BiSCUIT · Biomimetic Sensorized Barriers-on-a-Chip: Unveiling a new Generation of Market-Ready Investigation Tools

The lack of reliable in vitro pre-clinical models represents a critical aspect unanimously recognized by the scientific community as detrimental in the pathway of bringing new medications from the laboratory to the bedside: addressing this issue would provide immense benefits to drug discovery and development processes, by ethically limiting animal testing and drastically reducing costly failures in clinical trials. To date, most in vitro models fail at recapitulating the physiological microenvironment, and this often results in misleading data withdrawal. Starting from my prototype of real scale, dynamic and biomimetic blood-brain barrier model, in this project I aim at the validation of my system, after an upgrade step consisting in embedding sensing features in the platform, thus allowing a real-time evaluation of barrier formation and integrity maintenance. Characterized by microcapillary size/fenestrations and fluid flows similar to the in vivo physiological barrier, my tool will represent a drastic innovation over other well-established models in the literature and available on the market, allowing a reliable reproduction of the physiological environment and an accurate estimation of the amount of drug and/or nanomaterial concentration delivered through the barrier. Validation will be performed in relevant conditions, by implementing stroke and brain cancer models. All artificial components will be fabricated through two-photon polymerization (2pp), a disruptive mesoscale lithography technique that allows the fast fabrication of low-cost structures with resolution up to the nanometer scale, as well as great levels of scaffold reproducibility/accuracy. The proposed platform can be easily adopted in research laboratories and pharmaceutical industries as an advanced pre-clinical model, the primary biomedical applications of which consist in reliable screenings of drugs against pathologies of the central nervous system.