Deep 6 AI is a clinical trial recruitment software platform that uses artificial intelligence and natural language processing to help researchers identify eligible patients for clinical trials. Deep 6 AI enables health systems, pharmaceutical companies, and contract research organizations (CROs) to mine both structured and unstructured patient data, finding better-matching participants for trials in minutes instead of months.
How does Deep 6 AI improve clinical trial enrollment?
Deep 6 AI addresses one of the most significant challenges in clinical research: the slow and complex process of finding suitable patients for clinical trials. By leveraging advanced AI and NLP technologies, their platform analyzes vast amounts of electronic health records and other patient data, quickly matching patients to relevant studies based on highly specific eligibility criteria. This process streamlines recruitment and can greatly accelerate patient access to potentially life-changing clinical trials.
Who uses Deep 6 AI?
Deep 6 AI works with leading health systems, pharmaceutical companies, and CROs worldwide. Their platform is integrated into the clinical research workflow of these organizations, supporting teams that need to identify trial cohorts efficiently and accurately. While specific customer names are not listed, their focus is on serving major players in healthcare and life sciences.
How was Deep 6 AI started?
Founded in 2015 and based in Pasadena, California, Deep 6 AI was established by a team with expertise in healthcare technology and clinical research. Key founding members include Wout Brusselaers (CEO & Founder), Doug Cassidy (President), Christian Duvall (Chief Technology Officer), Sondra Pepe (Senior Vice President, Product), Peter Casasanto (Senior Vice President & General Manager, Life Sciences), Antonia Holway, PhD (Head of Clinical Programs), Amit Masaun (Vice President, Engineering), and Michael Loria (Chief Information Security Officer).
What makes Deep 6 AI different?
The main differentiator for Deep 6 AI is its use of AI and NLP to analyze both structured and unstructured patient data—a capability that enables rapid, precise patient-trial matching far beyond traditional manual or rules-based systems. This approach not only accelerates research timelines but also can improve trial outcomes by ensuring better patient matches.
You can learn more about their team and approach on their About page.
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