Concerto HealthAI focuses on using oncology-specific real-world data (RWD) and artificial intelligence (AI) enabled insight solutions to generate real-world evidence (RWE). The company will work with Bristol-Myers Squibb to apply AI to accelerate trials through the clinical development of synthetic control arm studies.
Per the agreement, Concerto HealthAI’s RWD and AI insights platform eurekaHealth will be used to explore RWE for regulatory purposes, validate clinical application for AI solutions, and execute clinical studies.
Jeff Elton, CEO of Concerto HealthAI told us, “eurkeaHealth is the top, middle, and bottom of our insight generation and next best action capabilities – the bottom supports the integration of data from different sources and is centered around a patient-centric data model; the middle allows AI to accommodate the ‘missingness’ and messiness’ that is often found in real-world data while speeding insights through ‘intelligent models’; and the top allows insights to be translated into protocols, sites, and actions.”
With the increased use of RWD, there has been a “rapidly emerging” use of synthetic control arms to replace what has been a standard of care or placebo arm, according to Elton.
“We use AI, machine learning and other approaches to predict who may respond, making higher powered and lower cost studies,” he explained. “We can also use AI and machine learning approaches to identify super- and lower-responders, focusing studies and approaches on these populations to assure the best possible outcomes for all subpopulations no matter how small.”
Regulatory organizations push RWE use
Recently, the 21st Century Cures Act accelerated the adoption of RWE-based approaches to clinical trials and post-approval studies.
In December 2018, the US Food and Drug Administration (FDA) reinforced its commitment to expanding the use of RWD in studies by issuing a framework to assess RWE in regulatory decisions and approvals.
Elton explained that with an increased demand for RWD by the FDA, the size of RWD data sets, and the increasing power of deeply abstracted data and AI approaches, it is possible to deploy RWE centric clinical development and an outcomes research operating model.