SOURCE-LINKED INTELLIGENCE

Diagnostic model and assay for personalized vaccine

CORDIS · observation · Publication date unknown

points over 4 influenza seasons. This analysis, covering multiple virus strains, identified robust molecular biomarkers linked to vaccine responses, which were validated through wet-lab experiments. Machine learning models based on pre-vaccination biomarkers were able to predict vaccine response in independent samples. Building on these findings, we propose to develop a diagnostic assay to measure these biomarkers and apply our established prediction model to stratify patients based on their responsiveness to the influenza vaccine. Samples from various patient cohorts, provided by our collaboration partners, will be used for verification and validation. Once validated, these biomarkers will be integrated into an innovative, fast, and reliable diagnostic test to predict vaccine responsiveness, through collaboration of an experienced industrial partner. Additionally, our team will create a user-interface app to translate biomarker measurements into diagnostic outcome. By enabling personalized vaccine strategies particularly for patients, this project has the potential to significantly

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recordType

award

status

SIGNED

region

EU

value

150000

unit

EUR