New IMI Calls for proposals | Update April 2020
The Innovative Medicines Initiative (IMI) is an EU public-private partnership that funds health research and innovation. IMI projects are accelerating the medicines development process, generating new scientific insights, and developing resources for open use by the research community. IMI does this by facilitating collaboration between the key players involved in healthcare research, including universities, the pharmaceutical and other industries, small and medium-sized enterprises (SMEs), patient organisations, and medicines regulators. IMI is a partnership between the European Union (EU) and the European pharmaceutical industry, represented by the European Federation of Pharmaceutical Industries and Associations (EFPIA).
Overview of new calls
IMI plans to launch two new calls, Call 22 and 23 on June 23, 2020. The draft texts have just been published. Please note that the final call texts can change considerably as compared to the current drafts!
IMI2-Call 22 is single-stage and meant for proposals designed to support research activities that will build on, and add value to, results from certain ongoing IMI2 projects. IMI2 – Call 23 is a standard, two-stage Call for proposals. Topics are listed below.
Eligibility criteria for IMI projects
- Consortia consisting of academic parties, SMEs and/or non-profit organisations can apply.
- Consortium partners that are based in one of the EU member states or associated countries are eligible for funding. Legal entities based in a third country can only receive funding under certain conditions.
- Consortia should consist of at least three independent legal entities, based in at least three EU member states or associated countries.
- The funding rate is 100%.
- Further eligibility conditions, funding rates and technology readiness levels follow the Horizon 2020 rules.
- Deadlines for these calls will be published at a later stage.
IMI Call 22 and 23 topic overview
Returning clinical trial data to study participants within a GDPR compliant and approved framework
A large amount of high-quality health data is collected during clinical studies (interventional and non-interventional). However, beyond the immediate objectives of the study, these valuable data are not used to the extent they merit. Objectives of this calls are:
- to align local and pan-European implementations and best practice for handling personal data protection regulations in order to harmonise the legal framework applicable to medical research;
- and to deliver a pan-European prototype process to return clinical trial data to study participants.
Modelling the impact of monoclonal antibodies and vaccines on the reduction of antimicrobial resistance.
This topic is part of IMI’s Antimicrobial Resistance (AMR) Accelerator programme.
The discovery and development of new preventions and treatments to address antimicrobial resistance (AMR) is an undisputed European and global challenge. Vaccines and monoclonal Antibodies (mAb) may reduce AMR. However, individual vaccine developers, mAb developers or health authorities do not have the resources and the full expertise required to make a realistic and comparable assessment of the use of the different products on the reduction of AMR. This could be possible through the use of a mathematical model. The goal of the project is thus to develop a framework for setting up antimicrobial resistance (AMR)-focused economic evaluations of vaccines and mAbs.
A platform for accelerating biomarker discovery and validation to support therapeutics development for neurodegenerative diseases
Neurodegenerative diseases, including Alzheimer’s disease (AD) and Parkinson’s disease (PD), represent a huge economic and societal burden. Although significant amounts of data and samples have been collected that could be used to accelerate biomarkers discovery and development for these diseases, this data is hard to access by the research community. The objectives of this call are therefore to create a set of agreed principles to enable sharing and access to data and samples taking into consideration all relevant barriers (e.g. General Data Protection Regulation (GDPR), legal, intellectual properties (IP), ethical, regulatory, societal).
Furthermore, a network should be established that can house high quality data and samples, which could have federated and centralised elements. The overall solution has to be interoperable (e.g. with other global data platforms), scalable and suitable for a broad variety of both data types (including digital), and of samples, from public and private (e.g. proprietary clinical trials) sources, whether they be part of the consortium or provided from external donors.
Optimal treatment for patients with solid tumours in Europe through artificial intelligence
The number of incident cancer cases in Europe is projected to increase by 14.1% by 2030. This leads to a growing demand for innovative cancer treatments. At the same time, the complex biology of cancer is getting more deciphered and as a result pharmaceutical companies are developing a multitude of new therapeutic agents such as novel kinase inhibitors, immunotherapy combinations, and cell therapies.
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 ‘model’ regions.
Shortening the path to rare disease diagnosis by using new born genetic screening and digital technologies
There are over 7000 rare diseases (RDs) resulting in 30 million patients in Europe and 250 million globally. Less than 10% of RD patients receive treatment and only 1% are managed using an approved treatment in Europe. There is a need for a strategic approach to address some of the major challenges faced by the RD Community. The overall objective of this call is to shorten the path to RD diagnosis by using new-born / paediatric (infants during their first weeks of life) genetic screening; and, via application of advanced digital technologies that enable rare disease suspicion / identification. The latter might require consolidation of existing fragmented efforts.
Behavioural model of factors affecting patient adherence
Patient non-adherence to prescribed treatment is an issue that affects patient health outcomes and healthcare system costs worldwide. It is estimated that it contributes to 200.000 premature deaths in the EU each year. The aims of this call are, to
- develop a comprehensive understanding of the factors which affect patient needs and adherence;
- identify the most significant factors;
- evaluate existing models and then either create an open access behavioural model or further develop an existing model;
- collect additional real-world data to refine the model;
- and to provide tools that will enable healthcare stakeholders to cost-effectively develop and implement solutions to address patient needs and improve adherence rates.
Restricted Call to maximise impact of IMI2 JU objectives and scientific priorities
This topic will be opened under call 22
Certain IMI2 JU topics, launched under IMI2 JU Calls for proposals that are now closed, anticipated in their corresponding Annual Work Plans the need for a stepwise approach. The scope of the restricted Call will be to support further research activities in those exceptional cases where it is necessary to enable successful consortia to build on the achievements of their initial action and move onto the next step of the challenge. This call is limited to the initial consortia of actions funded under topics published in the IMI2 JU Annual Work Plans of 2014, 2015 and 2016.
More information about IMI our our services?
Curious to discover whether your research activities are in line with the call requirements? Or do you need last-minute support for your IMI-call 18 proposal? The specialist consultants at Hezelburcht are experienced in developing and writing these types of applications. We look forward to supporting and advising you in your grant funding endeavours. Please contact us for more information!