The multi-site, prospective, non-inferiority trial was designed for assessing the AudibleHealth Dx software as a medical device (SaMD) in diagnosing Covid-19 using forced cough vocalization-signal data signature (FCV-SDS).
Using artificial intelligence (AI), the AudibleHealth Dx diagnoses Covid-19 by analysing the sound of forced cough vocalisation of a person.
The user needs to cough for four to six times in their mobile phone, in around two minutes, after downloading and registering the mobile application.
They will receive the test result in the app after submitting a cough.
In Florida, the company started the clinical study in the second quarter of this year for evaluating the efficacy of the AudibleHealth Dx device in 514 subjects, with 12.8% prevalence.
In the study, the AudibleHealth Dx Covid-19 test was compared to the US Food and Drug Administration (FDA) de novo-authorised BioFire RP2.1 Panel for identifying the Covid-19 infections.
The device showed at least 81% positive percent agreement (PPA) and at least 80% negative percent agreement (NPA).
RAIsonance founder and CEO Kitty Kolding said: “We spent two years refining this technology and building the device itself and were met with dozens of significant challenges along the way.
“And to ensure that this test can meet the complex testing needs of organizations, we also built a fully integrated, easy to use ecosystem to ensure that users– individuals, businesses, medical professionals, universities, and government agencies – can experience the full benefits of a totally digital Covid-19 testing solution.
“The combination of our convenient, mobile-app testing interface and our TestHub portal for high-volume purchasers, we believe, is nothing short of revolutionary.”
The company noted that this study data will be utilised in seeking Emergency Use Authorization (EUA) from the FDA.
Additionally, it has conducted a comprehensive usability analysis, which involved 443 participants.
As per the analysis, 98.4% of the participants said that the app screens are easy to understand and 97% of them completed the screens of the application completely independently.
Average time taken for completing the test was 5.39 minutes and 99.39% was the overall successful test completion rate.