Powering the future of
immune-mediated inflammatory disease (IMID) medicines
Our Clinical Discovery Engine directly addresses one of the greatest risks to health today
Currently FOCUSing ON eight diseases
CLINICAL DISCOVERY ENGINE
Our Engine combines the collection, generation, and analysis of data to drive more efficient drug development
The Engine begins with access to patients and their samples through our clinical network. Partnered physicians collect epidemiological and clinical data, and biological samples which are stored in the Vall d’Hebron Institute of Research (VHIR) IMID Biobank.
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.
Our IMID experts interrogate our data using multidimensional computational approaches to inform target discovery. This leads to new disease mechanism insights, disease markers and targets, and prioritization strategies.
Finally, we partner with industry leaders such as Evotec to drive drug discovery and development that can produce new medicines faster, cheaper, and with lower risks.
Our network of clinicians and academic partners give us unprecedented access to patient data and samples
- >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
- >15,000 clinical variables
- >150 epidemiological variables
- 2M epidemiological and clinical data points collected
- Collected for every subject
We use the most advanced bio-analytical methods to probe mechanisms driving disease
This allows us to match the right drug target to the right patient
Decision on optimal combinatorial Therapies in IMIDs using Systems Approaches
Coordinator: Dr. Sara Marsal
To discover effective drug combinations to treat IMID patients based on:
- Patient medical and epidemiological data
- Multi-omic patient analyses
- Preclinical and clinical experimentation