The National Cancer Institute (NCI), part of the US National Institutes of Health (NIH), has awarded $2m in funding to Enspectra Health through the Small Business Innovation Research (SBIR) programme.
The grant will fund the development of deep learning algorithms that can predict which pre-cancerous skin lesions are likely to turn into squamous cell carcinoma (SCC).
In a press release, Enspectra CEO Gabriel Sanchez said: “We are thrilled to have been awarded a Direct-to-Phase II SBIR grant from the NCI to support the development of predictive algorithms for skin precancers.
“This grant will accelerate our vision to noninvasively detect and monitor skin conditions earlier to advance care for the millions of patients with skin conditions.”
Pre-cancerous lesions, also known as actinic keratosis (AK), are caused by long-term exposure to the sun, particularly UV rays, and can progress to SCC. According to the Skin Cancer Foundation, only 5%-10% of AK can progress to cancer. However, the only way to diagnose which of the pre-cancerous skin lesions can progress to SCC is to do a skin biopsy.
Enspectra plans to use an imaging technology that combines reflectance confocal and multiphoton laser scanning microscopy to eliminate the need for biopsy.
Enspecta will first create a digital histopathology database of patients with AK. The information collected will include data before any treatment and will follow patients through the treatment with topical therapy. As patients who are unresponsive to treatment are more likely to develop SCC, the algorithm would be trained to predict which patients are likely to be unresponsive to treatment, thus, are likely to develop SCC.
There has been an increased focus on using new technologies such as artificial intelligence and machine learning in the pharmaceutical sector. In July, NVIDIA invested $50m to create drug discovery models for commercialisation.