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Machine learning software to design personalized neoantigen vaccines tailored to specific vaccine delivery systems

Project description

New software to design patient-specific cancer vaccines

Scientists expect personalised immunotherapy could cure cancer but this involves personalised vaccination – a complicated, time-consuming, costly laboratory process to target a specific case of mutation. For this reason, researchers are developing algorithms to identify immunogenic neoantigens via next generation sequencing (NGS) data from tumour samples. The EU-funded MEDIVAC project aims to support this process by applying the machine learning framework from Oncolmmunity (OI). It provides an opportunity to use several public and other databases to significantly increase the performance of the identification process for relevant neoantigens. This will bring medical science much closer to introducing a promising personalised vaccination for cancer therapy.

Field of science

  • /medical and health sciences/basic medicine/pharmacology and pharmacy/pharmaceutical drug/vaccines
  • /natural sciences/computer and information sciences/artificial intelligence/machine learning
  • /medical and health sciences/basic medicine/immunology/immunotherapy
  • /medical and health sciences/clinical medicine/cancer

Call for proposal

H2020-SMEInst-2018-2020-2
See other projects for this call

Funding Scheme

SME-2 - SME instrument phase 2

Coordinator

ONCOIMMUNITY AS
Address
Ullernchausseen 64
0379 Oslo
Norway
Activity type
Private for-profit entities (excluding Higher or Secondary Education Establishments)
EU contribution
€ 2 200 406,25