Identify patients with undiagnosed Hereditary Angioedema (HAE) earlier in their patient journey using real-world data and explainable AI
Transform fragmented healthcare data into actionable patient intelligence. Our HAE Patient Finder uncovers high-probability patients, prioritizes physician engagement, and enables earlier diagnosis – helping life sciences organizations improve patient outcomes while maximizing the impact of commercial and medical initiatives.
The Challenge
The diagnostic journey is too long. AI can shorten it.
Patients with HAE often experience years of delayed diagnosis due to nonspecific symptoms, fragmented care pathways, and frequent misdiagnosis. During this period, patients endure repeated emergency visits, unnecessary procedures, and significant disease burden.
Traditional patient identification approaches rely on confirmed diagnoses – missing patients who have yet to be recognized.
Chryselys’ Patient Finder solution powered by AI changes that.
Our Solution
From Healthcare Data to Actionable Patient Intelligence
The HAE Patient Finder analyzes longitudinal healthcare data – including medical and pharmacy claims, diagnosis history, procedures, provider interactions, and treatment patterns – to identify patients who exhibit hidden clinical signatures of HAE.
Rather than waiting for a diagnosis, the platform predicts which patients are most likely to have HAE and provides transparent explanations behind every prediction.
AI-Powered Patient Identification
Detect patients with a high likelihood of undiagnosed HAE using advanced machine learning trained on longitudinal healthcare data.
Explainable AI
Understand why every patient is identified with interpretable risk drivers, improving confidence for medical, analytics, and commercial teams.
Precision HCP Targeting
Identify physicians managing high-risk patients to enable focused medical education and diagnostic awareness initiatives.
Patient Prioritization
Rank patients by diagnosis probability, clinical evidence, and engagement opportunity to optimize field execution.
Continuous Learning
Models continuously improve as new healthcare data becomes available, ensuring predictions remain relevant and accurate.
Business Impact
Deliver measurable value across the patient journey
Earlier Patient Identification (9 out of 10 Patients flagged correctly identified)
Discover potential HAE patients before diagnosis, enabling faster intervention.
Smarter Medical Engagement through explainable AI
Prioritize physician outreach using AI-generated patient intelligence.
Higher Diagnostic Efficiency
Focus diagnostic efforts on the patients most likely to benefit.
Better Patient Outcomes
Reduce the diagnostic odyssey and improve timely access to appropriate therapy.
Optimized Commercial Investment
Allocate field and medical resources where they can create the greatest impact.