Abstract
Research activities focus on the development of optical biosensors for integration into organ-on- chip devices, aiming to enable real-time monitoring of key physiological and biochemical parameters such as pH, oxygen, and cytokines. The approach involves the use of microfluidic technologies and miniaturized optical components to create platforms capable of providing continuous and quantitative data without interfering with tissue model functionality. Sensor integration within the chips is designed to ensure compatibility with the biological environment and support applications in pharmacology, toxicology, and personalized medicine. Particular attention is given to optimizing the sensitivity and selectivity of the sensors, as well as their ability to operate under dynamic and complex conditions typical of in vitro biological systems. These research efforts aim to enhance the predictive value of organ-on-chip models, making them increasingly reliable tools for studying cellular and tissue responses
Objectives
- Objective 1 - To design and fabricate optical biosensors for the real-time detection of pH, oxygen, and cytokines within organ-on-chip platforms
- Objective 2 – To integrate the developed biosensors into microfluidic devices while ensuring biocompatibility and minimal interference with tissue models
- Objective 3 – To validate sensor performance under dynamic biological conditions, aiming to support applications in drug screening, toxicology, and personalized medicine
Collaborators
- CNR IMM
- CNR NANOTEC
- Università del Salento
Key 5 publications
- 1. Guarino et al. Controlling Endotoxin Contamination in PDMS-Based Microfluidic Systems for Organon-Chip Technologies, Polymer Testing 2025 in press
- 2. Colombelli et al. “Rational Design and Optimization of Plasmonic Nanohole Arrays for Sensing Applications, Chemosensors 2024, 12, 157
- 3. Rella et al., Maximizing Fluorescence Enhancement in Metal Nanoantenna Arrays for efficient bioanalytical devices proceeding EPJ Web of Conferences 309, 05009 (2024) EOSAM 2024
People
- Maria Grazia Manera
- Roberto Rella
- Daniela Lospinoso
- Valentina Arima
- Vita Guarino
- Giovanni Montagna