Skip to main content
Premium Trial:

Request an Annual Quote

IMIDomics, Celgene Partner on Immune-Mediated Inflammatory Disease Research

NEW YORK (GenomeWeb) — IMIDomics announced today that it has partnered with Celgene to advance Celgene's development of new treatments for immune-mediated inflammatory diseases.

IMIDomics is developing a database of genomic markers derived from biological samples for immune-mediated inflammatory diseases in order to identify factors involved in specific phenotypes, drug response, disease activity, disease severity, and disease stratification. The company focuses on rheumatoid arthritis, Crohn's disease, ulcerative colitis, psoriasis, psoriatic arthritis, and systemic lupus erythematosus.

Under the terms of their deal, IMIDomics will provide Celgene with access to its clinical and molecular database to identify new targets and biomarkers, support the development of new therapeutic candidates and next-generation companion diagnostics, and enable patient population stratification for clinical trials. Im exchange, IMIDomics will receive undisclosed project funding and stands to receive royalties based on products resulting from the alliance.

Additional terms were not disclosed.

"Under this agreement, we will apply our unique database of clinical, phenotypic, genotypic, and analytical findings to potentially advance and accelerate Celgene's discovery and development efforts targeting diverse immune-mediated inflammatory diseases with substantial unmet needs," IMIDomics Executive Chairman Sandy Zweifach said in a statement.

The Scan

Study Links Genetic Risk for ADHD With Alzheimer's Disease

A higher polygenic risk score for attention-deficit/hyperactivity disorder is also linked to cognitive decline and Alzheimer's disease, a new study in Molecular Psychiatry finds.

Study Offers Insights Into Role of Structural Variants in Cancer

A new study in Nature using cell lines shows that structural variants can enable oncogene activation.

Computer Model Uses Genetics, Health Data to Predict Mental Disorders

A new model in JAMA Psychiatry finds combining genetic and health record data can predict a mental disorder diagnosis before one is made clinically.

Study Tracks Off-Target Gene Edits Linked to Epigenetic Features

Using machine learning, researchers characterize in BMC Genomics the potential off-target effects of 19 computed or experimentally determined epigenetic features during CRISPR-Cas9 editing.