Open Call SC1-DTH-07-2018: Exploiting the Full Potential of in-Silico Medicine Research for Personalised Diagnostics and Therapies in Cloud-Based Environments

European CommissionThe progress in computer modelling and simulation applied in disease management is a European strength and various Decision Support Systems have been developed for different medical disciplines. While the market is developing today, addressing the need of more precise and personalised diagnostics and treatments, the proposed software tools and platforms often need to further conquer visibility and trust from users and investors to get implemented in the routine clinical practice. The access of researchers to high quality big data and in particular to clinical multi-disciplinary data is crucial for validating the use of new tools and platforms in the right practice context.

Through its new initiatives on digital health and care within the Digital Single Market policy, the European Commission aims at leveraging the potential of big data and high performance computing for the emergence of new personalised prevention and treatments for European citizens. The European Cloud Initiative will facilitate the access of researchers to the newest data managing technologies, High Performance Computing facilities to process data and to a European Open Science Cloud list of ICT services while ensuring the appropriate data safety and protection.

Shared infrastructures, data and services in open cloud-based environments will stimulate the virtual complex experimentations in medicine and the link between researchers and healthcare practitioners, for their common benefit.

Scope

Proposals are expected to develop and validate software tools and devices for diagnostic or treatment based on computational modelling and simulation applied in biology and physiology. The solutions should enable decision making in complex situations and contribute to a more precise and personalised management of diseases in order to reduce the burden of non-communicable diseases, such as cancer.

Computer-based decision making can apply to the choice of drugs, devices or other biomedical products, procedures, interventions, in vitro and in vivo diagnostics methods and tools, or combined diagnostics and treatments. In order to ensure access to large multi-disciplinary high quality data sets and diminish the shortage of relevant data, the teams are expected to use shared infrastructures and e-infrastructures, building on existing capacity and expertise and linking where possible with the European initiatives that manage databases relevant for personal health, such as BBMRI, ELIXIR or EATRIS, as well as with Centres of Excellences for computing applications in the area of biomedicine and bio-molecular research as appropriate. They should demonstrate access to the sufficient and relevant clinical data needed for advanced validations. The work should build on - and contribute to reusable data and computer models. Teams are encouraged to use EOSC services as appropriate and possible.

The Commission considers that proposals requesting a contribution from the EU of between EUR 10 and 15 million would allow this specific challenge to be addressed appropriately. Nonetheless, this does not preclude submission and selection of proposals requesting other amounts. Expected Impact:

The proposal should provide appropriate indicators to measure its progress and specific impact in the following areas:

  • Better translation of big and multi-disciplinary data into predictors for medical outcome and personalised decision making;
  • New digitised trusted diagnostic and treatment tools, and contributing to digitising clinical workflows;
  • Improved disease management, demonstrated in the specific disease context;
  • Links to other European research infrastructure projects and networks operating in related domains;
  • Contribution to the emergence of a European Data Infrastructure for personalised medicine in the context of the DSM, notably by providing reusable data and computer models for personalised prevention and health treatments;
  • Better data quality, interoperability and standards.

Deadline: 24 April 2018 17:00:00

Deadline Model: single-stage

Type of action: RIA Research and Innovation action

For topic conditions, documents and submission service, please visit:
http://ec.europa.eu/research/participants/portal/desktop/en/opportunities/h2020/topics/sc1-dth-07-2018.html

PS: Find your partners or consortia preparing a project proposal
If you are working on Horizon 2020 research project proposals and you would be interested in a SME partner from Germany, please contact us, we are happy to share our experience, expertise and knowledge. If you need help to identify a potential partner with particular competences, facilities or experience, please join and explore our project, (HEALTH IT) SPACE, at www.healthitspace.eu.

Most Popular Now

Open Medical Works with Moray's Dig…

Open Medical is working with the Digital Health & Care Innovation Centre’s Rural Centre of Excellence on a referral management plan, as part of a research and development scheme to...

Generative AI on Track to Shape the Futu…

Using advanced artificial intelligence (AI), researchers have developed a novel method to make drug development faster and more efficient. In a new paper, Xia Ning, lead author of the study and...

AI could Help Improve Early Detection of…

A new study led by investigators at the UCLA Health Jonsson Comprehensive Cancer Center suggests that artificial intelligence (AI) could help detect interval breast cancers - those that develop between...

AI-Human Task-Sharing could Cut Mammogra…

The most effective way to harness the power of artificial intelligence (AI) when screening for breast cancer may be through collaboration with human radiologists - not by wholesale replacing them...

Reorganisation, Consolidation, and Cuts:…

NHS England has been downsized and abolished. Integrated care boards have been told to change function, consolidate, and deliver savings. Trusts are planning big cuts. The Highland Marketing advisory board...

Siemens Healthineers infection Control S…

Klinikum Region Hannover (KRH) has commissioned Siemens Healthineers to install infection control system (ICS) at the Klinikum Siloah hospital. The ICS aims to effectively tackle nosocomial infections and increase patient...

AI Tool Uses Face Photos to Estimate Bio…

Eyes may be the window to the soul, but a person's biological age could be reflected in their facial characteristics. Investigators from Mass General Brigham developed a deep learning algorithm...

Philips Future Health Index 2025 Report …

Royal Philips (NYSE: PHG, AEX: PHIA), a global leader in health technology, today unveiled its 2025 Future Health Index U.S. report, "Building trust in healthcare AI," spotlighting the state of...

AI-Powered Precision: Unlocking the Futu…

A team of researchers from the Department of Diagnostic and Therapeutic Ultrasonography at the Tianjin Medical University Cancer Institute & Hospital, have published a review in Cancer Biology & Medicine...

AI Model Improves Delirium Prediction, L…

An artificial intelligence (AI) model improved outcomes in hospitalized patients by quadrupling the rate of detection and treatment of delirium. The model identifies patients at high risk for delirium and...

Building Trust in Artificial Intelligenc…

A new review, published in the peer-reviewed journal AI in Precision Oncology, explores the multifaceted reasons behind the skepticism surrounding artificial intelligence (AI) technologies in healthcare and advocates for approaches...

SALSA: A New AI Tool for the Automated a…

Investigators of the Vall d'Hebron Institute of Oncology's (VHIO) Radiomics Group, led by Raquel Perez-Lopez, have developed SALSA (System for Automatic Liver tumor Segmentation And detection), a fully automated deep...