Our Clinical Discovery Engine deepens our understanding of
immune-mediated inflammatory diseases (IMIDs)
PATIENT-BASED DISCOVERY
Currently focusing on eight diseases
CLINICAL DISCOVERY ENGINE
Our Engine combines the collection, generation, and analysis of data to drive better target selection and more efficient drug development
CLINICAL NETWORK
The Engine begins with access to patients and their samples through our clinical network. Partner physicians collect epidemiological and clinical data, and biological samples which are stored in the Vall d’Hebron Institute of Research (VHIR) IMIDBiobank.
DATA GENERATION
Samples are subject to the most modern biomolecular analyses, generating proprietary multiomics data. These data are integrated with epidemiological and clinical data, forming the backbone of the Engine. The provenance of all our data is controlled by IMIDomics.
TARGET DISCOVERY
Our experts combine a foundation of IMID and immunology knowledge with our proprietary data to inform target discovery and prioritization. It also leads to identification of disease markers that will direct our medicines to patients most likely to benefit from our drugs.
Development
Finally, we partner with industry leaders to drive drug discovery and development that can produce new medicines faster, cheaper, and with lower risks.
CLINICAL NETWORK
Our network of clinicians and academic partners give us unprecedented access to patient data and samples
BIOBANK
- >17,000 subjects
- Cross-sectional and longitudinal
- >1M sample vials of biological specimens
- Every subject donates whole blood and urine
- Biopsies from select subjects
Epidemiological and Clinical Data
- >10,000 clinical variables
- >150 epidemiological variables
- 2M epidemiological and clinical data points collected
- Collected for every subject
Data driven translation
Our data collections and analyses strengthens our clinical translational capabilities
DOCTIS
Decision on optimal combinatorial Therapies in IMIDs using Systems approaches
Coordinator: Dr. Sara Marsal
Discovering effective drug combinations to treat IMID patients based on: (move on)
- Patient medical and epidemiological data
- Multi-omic patient analyses
- Bioinformatics
- Preclinical and clinical experimentation
