AccuGenomics is the exclusive license holder to a suite of patented technologies from the University of Toledo that enable advanced genomic testing applications.  Amongst the technologies being developed and commercialized by AccuGenomics are the SNAQ™-SEQ spike-in standards for NGS that provide NGS-assay developers powerful standardization tools that improve the detection of low abundance DNA or RNA targets.  AccuGenomics partners with leading healthcare organizations in the development of these advance genomic tests.   We have several ongoing opportunities for partnerships which include a lung cancer risk test.

AccuKit™ LCRT13: A set of 13 biomarkers predictive for Lung Cancer in high risk patients based on age and smoking history

Lung cancer remains the most prevalent cause of cancer death in the United States (160,000 deaths each year). A recent NIH-sponsored study determined that annual screening by chest CT scan reduces mortality from lung cancer by more than 20%. However, the annual cost of CT scan screening all 7 million individuals at risk for lung cancer due to age and smoking history exceeds $5 billion. The AccuGenomics Lung Cancer Risk Test promises to identify the individuals genetically pre-disposed to lung cancer so that they can be prioritized for screening. This will markedly reduced cost of CT screening.

Format: RNASeq NGS Panel (Bronchoscopy and matching blood samples)

Status: Recruited 380 patient specimens.  Seeking a co-development partner for validation and commercialization.


Yeo, J., Crawford, E. L., Zhang, X., Khuder, S., Chen, T., Levin, A., Blomquist, T. M., & Willey, J. C. (2017). A lung cancer risk classifier comprising genome maintenance genes measured in normal bronchial epithelial cells. BMC Cancer, 17(1), 1–10. 

We are seeking additional co-development partnerships enabled by our SNAQ-SEQ technology in the areas of:

  • Minimal Residual Disease (MRD) detection using NGS-based ctDNA assays
  • Standardizing serial monitoring of ctDNA from cancer patients undergoing therapy
  • Extraction and process spike-in standards
  • RNASeq for Transcript Abundance
  • Standards for single-cell analysis

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