Verici Dx (AIM: VRCI), a developer of advanced clinical diagnostics for organ transplant, announced on Wednesday that it has initiated a collaborative research effort with The Westmead Institute for Medical Research in Sydney, Australia.

Supported by a four-year federal research grant, the collaboration is part of the Australian Government's Medical Research Future Fund (MRFF) 'Genomics Health Futures Mission', which allocates AUD500m for genomic medicine research. The focus is to enhance testing, diagnosis, and treatment in various medical areas, including organ transplants.

The collaboration aims to deepen the understanding of factors contributing to graft loss in organ transplants, specifically exploring genetic differences beyond the well-known HLA mismatches. The research will leverage Verici Dx's CAP/CLIA-certified laboratory for sequencing blood samples across three sites, incorporating diverse genetic data from multiple cohorts with varying ethnic backgrounds. The goal is to improve risk prediction and management in organ transplants, leading to better outcomes for patients.

In addition to research, the program includes a health economics analysis, a crucial step for the official recognition and approval of new assays (tests) for use in Australia.

Verici Dx is known for its kidney transplant platform, offering personalised tests for patient and organ response risk, utilising artificial intelligence-assisted transcriptomic analysis. The technology focuses on RNA signatures related to the immune response and other biological pathways critical for transplant prognosis. The company aims to accelerate innovation through collaborations with medical device, biopharmaceutical and data science partners.

The Westmead Institute for Medical Research (WIMR) is a multidisciplinary institute renowned for its research in cancer, immunology, liver disease, renal disease and transplantation. The institute uses genomics and genetic data for various medical advancements, including new treatments for cancer and autoimmune diseases, and predictive biomarkers for risk stratification in kidney transplantation.