PathogenDx Inc, an Arizona-based technology company which has developed an ultra-accurate DNA-based customized pathogen testing platform for the food, agricultural and health sectors, announced that it has received a second grant from the National Institute of Allergy and Infectious Diseases (NIAID) under the National Institutes of Health (NIH) to develop more accurate and efficient COVID-19 diagnostic testing technology.

The grant was issued under the NIH's Emergency Awards: Rapid Investigation of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) and Coronavirus Disease 2019 (COVID-19) PAR-20-178 two year Research Project Grant Program (R01) and will be used to expedite the research and development of PathogenDx's patented DetectX-Rv microarray.

In the next year, PathogenDx aims to utilize the additional funding to accomplish the following four goals: capture and identify new COVID-19 mutations; improve the sensitivity and specificity analysis of existing tests; improve testing turnaround by simplifying the detection of COVID-19; enhance detection and diagnose asymptomatic transmission. Under an expedited research and development timeline, PathogenDx is on track to meet these milestones before the end of the two year time frame.

"We applaud the NIH and NIAID for their ongoing efforts to safeguard the nation's public health and for investing in tangible solutions to fight the ongoing pandemic," said Milan Patel, CEO of PathogenDx.

"Existing q-rt PCR technology, which is currently widely used in COVID-19 testing, has alarmingly high false negative rates ranging from 15% to 48%. PathogenDx recognizes the NIH's commitment to addressing existing testing and diagnostic pain points and is confident that its DetectX-Rv technology will enhance accuracy and efficacy in the testing field. SARS-CoV-2 is here to stay in our ecosystem and mutations will likely occur long-term. The scientific community is still studying how the virus will mutate but it is clear that we need a longer-term diagnostic solution that can address these issues without compromising sensitivity and specificity, "Patel added.