Multiparametric Bioresorbable Sensor for Doxorubicin Detection via Molecularly Imprinted Synthetic Receptors
Articolo
Data di Pubblicazione:
2026
Citazione:
Multiparametric Bioresorbable Sensor for Doxorubicin Detection via Molecularly Imprinted Synthetic Receptors / Corsi, M; Di Giulio, T; Vandini, E; Ibrar Asif, M; Daini, E; Vilella, A; Leo, G; Ottani, A; Malitesta, C; Giuliani, D; Mazzotta, E; Barillaro, G.. - In: ADVANCED SCIENCE. - ISSN 2198-3844. - (2026), pp. 1-15. [10.1002/advs.202524369]
Abstract:
Monitoring chemotherapeutic drug concentrations directly at the tumor site remains a critical unmet need in oncology, as conventional pharmacokinetic assessments based on systemic circulation fail to capture the spatial and temporal heterogeneity
of drug distribution within solid tumors. Here, we report a bioresorbable, multiparametric optical sensor designed for the in
situ detection of the chemotherapeutic agent doxorubicin. The sensor integrates a nanostructured porous silica scaffold with a molecularly imprinted polymer (MIP) synthetic receptor that provides shape- and chemistry-selective recognition of doxorubicin
molecules. Molecular binding events are transduced through two orthogonal optical signals: i) shifts in effective optical thickness
and ii) fluorescence intensity changes, enabling accurate and self-validating quantification across clinically relevant concentration ranges. The sensor operates reliably in serum with a limit of detection as low as 0.1 µg/mL, and exhibits reversible performance
with minimal signal drift ( < 15.3%) over 12 weeks —consistent with standard chemotherapy regimens. In vivo implantation studies
in mice confirm biodegradation and biocompatibility, with no evidence of local or systemic toxicity. This platform introduces a versatile strategy for multiparametric, bioresorbable chemical sensing using MIP synthetic receptors, establishing a foundation for future implantable diagnostics in precision chemotherapy.
Tipologia CRIS:
Articolo su rivista
Elenco autori:
Corsi, M; Di Giulio, T; Vandini, E; Ibrar Asif, M; Daini, E; Vilella, A; Leo, G; Ottani, A; Malitesta, C; Giuliani, D; Mazzotta, E; Barillaro, G.
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