The overall aim of LIQBIOPSENS project is the further development and validation in real settings of a novel diagnostic platform for the early and fast detection of ctDNA and their KRAS and BRAF mutations associated to colorectal cancer through blood samples. The main features of LIQBIOPSENS are: reliability (detection rates vary from 95–100 %), low-cost (40-50 € per sample analysis), sensitivity (in the zM range), multiplexing capabilities (analysis of 27 KRAS and BRAF mutations simultaneously), short analysis time (30-60 min.), user-friendly interface and flexibility. Solution proposed by the LIQBIOPSENS project relies on the multidisciplinary integration of different Key Enabled Technologies: microelectronics, microfluidics, nanomaterials and genomics. In particular, LIQBIOPSENS platform is based on the integration of two novel complementary technologies. On the one hand, the revolutionary DGL© technology property of DestiNA Genomics Ltd, capable of delivering faster, more error-free detection of nucleic acids and their mutations than current enzyme-based detection systems, making 'false positive' results a thing of the past. On the other hand, a novel high resolution acoustic wave microsensor technology property of AWSensors, that allows an accurate, inexpensive, label-free, direct and real time transduction method to quantitatively evaluate the results of the application of the above mentioned DGL© technique.

Breast cancer is the most common type of cancer affecting woman in the EU. Multidisciplinary Breast Units (BUs) were introduced in order to deal efficiently with breast cancer cases, setting guideline-based quality procedures and a high standard of care. However, daily practice in the BUs is hampered by the complexity of the disease, the vast amount of patient and disease data available in the digital era, the difficulty in coordination, the pressure exerted by the system and the difficulty in deciding on cases that guidelines do not reflect. DESIREE aims to alleviate this situation by providing a web-based software ecosystem for the personalized, collaborative and multidisciplinary management of primary breast cancer (PBC) by specialized BUs. Decision support will be provided on the available therapy options by incorporating experience from previous cases and outcomes into an evolving knowledge model, going beyond the limitations of the few existing guideline-based decision support systems (DSS). Patient cases will be represented by a novel digital breast cancer patient (DBCP) data model, incorporating variables relevant for decision and novel sources of information and biomarkers of diagnostic and prognostic value, providing a holistic view of the patient presented to the BU through specialized visual exploratory interfaces. The influence of new variables and biomarkers in current and previous cases will be explored by a set of data mining and visual analytics tools, leveraging large amounts of retrospective data. Iintuitive web-based tools for multi-modality image analysis and fusion will be developed, providing advanced imaging biomarkers for breast and tumor characterization. Finally, a predictive tool for breast conservative therapy will be incorporated, based on a multi-scale physiological model, allowing to predict the aesthetic outcome of the intervention and the healing process, with important clinical and psychological implications for the patients.

The main objective of GoodBerry is to provide the necessary knowledge and procedures to facilitate the development of highly productive and top quality berry fruits, even under multiple suboptimal growth conditions, at a competitive cost. The project is based on an integrative multi-actor approach, from cultivation techniques to molecular studies, aiming the development and validation of a range of tools to improve competitiveness of European berry production, and eventually the attraction and confidence of consumers. The selection of the model species can be considered as strategic since strawberry is the most important berry crop in Europe and the production of raspberry and blackcurrant are increasing strongly in recent years. The project will apply the most recent technical advances in: a) The identification of berry germplasm exhibiting advantageous balance of production vs nutritional quality throughout the EU, b) The search of innovative production systems to maintain high yield in a range of European-wide environments, c) The development of standardized and reliable analytical tools to evaluate berry production and fruit quality. As result, it is expected: a) the implementation of modern breeding strategies to accelerate the release of new berry cultivars; b) The adoption by EU-growers of high quality production systems to improve fruit quality. The proposal establishes as obligatory to disseminate and communicate the results to the scientific community, industry, the broad public and interested stakeholders user. The final impact will be to consolidate the emerging needs of high-quality berries, and to boost consumer and market confidence supported by an improved competitiveness of producers. It is a multidisciplinary, collaborative project based on complementary expertise and skills of internationally recognized berry research institutions, and highly involved key berry SMEs that will combine their effort to secure the robustness of the results.