Heart disease is the leading cause of death in women, yet millions with chest pain suffer from ANOCA, a condition caused by dysfunction of the coronary vessels that is often missed by standard diagnostic tests. As a result, patients can face years of uncertainty and repeated hospital visits before receiving a diagnosis, while the current gold-standard CFT test is invasive, costly, painful, and limited available.
In this PhD project, you will help develop the first blood-based test for ANOCA, combining next generation sequencing, multi-omics analyses, and advanced machine learning to diagnose the disease and identify its underlying subtype from a simple blood draw. This approach could reduce diagnosis time from years to weeks, replace unnecessary invasive procedures, lower healthcare costs, and enable earlier, more personalized treatment for a large and underserved patient population.
By integrating clinical, sequencing data, and circulating biomarkers, the project aims to:
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Develop and validate advanced machine learning models for the stratification and diagnosis of ANOCA;
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Provide cell-type–resolved and pathway-level mechanistic insights into ANOCA pathophysiology through multi-omics analyses;
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Contribute to the clinical translation, implementation, and commercialization of novel diagnostic technologies, including potential spin-off creation.
