Our Business

We use genomic/bioinformatics pipelines to identify and functionally validate the best drugs that therapeutically target cancer cells, including those that are drug-resistant or "undruggable". Our aim is to match every cancer to targeted drugs based on identifying each cancer's vulnerabilities.

Genomic sequencing of patient cancers has improved survival by identifying specific "driver" mutations that can be targeted therapeutically ("precision oncology"). However, only 15% of all cancer cases have actionable targets. Even when targeted drugs are used, they often fail over time because new mutations give rise to resistant cancer cells. Further genomic sequencing of these variants finds secondary targeted drugs in only a fraction of cases. A major deficiency in this field is that it relies on a small panel of cancer-related genes that, in turn, are associated with under 0.5% of FDA-approved drugs for all diseases. At Veronomics, we seek to understand how identifying all genomic vulnerabilities in cancer cells, even in drug-resistant or undruggable cases, can maximize the identification of all drug susceptibilities, thereby pairing these cases to their appropriate targeted therapeutics.  

 

Founded in 2018, Veronomics has built on its expertise in using genomic screening to identify essential pathways in cancer cells. We have developed VeroTest1, a pipeline that marries powerful genomic essentiality screens to massive experimentally-derived datasets that describe sensitivity to >100,000 FDA-approved drugs. Using our proprietary Successful Drug Prediction Algorithm (SDPA), we have maximized our ability to identify functionally validatable drug sensitivities of cancer cells based on initially identifying essential gene and pathways. VeroTest1 is offered to biopharma companies and academic labs as an accurate, rapid and cost-effective means of identifying drug-susceptibilities and next-line therapeutic targets based on mechanistic essentiality pathways.

Cancer's Therapeutic Matchmaker

Using Genomics and Bioinformatics to Match Cancers with Their Therapeutic Medicines