FluiDx-AD is developing a complementary suite of three minimally invasive in vitro diagnostic tests for Alzheimer’s disease (AD) based on biomarkers measurable in saliva, plasma, and blood cells. Together, these assays are designed to support the full diagnostic pathway, from early population-level risk screening to confirmatory diagnosis and treatment-related risk stratification.
During the first project period, several technical and scientific progress has been achieved.
A secure central FluiDx-data infrastructure was established to integrate clinical information and biomarker measurements from multiple cohorts, resulting in a large multi-site dataset. This resource provides a robust foundation for biomarker discovery, assay optimisation, and validation studies.
Several advances were made in the development and optimisation of the three diagnostic systems.
- For SalivaDx-AD, protocols for saliva collection, biomarker extraction, and ultrasensitive detection of AD-related proteins were established, together with documented analytical performance, stability, and usability characteristics.
- For PlasmaDx-AD, assay sensitivity and robustness were substantially improved through optimisation of electrochemiluminescence-based immunoassays, enabling reliable detection of low-abundance biomarkers and evaluation of candidate diagnostic panels using large biobank datasets.
- For BloodCellDx-AD, protocols for assessing peripheral amyloid-β clearance capacity were refined, demonstrating reproducible performance and preparing the assay for evaluation as a stratification tool for treatment-related risk.
Across all platforms, standard operating procedures were defined, analytical characteristics documented, and protocols for proof-of-concept studies, reference range determination, and clinical validation were completed
Collectively, these achievements mark a transition from early research concepts toward clinically evaluable diagnostic tools. The project has established the necessary scientific foundations, technical methodologies, and data resources to support large-scale validation and future regulatory development of minimally invasive diagnostics for Alzheimer’s disease.