Deep 6 AI

Deep 6 AI fills a genuine gap: most clinical trial screening relies on structured data, missing up to 80% of patients whose eligibility clues are buried in clinical notes. The NLP is purpose-built for medical text—handling negation, temporality, and family history—which sets it apart from generic text analytics. Integration with Epic and Cerner is a major plus, as is the patient self-screening portal. However, the biggest barrier is access: you cannot try it without a sales conversation, and pricing is enterprise-level. It also requires IT support to set up EHR hooks, so small sites may struggle. Validation studies are encouraging, but they're vendor-sponsored. For large hospital systems or CROs running many trials, the ROI can be substantial. For a single-site coordinator with a non-digital EHR, it's overkill. Competitors include TriNetX (structured queries), Verily (data ecosystem), and Accenture's AI solutions. Deep 6's edge is its focus on unstructured text; its weakness is the walled-garden pricing model.

Deep 6 AI is a clinical trial patient screening platform that uses artificial intelligence to analyze unstructured electronic health records (EHR) and clinical notes. It is designed for clinical research coordinators, site managers, and sponsors who need to rapidly identify eligible patients for clinical trials. The platform ingests free-text data—including physician notes, discharge summaries, and pathology reports—and applies natural language processing (NLP) and machine learning to match patients against complex trial inclusion/exclusion criteria in minutes instead of months. What makes Deep 6 AI different is its focus on real-world, unstructured clinical data, which constitutes up to 80% of patient health records and is often ignored by traditional structured database queries. By reading clinical narratives with specialized medical NLP models, Deep 6 can surface patients who would otherwise be missed, including those with rare diseases or nuanced presentations. The platform also offers a patient-facing self-screening tool and integrates with major EHR systems and clinical trial management systems (CTMS). Deep 6 AI targets both sites and sponsors. For sites, it accelerates pre-screening and reduces manual chart review. For sponsors and CROs, it enables trial feasibility assessment, site selection, and faster enrollment. The company has published validation studies showing significant reductions in screening time and increases in enrollment rates. Its AI models are trained on medical ontologies (e.g., SNOMED CT, ICD-10) and continuously updated. Unlike pure EHR query tools, Deep 6 AI can interpret negation, temporality, and family history from clinical text. However, its value depends on the quality and completeness of the source EHR data, and the platform requires integration with existing health IT infrastructure. It is a specialized B2B SaaS tool, not a general-purpose AI assistant.