ADAPFI-AGE — Confidence-Aware Multimodal Biomarker Tool for Healthy Ageing

ADAPFI is developing ADAPFI-AGE, an adaptive and confidence-aware artificial intelligence framework for analysing longitudinal multimodal biomarkers in ageing-related and chronic diseases.

The proposed technology combines molecular, clinical, physiological and functional measurements to:

• construct individual longitudinal health trajectories;
• estimate changes despite missing, noisy or heterogeneous data;
• quantify uncertainty and indicate when available evidence is insufficient;
• detect early changes and predictive biomarker patterns;
• assess response to preventive or therapeutic interventions; and
• support personalised monitoring and clinical decision support.

ADAPFI contributes expertise in adaptive state estimation, multimodal data fusion, prediction, anomaly detection, uncertainty quantification and confidence-aware digital twins.

We are seeking partners for Horizon Europe Health 2027 proposals, particularly:

• universities and research organisations specialising in ageing biology, chronic or neurodegenerative diseases;
• hospitals and clinical centres with suitable longitudinal cohorts;
• biobanks and multimodal biomarker or multi-omics laboratories;
• intervention developers and healthcare technology companies;
• experts in clinical validation, ethics, regulation and health-data governance; and
• project coordinators or consortia preparing proposals on predictive biomarkers, virtual human twins or personalised healthcare.

The initial objective is a retrospective proof of concept using an established biomarker signature and an appropriate longitudinal cohort, followed by prospective clinical validation.