Metabolomics is the new "Omics" that focuses on characterizing low molecular weight compounds generated by metabolism.

There are more than 40,000 metabolites known to be in the human body. The small molecules (‘metabolites’) that appear in a person’s urine provide very useful information about a patient's current health. 

PolypDx™ was developed with the successful identification of distinct metabolomic fingerprints in urine samples of patients with adenomatous polyps, the precursor to colorectal cancer. These distinct signatures were discovered using 1,000 samples collected in a clinical trial attached to the Edmonton Colon Cancer Screening Program (SCOPE), in conjunction with Alberta Health Services (formerly, Capital Health). This clinical trial compared the sensitivity and specificity of the urine metabolomics tests (PolypDx™) and fecal-based tests (fecal-guaiac, and fecal-immune) relative to the gold standard - full colonoscopy by expert gastroenterologists. 


Our Technology

Many researchers have successfully identified metabolomic-based signatures that may potentially be used as diagnostics, but often these metabolomic-based signatures are comprised of a large number (60-90) of metabolites that makes it cost-prohibitive to incorporate into a large, population-based screening tool.

The innovation of PolypDx™, is that we were able to reduce the metabolomic signature (using a combination of machine learning and statistical analysis), to a small number of metabolites, while maintaining the high accuracy necessary to be useful as an accurate diagnostic screening tool.


In the development of PolypDx™, we had a distinct advantage in regards to clinical connections and access, via a clinical trial, to a large clinical sample repository that is well-characterized with both colonoscopies conducted as well as fecal guaiac and fecal immune-based tests. 

We also formed several important collaborations to further enhance our current technology, including metabolomic analysis expertise from the The Metabolomics Innovation Centre (TMIC) and in the development of a diagnostic algorithm with the Alberta Machine Intelligence Institute (Amii).