We bring hope to
Cancer in children is rare but when it happens, clinically prescribed treatment options are not always as efficient as one would hope. Of those that are cured, a substantial proportion suffer long-term serious health consequences from the intensive treatments that are currently required. A major reason for cancer being so difficult to treat effectively is that cancer cells undergo many random changes, which means that each cancer has an essentially unique combination of molecular characteristics. To address this problem, it is important to develop ways of specifically tailoring treatment combinations for the molecular profile of each individual cancer, to maximize cures and to minimize short- and long-term treatment side-effects.
The project team 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. We 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. While the ever-present complexities of cancer continue to challenge our scientific community, it is reassuring that European projects like iPC are using the latest technology and brightest minds to find solutions which, in turn, usher in better patient care.
Reference Number: 826121
Programme type: Horizon 2020
Programme acronym: H2020-ICT-2018-2
Project Start: 01.01.2019
Cost and Funding
Costs: € 15.066.525,00
Funding: 97,89% EU-funded
While the ever-present complexities of cancer continue to challenge our scientific community, it is reassuring that European projects, such as iPC are using the latest technology and brightest minds to find solutions, which, in turn, usher in better patient care. To sum up, 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.
Mission and Objectives
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 our goals, we have assembled an interdisciplinary team consisting of basic, translational, and clinical researchers—all amongst the leaders in their respective fields—and established strong relationships with European Centres of Excellence, patient organizations, and clinical trials focus on personalized medicine for our 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.
Data collection and generation
Big data analysis of available data sources
Network-based meta-analysis of mulit-omics and text-mined data
Blending machine learning and mechanistic models
Mechanistic and agent-based models
Transcriptomic models for clonal deconvolution, intratumoural heterogeneity and non-coding elements
Mulit-omics and metabolomic models for drug discovery
Use cases and validation
Communication, dissemination, exploitation and training
Ethics and legal aspects, project, risk and innovation management