Explore AI’s Role in Oncology Trial Recruitment at ASCO

Explore AI’s Role in Oncology Trial Recruitment at ASCO

Swiftly and accurately identifying eligible patients for oncology clinical trials is paramount to saving lives. However, the traditional methods of finding patients for clinical trials by manually sifting through medical records have proven to be time-consuming and inefficient, hindering the progress of groundbreaking research. In oncology trials, the eligible patient population is often narrow due to complex inclusion/exclusion (I/E) criteria; disease progression is hard to catch at the right time because researchers are not always the ones treating the patient; and identifying patients with rare genetic mutations or specific phenotypic profiles is a slow process, requiring site staff to sift through millions of patient records and disparate lab reports. Fortunately, artificial intelligence (AI) has made it possible to accelerate clinical trial recruitment for oncology trials by streamlining the pre-screening process. AI enables researchers to mine deep within electronic medical records (EMRs) to precisely identify which patients match a trial’s eligibility criteria, screening data for millions of patients in minutes. This automates the process of finding the right patient for the right trial at the right time, accelerating recruitment and getting life-saving treatments to patients faster. 

At this year’s Annual ASCO Meeting, Deep 6 AI is set to showcase its AI-powered software platform, which is used extensively for oncology research by the nation’s top cancer centers, health systems, and pharmaceutical companies. Where traditional, manual EMR keyword searches fall short finding patients for trials, Deep 6 AI addresses it head-on with a comprehensive next-generation patient matching solution.

Artificial Intelligence for Oncology Clinical Trials

The Deep 6 AI software mines the industry’s deepest, real-time EMR data sets across 40M+ patient lives at 25+ major health systems, including 7 NCI-Designated Cancer Centers and 3 NCI Community Oncology Research Programs, delivering unprecedented matching speed and precision. By mining deeper data sets that include structured and unstructured information from EMRs, genomic reports, and more, it matches patients to trials with complex eligibility criteria in a fraction of the time. Its AI can also find patients for oncology trials by mining clinical data for specific genetic markers or disease progression.

  • It can find patients with specific genetic markers easily. With Deep 6 AI, researchers can mine the entire EMR, including clinician notes, omics, genetic reports, and other clinical data in minutes to find patients with specific genetic markers while reducing site burden.
  • It can identify thousands of genes and mutation types. Deep 6 AI can query EMRs for 19,000 genes, multiple mutation types, and over 30,000 locus-specific mutation names with unprecedented precision. 
  • It can find patients with disease progression in real time. Deep 6 AI can pinpoint the most eligible patients for a clinical trial at the right time in their disease progression by mining real-time health information in clinician notes to identify key phrases, such as ‘worsening metastatic disease,’ ‘enlarging lymphadenopathy,’ or ‘new mass.’ 

Another distinguishing factor of this next-generation solution is that it focuses on accelerating ‘the last mile’ recruitment by offering strong integrations with healthcare workflows to create actionability and reduce site burden.

Case Studies for AI in Oncology Clinical Trials

The following two case studies describe the impact artificial intelligence has had on accelerating patient recruitment for oncology clinical trials. In both cases the Deep 6 AI technology was used by site staff to automate the screening process and reduce their workload, recruit patients faster, and shorten trial timelines. 

Study: Cancer Center Identifies 116 Patients for a Small Cell Lung Cancer (SCLC) Clinical Trial

A National Cancer Institute-Designated Cancer Center was recruiting patients for a small cell lung cancer (SCLC) trial. Patients with SCLC are difficult to find. Searching diagnostic codes in EMRs can be used to find patients with ‘lung cancer,’ but there is no code for ‘SCLC.’ Site staff were having to manually read through patient records to find patients with ‘SCLC,’ which was extremely time-consuming. The research team realized that if they continued using traditional search methods they would not hit their recruitment target so they deployed Deep 6 AI. The researchers were immediately able to generate a screen-ready list of 116 patients that were potential matches for this study. They then validated each of these 116 patients to see which of them had the target genome and how many of them previously received treatments that did not work, which were criteria for the trial. Ultimately, by using Deep 6 AI, the research team accelerated patient recruitment and reduced the burden on their staff. The Cancer Center is now using the software for more than 150 clinical trials.

Study: Life Sciences Company Finds 2x More Patients for a Clinical Trial of a Second-Line Therapy for Colorectal Cancer

In another example, a clinical-stage life sciences company was conducting a study of a second-line therapy for colorectal cancer. But due to complex I/E criteria, they were having trouble reaching their enrollment goals. In less than two months from signing their contract with Deep 6 AI, they activated two sites in the Deep 6 AI ecosystem and were able to query millions of EMRs in real time to find patients with the right genetic mutation who were also at the right stage in their disease progression. From those two sites, they enrolled four of the AI-matched patients, which was two times more than their goal of one patient per site every three months. A few months later the FDA advanced this drug to a first-line therapy and enrollment ceased.

Accelerating Oncology Research with AI

With the complexities involved in oncology trial recruitment, the implementation of AI solutions can have a measurable impact on the site’s ability to find and recruit the right patients and the success of the trial overall. The Deep 6 AI platform simplifies this process for researchers and streamlines operations for sites, sponsors and partners by determining the feasibility of running a specific trial, accelerating recruitment, and bringing novel, life-saving medical treatments to patients faster.  

Visit Deep 6 AI at the Annual ASCO Meeting

Visit Deep 6 AI at the Annual ASCO Meeting on May 31 to June 4, 2024, in Chicago, IL. Contact us to schedule a meeting with our oncology team to learn about using AI to automate the pre-screening process and minimize the burden on site staff.  

About The Author

Nour Malki