Clinical Trial Solutions

Dyania Health: Finding Trial Candidates Hidden in Medical Records

Dyania Health — AI clinical trial solutions

Overview: How Dyania Health’s AI-Driven Clinical Trial Solutions Platform Transforms Patient Identification and Eligibility Screening Dyania Health develops Synapsis AI, a clinical trial solutions platform that analyses electronic medical records to support patient identification, eligibility pre-screening and study feasibility. It addresses the manual effort involved in reviewing clinical histories against detailed trial criteria, particularly when […]

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Overview: How Dyania Health’s AI-Driven Clinical Trial Solutions Platform Transforms Patient Identification and Eligibility Screening

Dyania Health develops Synapsis AI, a clinical trial solutions platform that analyses electronic medical records to support patient identification, eligibility pre-screening and study feasibility. It addresses the manual effort involved in reviewing clinical histories against detailed trial criteria, particularly when relevant information is dispersed across records and changes over time. Its Patient Finder application continuously reviews updated records to identify potential participants, rather than relying solely on one-off searches.

Synapsis AI combines a medically trained language-model system with clinical reasoning logic to extract patient characteristics and assess study requirements. Dyania’s in-house physicians translate protocol criteria into deterministic logic for its reasoning engine and review screening results before delivery. The platform supports questions about individual records, candidate searches by trial site and feasibility assessments based on the available patient population. These functions connect medical-record interpretation with recruitment planning and protocol assessment.

The potential benefits are reduced chart-review workload and earlier identification of candidates for further assessment. Using the same record-analysis foundation, Synapsis AI also supports observational research and registry reporting by organising clinical characteristics into usable outputs. These capabilities can make existing records more useful across research workflows; identifying a potential match, however, does not establish final eligibility, consent or successful enrolment.

Last checked on October 6, 2026: Cleveland Clinic’s March 2026 report adds published evidence for Synapsis AI’s rare-disease trial pre-screening, with auditable eligibility justifications and clinician review.

What is Dyania Health?

Dyania Health develops Synapsis AI, a clinical trial solutions platform that analyses electronic medical records to identify potential participants, pre-screen eligibility and assess study feasibility. It serves healthcare systems, clinical researchers and pharmaceutical sponsors, with additional applications in registry reporting and observational studies. Its approach combines medically trained language models with physician-defined eligibility logic and result review, with deployment inside a healthcare organisation’s on-premises or private-cloud environment.

Intended Use and Limitations

  • Cleveland Clinic announced an enterprise-wide Synapsis AI collaboration in August 2025, following cardiology and oncology pilots and neurology validation.

  • A study published in the Journal of Cardiac Failure reported 96.2% accuracy across 7,700 trial-specific questions for rare-disease eligibility screening; results apply to that evaluated workflow.

  • The Cleveland Clinic study documented auditable eligibility justifications and retained clinical-team validation as an essential safeguard.

  • Cleveland Clinic discloses that it has invested in Dyania Health and may benefit financially from technology sales, limiting the independence of its supporting evidence.

  • Dyania states that Synapsis AI runs within the healthcare organisation’s firewall, on-premises or in a private cloud, without transferring patient data outside that environment.

  • Dyania claims HIPAA/GDPR alignment and references HITRUST, but the reviewed product pages do not provide independently verifiable HITRUST or ISO certification details.

  • FDA clearance or approval and CE marking are not specified on the reviewed live product pages; these should not be assumed from clinical deployment.

  • Dyania reports physician involvement in eligibility-rule design and review of screening errors, and acknowledges that AI hallucinations have not been eliminated.

  • Dyania raised a $10 million Series A in October 2024, led by HealthX Ventures with participation from Tech Square Ventures and Cleveland Clinic Ventures.

  • Dyania’s website lists a 2025 Fierce Innovation Award in Artificial Intelligence Solutions; this is industry recognition, not regulatory approval or clinical certification.

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Stephen

Founder of HealthyData.Science · 20+ years in life sciences compliance & software validation · MSc in Data Science & Artificial Intelligence.
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