Deep Lens
Matching the Right Patient to the Right Clinical Trial

Over the last few decades, patient recruitment for clinical trials has remained a significant roadblock to the effective execution of drug development programs. The problem is explicitly acute in oncology. Cancer therapeutics comparatively has the lowest clinical trial success rate of all major diseases. It is estimated that, in oncology, about 85 percent of clinical trials are not completed on time, and almost half of them get delayed due to inadequate patient enrollment.

Clinical trial sponsors—pharmaceutical companies, biotech companies, and clinical research organizations—struggle to find suitable patients for their clinical trials. Scrutinizing a large database of cancer patients and discovering the right patient for a clinical trial – particularly a precision medicine trial with extremely narrow eligibility criteria -- proves to be a daunting task for them. On a similar note, hospital providers find it challenging to ensure that the trial is the right one for the patient and that the staff on-site are sufficiently trained for the clinical trials. Just as sponsors want to bring their trials to as many patients as possible, providers want to give their patients access to as many trials as possible so that they don’t have to travel to another hospital or, worse, not be identified for a trial that they may be qualified for.

This brings Deeps Lens, an Ohio-based AI company, into the spotlight. Deep Lens is focused on finding the right patient for the right clinical trial at the right time. “We act as a perfect matchmaker between clinical trial sponsors, study sites and eligible patients, eliminating much of the manual labor and subsequent resource constraints that often contribute to challenges in the clinical trial enrollment process. The goal is to ensure that no patient falls through the cracks, and that all eligible patients have every opportunity–no matter where they are receiving care–to participate in trials with emerging new therapies,” says Greg Andreola, Chief Revenue Officer at Deep Lens.

Deep Lens’s earnest efforts are directed toward bringing clinical trials to many more institutions, including cancer centers, community oncology centers, and academic medical centers, with the intent to give access to more trials for the required patients, right at the time of diagnosis. To that end, Deep Lens delivers its potential solution, which is driven by artificial intelligence and natural language processing.

“Despite an increase in the complexity, sophistication and quantity of new cancer therapeutics in development, the number of clinical trials that struggle or fail to enroll patients remains remarkably high,” said Mark Vance, Vice President of Technology at Deep Lens.

Our tool called VIPER is a HIPAA- and GDPR-compliant cloud-based patient recruitment tool that is specifically designed to inform and educate care teams of potential trial participants

“This means that patients are not accessing therapies that may have the potential to change the course of their disease and that promising drugs in development may never have a chance to reach the market. Our solution, VIPER, is a HIPAA- and GDPR-compliant cloud-based patient recruitment tool designed to improve upon the current process through advanced AI-based technology. VIPER ingests and analyzes multiple sources of patient data, including electronic medical records, pathology and genomic data, and automatically identifies patients who may be eligible for a specific trial. This process streamlines workflow, reduces staff burden and produces analytics and reporting that helps sponsors, study sites and providers meet trial objectives.”

The real-time interactive dashboards of VIPER with exceptional data mining capabilities act as a great communication tool between the principal investigators and sponsors. The dashboards provide the principal investigator with a snapshot of each trial and the performance associated with those trials, enabling them to have comprehensive and critical information at their fingertips. The sponsors also have access to these dashboards that show de-identified data on the performance of each of the sites running those trials, thereby allowing them to evaluate why a particular trial is either performing, over-performing or under-performing.

Andreola mentions one of Deep Lens’ success stories in which they collaborated with an oncology company that was conducting a biomarker-driven clinical study that was struggling to enroll. Through the deployment of VIPER, a new study site within the Deep Lens network was identified and onboarded and patient screening for the trial began immediately. A few months following VIPER’s installation, the enrollment rate at the new site was 300 percent higher than the existing rate across the oncology company’s existing network.

Giving a glimpse into their roadmap, Andreola mentions that Deep Lens looks forward to expanding the availability of their solution to an international market, specifically to the UK and Australia, and to move toward other disease spaces like neuroscience. With a keen focus on the efficacious treatment of cancer and establishing a quality environment for clinical trials, Deep Lens is heavily contributing to oncology research enhancement.