PM.20.045 – Next generation immunodermatology

Route: Personalised medicine: the individual at the centre

Cluster question: 095 How can we personalise health care, for example by using biomarkers?

Until recently, Dermatology has been neglected from therapeutics development resulting in a high unmet need for many skin diseases. As consequence the patients suffer from an extremely low quality of life and the society is challenged with a high economic burden. While the pathogeneses of skin diseases are complex and multifactorial, the key driver of the etiology is the dysregulation of the immune system. However, the understanding of the disorders remains limited because of the fragmented and mono-dimensional investigations. Therefore, we propose to develop a novel platform for comprehensive, multi-modal characterization of four skin diseases including: i) mycosis fungoides, an orphan malignancy belonging to the cutaneous T-cell lymphomas, ii) atopic dermatitis, a highly prevalent disease with a high immune inflammatory component, iii) chronic spontaneous urticaria, an allergic condition of the skin and iv) cutaneous, systemic lupus erythematosus a rare but life threatening disease. The platform will contain different tools that enable characterization of the various aspects of the disease patient-reported outcomes, the classical physician-based clinical scoring, biophysical, cellular, microbiological, molecular biomarkers and the external factors. State-of -the art technology will be used and obtained data will be merged to provide a system-wide view on each individual including spatial mass cytometry, mass spectrometry imaging, proteomics, lipidomics, metabolomics and smart sensors for home monitoring. This novel ‘systems dermatology’ approach will integrate all various data sets in order to phenotype the pathophysiology in high detail. This integrative and multi-disciplinary strategy will enable high-resolution sub-typing and individualization of treatment for the patients. In addition, the profiling of the disease characteristics will facilitate the development of novel, non-invasive biomarkers for clinical diagnosis and for monitoring of treatment effects. The final step of data integration will be done through an artificial intelligence approach and hence the platform can be applied in further immunological and dermatological diseases.

Keywords

Artificial Intelligence, atopic dermatitis, clinical trial, deep phenotyping, lupus, multi-omics, spatial mass cytometry, trial@home

Other organisations

Erasmus Medical Center (EMC), Leiden Universitair Medisch Centrum (LUMC), Maastricht University (UM), TNO

Submitter

Organisation Leiden Academic Center for Drug Research, Leiden University (LEI) and Centre for Human Drug Research
Name Dr. R. (Robert) Rissmann
E-mail rrissmann@chdr.nl
Website https://www.universiteitleiden.nl/en/science/drug-research and www.chdr.nl