Optimal treatment for patients with solid tumours in Europe through Artificial Intelligence

Call Updates

Nov 30, 2020 12:14:36 PM

An overview of the evaluation results (flash call info – IMI2 Call 23 – first stage) is now available under the Call’s “Additional documents” tab

Nov 30, 2020 11:51:27 AM

Evaluation results for stage 1 have been communicated to applicants. The thresholds applied were those indicated in the Call Conditions, i.e. threshold of 3 for each individual criterion and overall threshold of 10, applied to the sum of the three individual scores.

Oct 1, 2020 11:05:05 AM

Proposal numbers

Stage 1 submission deadline for the Call IMI2-2020-23-two-stage closed on 29 September 2020.

54 proposals have been submitted.

The breakdown per topic is:

IMI2-2020-23-04: 19

Evaluation results for stage 1 are expected to be communicated in December 2020. 

Jun 23, 2020 12:00:01 AM

The submission session is now available for: IMI2-2020-23-04(IMI2-RIA)

Jun 23, 2020 12:00:00 AM

IMI2 - Call 23: Informative webinars to applicants

Optimal treatment for patients with solid tumours in Europe through Artificial Intelligence

ID: IMI2-2020-23-04
Type of action: IMI2-RIA Research and Innovation action
Deadline Model: two-stage
Opening: 23 June 2020
Deadline: 29 September 2020 17:00:00 Brussels time
2nd stage Deadline: 17 March 2021 17:00:00 Brussels time

Horizon 2020

Work programme year: H2020-JTI-IMI-2020
Call name: H2020-JTI-IMI2-2020-23-two-stage
Call ID: H2020-JTI-IMI2-2020-23-two-stage

Specific Challenge:

Demands of cancer care in Europe continue to increase significantly, with the number of incident cancer cases in Europe projected to increase by 14.1% by 2030. This leads to a growing demand for innovative cancer treatments among patients, payers, physicians, and society. At the same time, the understanding of the complex biology of cancer is growing, and as a result, pharmaceutical companies are developing a multitude of new therapeutic agents.

This trend for new, effective therapies creates more treatment options for patients. However, it confronts physicians with an increasingly expanding number of potential therapeutic options, which each need to be understood and adopted effectively. To become familiar with the huge volume of available information, physicians need to learn continuously about medical guideline changes and marketed treatments. In conclusion, future decision-making processes will become ever-more complex, with the potential outcome of sub-optimal or even incorrect treatment choices being made. Furthermore, some patients have disease characteristics for which evidence of guideline recommendations is scarce and physicians lack information about real-world treatment outcomes. Hence, the challenges to be addressed are assisted guideline-based decision-making and the discovery of knowledge about treatment outcomes in real-world settings. As the latter challenge requires analysis of large data sets, the application of Artificial Intelligence (AI) will be a key technology.

Please refer to Call topic text.

Scope:

The scope of this call topic is to establish guideline-based decision support and platform solutions to generate knowledge discovery for breast, lung and prostate cancer with applicability to other indications, in several European (EU member states and H2020 associated countries) ‘model’ regions. The funded action will focus only on breast, lung and prostate cancer. These indications show a high number of cases per year, a high, unmet medical need, multiple available therapeutic options and a fast-evolving treatment environment. Expansion to other indications is not part of the funded action but a proposed solution should allow for expansion afterwards. The three core objectives of this call topic are as follows:

Objective 1: Establish a guideline-based decision support for prioritised indications

Objective 2: Establish a structured and interoperable data platform to unlock real-world-data potential in an oncology network

Objective 3: Leverage the real-world-data gathered by the action to establish an AI-knowledge base and support treatment decisions for prioritized indications.

Please refer to Call topic text.

Expected Impact:In their proposals, applicants should describe how the outputs of the project will contribute to the following impacts and include wherever possible baseline, targets and metrics to measure impact.

An explainable AI-based knowledge discovery platform should enable the development of data-driven solutions with the goal to sustainably improve oncologic treatments throughout the EU and beyond;
The results obtained from these model regions are expected to be of relevance to countries with different socioeconomic backgrounds;
The platform should allow oncologists to save valuable time due to the automatic data gathering and facilitated guideline-based assessment;
In addition, physician-patient communication and shared decision making should be supported which might improve proactive therapy involvement to accomplish increases in individual quality of life as well as overall patient satisfaction;
The platform may also allow research questions from various stakeholders to be answered through data analysis and data pooling as well as data extraction. Besides overall survival, this could include real-world quality of life (QoL) and safety evaluations of new therapies as well as novel combinations under real world conditions. This can potentially contribute to value-based healthcare assessments at EU level;
The solutions provided by a public-private consortium will significantly benefit European society: patients receive optimal personalised treatment; physicians are supported in complex decision-making processes; and payers as well as pharmaceutical companies receive information about real world treatment outcomes as a foundation for value-based healthcare approaches;
The topic is well aligned with the EU Commission’s strategy to develop a European Health Data Space and Europe’s Beating Cancer Plan.