Description:
Patients affected by HPA must constantly monitor plasma phenylalanine (Phe) concentrations in order to adjust diet and/or pharmacological therapy and avoid severe neurotoxic damage. The project aims to develop a demonstrator for self-testing phenylalanine levels in patients with hyperphenylalaninemia (HPA), to test its functionality, robustness, and reliability in a real operational environment, and to integrate the demonstrator into a platform based on Artificial Intelligence algorithms to support clinical follow-up and enable personalization of the therapeutic approach.
Project objective:
The objective of the project is the design and development of a biosensor for self-monitoring phenylalanine (Phe) levels. In particular, the aim is to develop a colorimetric biosensor characterized by several key features such as simplicity, rapid response, and the possibility of integration into simple and portable devices.The project seeks to advance the field of colorimetric nanobiosensors for the determination of Phe, and the resulting device would improve patients’ quality of life by enabling direct self-monitoring of Phe levels without the need to visit a specialized laboratory.
The development of a platform based on Artificial Intelligence algorithms, built using key enabling technologies, for fast, robust, and low-cost self-monitoring of patients’ Phe levels will facilitate communication between patients and clinicians at the relevant reference centers, allowing proper real-time adjustment of therapy. These activities fall within the context of what in recent years has been defined as the “IoMT, Internet of Medical Things,” which lays the foundation for what many analysts describe as a revolution in the healthcare sector.
Coordinator and involved staff:
Lead institution:
Partner institutions:
Università degli Studi di Catania, CNR-Istituto di Chimica Biomolecolare, Tinexta cyber
