WP1 established the biological and engineering foundations. SAP screening showed that synthetic and hybrid systems were the strongest absorbent candidates, while antibody-antigen validation confirmed detection routes for IL-6, IL-8 and IL-10, and later optimized detection of IL-4 and TGF-beta1 using improved antibodies. For genetic detection, CCDC170 rs1971256 was selected because it met the targeting constraints for Cas9-sgRNA recognition, and in vitro cleavage experiments confirmed sequence-specific binding and cleavage behaviour. WP2 delivered the core absorbent and textile material platform. PMAA-EDGMA, especially the 4 per cent EDGMA formulation, showed strong absorption and retention performance. Synthetic and hybrid SAPs exhibited lower water loss than a commercial SAP reference and retained better performance in saltwater conditions. Cellulose-based electrospun membranes were fabricated with controlled morphology, high porosity, tunable absorbency, and mechanical integrity, as well as degradation behaviour, creating a realistic material basis for integration into the sensing pad. Multiphysics-related approaches were also developed to recapitulate the electrospinning process structure. WP3 advanced in-situ biosensing. Graphene-based inkjet-printed electrodes were developed using conductive graphene and Graphene Acid functional layers. A TGF-beta1 electrochemical impedance sensor showed a concentration-dependent response from 0 to 300 ng/mL, consistent with a single-site antigen-antibody binding model. In parallel, a paper-based glucose fuel cell with molecularly imprinted polymer recognition for IL-6 generated electrical output and showed a linear response in buffer between 3.0 x 10^-10 and 3.0 x 10^-7 M, supporting the concept of a self-powered sensing route.
WP4 produced the strongest analytical milestone of the reporting period. CVD-graphene gFETs were redesigned to remove the internal gold gate, reducing non-specific biomolecule affinity. PBASE-based functionalization was optimized, Cas9-sgRNA immobilization was confirmed by AFM and electrical measurements, and the bioconjugated gFET/CRISPR platform selectively detected CCDC170 DNA over five orders of magnitude, with 1.34 mV/decade sensitivity, 27.5 fM LoD and 21 pM LoQ in buffer. WP5 translated the microfluidic workflow from model to prototype. Four modules were fabricated and tested for red blood cell removal, nucleated-cell sorting, nucleated-cell lysis and DNA capture/recovery. The updated DLD module used a lower cut-off diameter near 4.6 um, improving recovery of biologically relevant nucleated cells. RIPA buffer enabled complete cell lysis in the device, and early module chaining showed that RBC-depleted lysate could feed into sorting and lysis steps, with DNA yields comparable to benchtop protocols. WP6 and WP8 moved the system toward practical operation. For the wearable sensoPAD, EIS was selected as the preferred readout because of lower power and simpler signal handling. The most efficient architecture combined MAX30131-based EIS electronics, NFC communication and micro-supercapacitors, supporting a battery-less use case. For the sensoMFgFET device, electronics were designed around acquisition from 28 graphene-FET channels and wireless transmission to the cloud. Early mobile and cloud prototypes defined device discovery, data acquisition, REST/MQTT communication, NoSQL storage, authentication and future AI-enabled analytics.
WP11-WP12 strengthened the translation pathway. The project established dissemination channels, launched awareness activities, mapped exploitable results and defined market logic. By M18, communication had reached 2,472 website visits, 632 social media followers, 63,695 impressions, more than 65,000 people reached, two newsletters, 11 external events, one webinar and more than 70 promotional materials distributed or downloaded. Exploitation work identified 18 exploitable results and 14 key exploitable results, while business modelling produced eight preliminary commercialization options for the sensoPAD, sensoMFgFET, mobile/cloud platform and integrated SENSOPAD solution.
