Imagine a smart system that acts like an early warning signal for moms-to-be. It uses a phone app to spot signs of depression early and helps doctors track a mother's health in real-time. By understanding how a mother's mood affects the baby's brain development, it helps create better treatments to ensure both mom and baby have a healthy start.
Up to 30% of pregnant women suffer from depression, often going undetected due to stigma or lack of screening, which leads to poor mental health outcomes for both the mother and the child.
A digital platform consisting of a mobile App for biomarker and lifestyle data collection and a connected dashboard for clinician monitoring.
If you are a health app developer dealing with low user engagement in prenatal care — this project developed a digital platform and mobile App that collects AI-based biomarkers and lifestyle data. This allows for early screening and personalized treatment paths for pregnant women.
If you are a pharma company dealing with a lack of targets for perinatal mental health drugs — this project used rodent and fish models to identify neurobiological mechanisms. This provides new targets for developing novel medications or repurposing existing ones.
If you are a clinic owner dealing with undetected maternal depression in 30% of patients — this project developed a clinician dashboard. This tool enables early detection and monitoring of depressive symptoms to improve patient outcomes.
Based on available project data, the specific commercial pricing or implementation cost is not provided, though the EU contributed EUR 8,925,241 to the research and development phase.
Yes, the project already combines data from large cohorts of pregnant women and offspring around the world, suggesting a design intended for diverse populations.
Based on available project data, specific licensing terms are not mentioned, but the project involves 17 partners including 2 industry entities and 1 SME.
The system integrates via a dedicated dashboard for clinicians, which connects to data collected by a mobile phone App used by the patients.
The project period runs from 2022-11-01 to 2026-10-31, indicating that full results and final tools will be available toward the end of 2026.
The consortium is heavily academic, with 13 universities and 2 other non-profit entities, but it maintains a 12% industry ratio through 2 industry partners, including 1 SME. This structure suggests a strong focus on deep scientific validation (epigenetics and animal models) while ensuring a path toward a digital product via the industry members.
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