ROCKVILLE, MARYLAND, USA, July 24, 2020 —AOAC INTERNATIONAL today announced that their SARS-CoV-2 Emergency Response Program is now accepting applications for environmental surface test kits to be validated by the AOAC Research Institute’s Performance Tested Methods Program. The AOAC Research Institute is a division of AOAC INTERNATIONAL.
The Performance Tested Methods program provides independent third-party expert review and certification for proprietary test kit performance. The certification mark assures users that an independent assessment found that test method performance meets an appropriate standard for its intended use.
The deadline for applications has been extended to August 5, 2020 for the initial set of applicants, with the full validation process expected to be completed by mid-September. The SARS-CoV-2 technical review will be done by an international team of leading scientists from industry, academia, and government agencies including the U.S. Food and Drug Administration, U.S. Environmental Protection Agency, U.S. Centers for Disease Control and Prevention, Wayne State University, and Qingdao Customs District of China.
Environmental surface test kits are designed to be used on-site by a layman, and may include sample collection swabs, safety equipment such as gloves and alcohol wipes, and shipping materials for sending collected samples to a laboratory.
Environmental monitoring is already common in the food industry to monitor facilities for pathogens and allergens and to determine if sanitation programs are being effective. Reliable tests for detecting coronavirus on environmental surfaces are critical to food supply chain and retail businesses concerned with protecting workers and consumers as public health restrictions are relaxed.
“There are many things yet to be learned about this virus, particularly its survivability in the environment and on surfaces. This is a high-profile project and it is our hope that these validated and certified test kits, and the data generated, can help us to better understand the virus, guide public health response, drive innovation and provide a greater sense of confidence to the general public,” said Dr. Palmer Orlandi, AOAC chief science officer.
In this initial phase, the AOAC INTERNATIONAL SARS-CoV-2 Emergency Response Program will validate detection on stainless steel surfaces only. Following this, AOAC plans to expand validation to a broader range of environmental surfaces and food matrices.
This method validation program is breaking new ground by implementing “in silico” (in silicon) analysis to harness the power of modern databases and computational power in biological experiments. Test kit manufacturers will compare the SARS-CoV-2 genetic sequence targeted by their test kit against a database of whole genome sequences of target and non-target organisms. This approach is more comprehensive, faster and less expensive; and it does not require obtaining and shipping SARS-CoV-2 virus sample materials, which could be difficult and potentially dangerous.
In addition, in silico analysis has a significant advantage over wet-lab testing alone in that genetic sequences from tens of thousands of strains of SARS-CoV-2 and near neighbors can be analyzed for inclusivity and exclusivity. The result is a more accurate estimate of the false-positive (a positive result when the virus is not present) and false-negative (a negative result when the virus is present) rates of an assay. This is an important part of the accuracy of a COVID-19 detection method. There have been reports of false-negative rates as high as 30% with clinical-based SARS-CoV-2 methods.
While in silico analysis is an emerging technology, its effectiveness has been extensively researched as part of AOAC’s Stakeholder Panel on Agent Detection Assays (SPADA) program, which generated detailed guidelines on its implementation. The SARS-CoV-2 validation program is expected to deepen scientific understanding of in silico analysis by generating comparative data from a broad range of analytical approaches, components, and parameters.
