Spectral AI has added three clinical trial sites to a US pivotal study evaluating its AI-based diagnostics platform DeepView.
The addition of Texas’ University Medical Center, Florida’s Tampa General Hospital Burn Center, and the University of South Alabama’s health emergency department brings the total number of locations in the country to 16.
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Spectral AI stated that a mixture of burn centres and emergency departments make up the list of trial sites.
Spectral AI’s CEO Peter Carlson said: “The addition of these new sites brings us closer to completing the 2024 Burn Pivotal Study and seeking US Food and Drug Administration (FDA) approval for the DeepView System for burn indication in 2025.”
The pivotal study (NCT06131203) is specifically evaluating DeepView’s algorithms and their ability to assess burn healing potential.
The technology is already approved for use in adults in the UK, gaining regulatory approval in February this year.
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By GlobalDataThe trial’s endpoint is the superiority of the company’s device sensitivity to a healthcare professional’s bedside examination while also being non-inferior in terms of specificity.
According to ClinicalTrials.gov, the study is estimated to enrol 240 patients with a thermal burn that occurred less than 72 hours before imaging. Spectral AI hit its paediatric enrolment goal earlier this month.
DeepView uses algorithms to analyse multispectral imaging of wounds against a burn biopsy tissue database. According to Spectral AI, the predictive device can help assess wound healing outcomes and support clinical decision-making. Gaining insight into the deepness and severity of a burn early is critical for patients to ensure appropriate care.
The wound care management market is expected to total $38.8bn by 2030, with a CAGR of 3.4%, according to analysis by GlobalData.
Shares in Spectral AI have been relatively stable over the past few months. In March 2024, the stock took an upturn after the Nasdaq-listed company secured a contract with US federal organisations to develop a handheld version of its system for military personnel in the field.
