SF-based CRISPR diagnostics startup Mammoth Biosciences has published the first peer-reviewed study that shows validation of using its testing method to detect the presence of COVID-19 in patients. The study, published in Nature, shows performance on par with existing PCR-based molecular tests, the one ones currently authorized for use by the FDA to test for the novel coronavirus.
Mammoth’s DETECTR platform is designed to have advantages over traditional testing methods in a few different ways, including in its reconfigurability to address new viruses, since it uses CRISPR to target specific genetic sequences, and activate a “cleavage” that effectively acts as a signal for the diagnostic equipment to pick up. Basically, in the same way CRISPR allows scientists to target a specific string of DNA for removal or alteration, with scalpel-like precision, Mammoth’s diagnostic allows for programmable, targeted matching with a reference string, leading to confirmation that viral RNA is present in the patient.
The test that Mammoth is developing showed validated use in under two weeks, the researchers claim, since their platform is designed from the ground up for rapid reconfigurability to address new viral threats. The test can deliver results in under 45 minutes, and the results delivery is via what’s called a ‘lateral flow strip,’ which is essentially the same kind of read-out you see with at-home pregnancy tests, making them relatively easy to interpret. DETECTR also doesn’t require a lab setting to delver results, and instead can be conducted with portable heat blocks, combined with commonly available standard reagents.
In the study, which included samples from 36 patients with confirmed COVID-19 infections, and 42 patients who had other types of viral respiratory infections, the tests showed 95% positive diagnostic accuracy, and 100% negative efficacy. Samples used were taken from respiratory swabs.
This doesn’t mean this test can roll out to actual sites for use, but it’s a good validation of Mammoth’s model and test design, and could eventually lead to actual deployment of its test in a clinical setting, providing other, larger-scale studies back up the data.
