The main objective of NGID is to develop infrastructure that enables personalised patient care. We will produce a prospective data set unique in resolution (depth) and extent (broadness) in time: a novel, centralized, longitudinal data repository. We will translate our insights and findings into minimal set biomarker profiles (individual signatures) that allow for ultra-deep phenotyping for each patient with an immuno-dermatological disorder, leading to identification of disease endotype, and personalised care through accurate prediction of effective treatment. In the development of this personalised care approach, we aim to achieve a number of scientific objectives and breakthroughs, for our and other research fields:
- Advanced understanding of the pathophysiological mechanisms of immuno-dermatological diseases
- Technological advancements for ultra-deep, ultra-high resolution skin characterization, including spatial biology
- Identification of novel biomarkers for disease subtyping, monitoring and treatment
- Design of tailor-made, animal-free translational human (disease) models
- Insights into the influence of psychological and behavioral factors on disease outcomes
- Novel data fusion, data analysis and machine learning technologies for biomedical data
NGID will provide ultra-deep and ultra-high resolution dermatological data and identify biomarkers that elucidate pathophysiological mechanisms related to all six immune-dermatological diseases. Furthermore, high-potential biomarkers and mechanistic pathways will be further investigated and validated using translation human skin models where experimental insights will be gained on the skin (dys)function. Tailored to each specific disease and patient, this advanced understanding of immuno- dermatological pathophysiology for each of the six skin diseases makes NGID a ‘moonshot’ project with a far-reaching impact in other scientific fields including neurology, psychiatry, cancer and immunology in a broader sense. The uncovering of molecular mechanisms and main contributors leads to novel target discovery and drug screening strategies, i.e. our project will fuel drug development pipelines. It is therefore highly impactful for pharmacology.