The goal of the iPC project is to collect, standardize and harmonize existing clinical knowledge and medical data and, with the help of artificial intelligence, create treatment models for patients. Armed with these treatment models, scientists will then test them on virtual patients to evaluate treatment efficacy and toxicity, thus improving both patient survival and their quality of life.

To accomplish those goals, an interdisciplinary team consisting of basic, translational, and clinical researchers — all amongst the leaders in their respective fields — was assembled and established strong relationships with European Centres of Excellence, patient organizations, and clinical trials focus on personalized medicine for the proposed case studies.

In summary, iPC will address the critical need for personalized medicine for children with cancer, contribute to the digitalization of clinical workflows, and enable the Digital Single Market of the EU data infrastructure.

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iPC will focus on identifying effective personalized medicine for paediatric cancers and will address a multitude of challenges. To meet these challenges, a comprehensive computational effort to combine knowledge base, machine-learning, and mechanistic models to predict optimal standard and experimental therapies for each child will be proposed. iPC will produce, assemble, standardize, and harmonize accessible high-quality multi-disciplinary data and leverage the potential of Big Data and HPC for the personalized treatments of European citizens. 

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Only publications related to the H2020 iPC Project will be curated.

April 18, 2019
Harvesting API:
OAI-PMH Interface

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