Daily Newsletter

08 January 2024

Daily Newsletter

08 January 2024

Deep 6 AI and Graticule develop clinical trial recruitment algorithm

The algorithm identifies eligible patients by extracting critical information from both structured and unstructured data sources.

Archana Rani January 08 2024

Precision research platform Deep 6 AI has partnered with Graticule to develop a new algorithm designed to expedite patient screening and recruitment for clinical trials.

The "first-of-its-kind" solution employs artificial intelligence (AI) and natural language processing (NLP) to sift through vast amounts of electronic medical record (EMR) data.

It identifies eligible patients by extracting critical information from both structured and unstructured data sources, such as clinical notes and radiology reports.

The screening algorithm will then qualify and prioritise eligible subjects using the insights to give a precise picture of the individuals who would benefit from the intervention.

Graticule chief technology officer Dan Housman said: “Traditionally, it takes up to two years for life sciences companies to get access to EMR data to develop novel patient matching algorithms.

“Additionally, traditional methods of ‘clinical data pulling’ often burden an already overworked hospital IT staff. We partnered with Deep 6 AI to accelerate the development and deployment of screening tools that reduce site burden through access to ready-to-use deep EMR data from 1K+ research facilities across the Deep 6 AI ecosystem.”

Coupled with quick implementation services, the algorithm is being piloted actively at sites in the research ecosystem of Deep 6 AI for expediting trial completion.

Deep 6 AI founder and CEO Wout Brusselaers said: “We help clinical research teams identify targeted patient populations with great precision and speed by using AI to mine deeper data that goes beyond traditional claims and structured EMR data.

“By applying Graticule’s real-world data research methods and advisory services to the real-time, real patient data within our research ecosystem, we have drastically improved the utility of the research algorithms and screening processes we offer.”

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