Prostate Cancer (PCa) is the second leading cause of cancer, among men in Europe. There are currently major unmet needs in this field, such as insufficient knowledge on risk factors that contribute to PCa and on patient characteristics (including genetic profiles) that could facilitate patient stratification. Finally, there is lack of meaningful engagement of all key stakeholders, while the knowledge currently gained from clinical practice and real life data is not being fed back into PCa patients’ care pathways. There is thus a need for better definition of PCa across all stages, improved patient’s stratification at diagnosis, and standardisation of PCa-related outcomes based on real life data. PIONEER’s unique dual approach is to first identify critical evidence gaps in PCa by respected Key Opinion Leaders, and then embark on a research priority setting exercise that reflects the needs of all key stakeholders in PCa management. To achieve this, PIONEER has brought together comprehensive datasets that consists of the most relevant prostate clinical trials and registries, large epidemiological cohorts, electronic heath records, and real-life data from different European (and non-European) patient populations. These unique data sets will be integrated, standardised, harmonised and analysed using approaches that are built on our experience of similar previous IMI projects i.e EMIF, and eTRIKS, and analysed using a unique set of methodologies and advanced analytics methods (OMOP, eHS). PIONEER has already performed a first PCa research priority setting survey, where major stakeholders were asked to identify the current unmet needs in PCa. The five most important open questions will be used as pilot studies to verify PIONEER’s research framework. As such, PIONEER’s deliverables will be outcome-driven, value-based and patient-centric, and relevant to all key stakeholders, as they would have been meaningfully involved from the inception of the project.

VICT3R, a public-private partnership running under the European Innovative Health Initiative, aims to significantly reduce the number of animals used in experimental studies performed during the nonclinical drug and chemical safety evaluation by replacing the animals of the concurrent controls groups (CCGs) with Virtual Control Groups (VCGs). These VCGs will be generated by means of state-of-the-art statistical or artificial intelligence (AI) approaches that optimally exploit the wealth of historical data from control animals accumulated over decades by pharmaceutical companies and other relevant industrial and academic sectors. The VCG concept was conceived and prototyped during the recently finished eTRANSAFE IMI2 project for its application in the nonclinical safety assessment of the pharmaceutical industry. A preliminary evaluation of the VCG concept carried out in the eTRANSAFE project demonstrated that it is generally feasible, yet scientifically and operationally challenging and must therefore be refined before its adoption for regulatory hazard and risk assessment. The main challenges consist of adequate data collection and curation, identification of key variables to achieve optimal matching between VCGs and CCGs, and validation of procedures including compliance with Good Laboratory Practice (GLP). These challenges will be systematically tackled in VICT3R for achieving the full development and regulatory acceptance of the VCG concept. VICT3R will collect, curate and analyse large data sets of control animals from different species to produce a large high-quality database. The database will be made available to VICT3R partners, regulators, and policy makers with the purpose to allow maturation of the VCG concept and to prove its validity, reproducibility and robustness. While VICT3R will be primarily focused on repeated dose toxicity studies, the extension of the VCG concept to other types of studies involving animals will also be tackled. VICT3R will promote that its database and software platform is maintained and expanded long term.