery (DD) virtualisation. The project will use more than a billion private and competitive DD-related data and hundreds of Tbs image data assuring the strict privacy of the used material and will create an open service available to the sector.

Objective

MELLODDY will demonstrate how the pharmaceutical industry can better leverage its data assets to virtualize the Drug Discovery (DD) process with world-leading Machine Learning (ML) technologies as an answer to the ever-increasing challenges and stricter regulatory requirements it is facing. The lack of a tested, secure and privacy-preserving platform for federated machine learning that enables pharmaceutical partners to extract DD-relevant information from all types of, not only their own but even each other’s competitive data, without mutual disclosure of the chemistry and biology each partner has worked on, has previously held back such demonstration, to the detriment of patients in the EU and beyond.
MELLODDY’s ten pharmaceutical partners will enable this demonstration with an unprecedented volume of more than a billion highly private and competitive DD-relevant data points, and hundreds of Tbs of image data that annotate the biological effects of more than 10 million small molecules. The successful demonstration of the predictive benefits, i.e. increased predictive model performance and chemical applicability domain, of unlocking this data volume, while strictly preserving the privacy of all underlying data and the resulting predictive models, will shape best practices and translate into substantial efficiency gains in the DD process, and in the future, drug development. Finally, MELLODDY will prepare and exploit a service-for-fee vehicle to ensure the MELLODDY technologies are available to the rest of the pharmaceutical sector.

Coordinator

OWKIN FRANCE
Net EU contribution
€ 2 683 635,00
Address
14-16 BOULEVARD POISSONNIERE
75009 PARIS
France

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SME

The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.

Yes
Region
Ile-de-France Ile-de-France Paris
Activity type
Private for-profit entities (excluding Higher or Secondary Education Establishments)
Links
Total cost
€ 2 784 340,00

Participants (16)