Intensified continuous processes are a key innovation of the last decade for the production of high quality, high value and customer-specific products at competitive prices in a sustainable fashion. To realize the potential of this technology, key steps must be made towards long-term stable, tightly controlled and fully automated production. The goal of the CONSENS project is to advance the continuous production of high-value products meeting high quality demands in flexible intensified continuous plants by introducing novel online sensing equipment and closed-loop control of the key product parameters. CONSENS will focus on flexible continuous plants but the results will be transferable also to large-scale continuous processes. The research and development is driven by industrial case studies from three different areas, spanning the complete value chain of chemical production: complex organic synthesis, speciality polymers, and formulation of complex liquids. Innovative PAT technology will be developed for online concentration measurements (mid-resolution process NMR), for the online non-invasive measurement of rheological properties of complex fluids, and for continuous measurements of fouling in tubular reactors. New model-based adaptive control schemes based on innovative PAT technology will be developed. The project results will be validated in industrial pilot plants for all three types of processes, including validation in production containers that have been developed in the F3 Factory project. Further, methods for sensor failure monitoring, control performance monitoring and engineering support for PAT-based solutions will be developed. The exploitation of the new technologies will be facilitated by a tool for technology evaluation and economic impact assessment. A Cross-sectorial Advisory Board supports the transfer of PAT technologies and adaptive control to neighboring sectors of the European processing industry.

ENLIGHT-TEN+ is a European Network Linking Informatics and Genomics of Helper T cells in Tissues: A crucial missing link in our current research environment is the lack of qualified individuals who possess the immunology skills to recognise and define important scientific questions amenable to -omics approaches, and also the bioinformatic expertise to interrogate and interpret the resulting Big Data appropriately. Thus, our mission is to provide cross-disciplinary training for a new generation of enthusiastic researchers who have in-depth understanding of T cell immunology and are also capable to handle large datasets. Our network of 15 beneficiaries from 10 European countries combines expertise on T cell biology with state-of-the-art technologies generating Big Data, cutting-edge bioinformatic tools including artificial intelligence, preclinical models and samples from patient cohorts. ENLIGHT-TEN+ will identify microenvironmental factors shaping the functional properties of tissue-resident T cells, which offer important therapeutic potential in various human autoimmune diseases, making them a key target for pharmaceutical companies. 15 early-stage researchers (ESRs) will be empowered to push our knowledge of tissue-resident T cells beyond the state-of-the-art which will enable the identification of novel biomarkers and support the development of advanced therapeutic concepts. The generation of Big Data is an emerging and challenging field, and there is high demand in both the academic and industrial sector for researchers to be able to analyse, integrate and exploit this rich source of information. ENLIGHT-TEN+ will combine individual strengths of innovative laboratories and enterprises from complementary disciplines to provide unique interdisciplinary training as an ideal stepping-stone for the ESRs to enter and strengthen Europe’s academia as well as pharmaceutical and bioinformatics companies, thereby placing them at the forefront of this emerging field.

The PREFER project will deliver an overview and evaluation of preference elicitation methods to be applied in the entire drug life cycle, i.e. in the early stages of identifying medical needs, in clinical testing, to guide decisions on reimbursement and to make decisions on withdrawal of drugs from the market. A broad array of (combinations of) patient preference methods will be tested prospectively in a large number of case studies. The availability of large patient cohorts will enable to test new methods or deviations from existing methods in a randomized manner, by comparing well-known methods with newer ones. The use of simulation studies will both contribute to smarter design of case studies and to exploring the sensitivity of outcomes of preference studies. Based on discussions with a broad representation of stakeholders e.g. patients, patient organisations, regulatory authorities, HTA bodies and reimbursement agencies, suitable methods will be tested and their contributions to improved decision making will be discussed in recommendations adapted to the needs of all relevant stakeholders. The recommendations from PREFER are expected to lead to changed practices, in that industry will routinely assess whether a preference study would add value at key decision points in the medicinal product life cycle and, if so, implement patient-preference elicitation studies according to the PREFER project recommendations. The PREFER consortium consist of 16 industry partners and 16 academic and SME members including representation from academia, patient organizations, HTA bodies, reimbursement agencies, and project management.