Insomnia O’ clock: new technology to insomnia detection algorithm

Overview

Project Summary

Insomnia, a widespread and complex sleep disorder, poses challenges for accurate diagnosis due to its reliance on self-reported symptoms and diverse symptom presentations. This complexity, along with comorbidities with other conditions, hampers the identification of biomarkers. Leveraging bioinformatics and machine learning, we have pinpointed blood-based molecular markers differentiating insomnia patients from healthy individuals. Our aim is to develop InsomniaO’clock, a highly sensitive and specific algorithm, for insomnia diagnosis and disease subtype assessment. Compared to self-reported complaints, the InsomniaO’clock algorithm has the potential to provide faster information regarding diagnosis, severity and better accuracy.This innovative tool aims to improve health, clinical quality and safety to reduce insomnia burden alleviating long waiting lists and reducing diagnosis costs in public and private hospitals, enhancing diagnostic accuracy and patient care.

Main Goals

Our goal is to establish a highly sensitive and specific algorithm the InsomniaO’clock, based on the set of clock-related biomarkers identified in an accessible biological fluid (blood). With the support of the Fundación MAPFRE, we intend to generate an innovative tool that will contribute to better diagnostic accuracy which is beneficial to the patient's quality of life and will have social and economical impact, as most of the expenses attributed to insomnia are due to high rates of work absenteeism, loss of productivity and increased health care utilization.

Project Details