The long-term goal of MX-MAP is to develop a functional pipeline for the immune characterization of new 2D nanomaterials of MXene family, for the qualitative and quantitative assessment of the human immune compatibility and immune activity towards biomedical applications. The immune characterization of the tested materials on the basis of intrinsic physical-chemical and immunological properties, through the combination of the most innovative technologies such as single-cell mass cytometry (CyTOF), will open breakthrough perspectives for the development of new therapeutic approaches applying nanomaterials as immunomodulators, scaffolds for tissue engineering, cancer therapy, and antibacterial agents. MX-MAP will develop key chemistry and immune-based strategies for MXene medical applications. The implication of this project extends beyond the specific nanoscience program greatly advancing the engineering process of 2D materials and their use in biomedicine. The MX-MAP project involves fourteen key players in European and non-European countries, including the United States, Canada, Saudi Arabia, and three partners from Ukraine, coming from academia and SMEs. This program will provide strong support for the development of the careers of young brilliant scientists who want to grow towards an interdisciplinary vision of Science. Chemistry, biology, immunology, engineering, and cancer research are the expertise of MX-MAP. The senior team members are among the most influential scientists, including Prof. Yury Gogotsi (H-index=168) - inventor of MXenes, Prof. Klaus Ley (H-index=147) - one of the most cited immunologists worldwide, and Prof. Husam N Alshareef (H-index=99). The Consortium is perfectly balanced in terms of equal gender presence; the project Coordinator Lucia Gemma Delogu is a female, and 2 out 4 of four WP leaders are female. The project embraces a large view of inclusiveness and diversity, including countries with smaller economies such as Ukraine.

The CHARM project aims to radically transform the cancer diagnosing process and bring the emerging field of digital histopathology to the next level, introducing a novel technology for tissue analysis, capable to measure the molecular composition of the patient tissue samples and to recognize and classify the tumor in a completely label/stain-free way. The instrument, integrated with artificial intelligence (AI), will offer to histopathologists a reliable, fast and low-cost Clinical Decision Support System (CDSS) for cancer diagnosis and personalized cancer therapy. We will develop a Class C, (IVDR, In-Vitro Diagnostic Regulation) medical device consisting of a turnkey low-cost broadband Coherent Raman Scattering (CRS) microscope (enabled by our patented graphene-based fiber laser technology), named the Chemometric Pathology System (CPS), integrating an AI module based on deep learning, statistics and machine learning. The CPS will be capable of automatically analyzing unstained tissues, providing fast and accurate tumour identification (differentiating normal vs neoplastic tissues) with accuracy >98% and final tumour diagnosis prediction (differentiating and grading histologic subtypes) with accuracy >90%, thus offering to the histopathologist a decision tree compatible with existing clinical protocols but with biomolecular-based objectivity and reduced time to result (TRL6). We will develop a robust business case for the application and ensure the project continuation to higher TRLs and the final market entrance. This proposal builds on the results of the ERC POC project GSYNCOR.