Deep Lens to advance AI trial recruitment technology

9th April 2019 (Last Updated April 10th, 2019 14:14)

US-based Deep Lens has raised funds in a series A round to advance its artificial intelligence (AI) pathology platform, VIPER, which is intended to drive clinical trial recruitment at the diagnosis stage.

The $14m financing round was led by Northpond Ventures and joined by Rev1 Ventures, Sierra Ventures and Tamarind-Hill Partners. This brings the company’s total funding support to $17.5m.

Deep Lens will use the fresh funds to further develop its AI and platform capabilities, as well as scale its service, sales and marketing network to improve access to the trial recruitment technology.

Deep Lens co-founder and CEO Dave Billiter said: “This Series A financing is further validation of the value of our industry-changing approach to digital pathology in delivering the right cancer diagnoses faster and accelerating oncology trial recruitment and timelines.”

Powered by AI, VIPER uses advanced pathology workflows for peer-to-peer alliance and patient identification in clinical trials. It is meant to deliver quick and accurate information on patient eligibility for the studies.

As the platform identifies patients at the time of diagnosis, it is expected to accelerate enrolment and potentially reduce the trial duration.

Originally designed for research use, the technology was utilised as the de-facto platform in certain oncology studies. Deep Lens later started commercialising the platform.

Deep Lens co-founder and chief scientist TJ Bowen said: “In the past year we have successfully launched our industry leading platform, VIPER, to the pathology industry at-large, we have integrated deep learning (AI) and we have made VIPER available free-of-charge to pathology groups worldwide as we work to identify patients at the time of diagnosis for available clinical trials.”

Last month, Deep Lens partnered with Worldwide Clinical Trials to fast-track enrolment in oncology trials using the VIPER digital pathology platform.