Optimizing Patient and HCP Targets
Identifying Undiagnosed IgA Nephropathy Patients for a Global Nephrology Brand
How a predictive model distinguished IgAN and non-IgAN patients with 94% accuracy.
THE CHALLENGE
A global pharmaceutical client was gearing up for the US commercial launch of their innovative therapy for IgA Nephropathy. To ensure a successful launch, they needed a comprehensive understanding of the IgAN landscape and sought to identify their target patient population.
However, the challenge lay in the overlapping diagnosis codes, which made it difficult to define this population clearly. To address this, the client enlisted EVERSANA to identify ‘relevant’ IgAN patients, including those who were undiagnosed or misdiagnosed, ahead of the drug launch.
THE SOLUTION
- EVERSANA partnered with a client to identify a relevant IgAN patient population in collaboration with the medical team and defining inclusion/exclusion criteria in claims data.
- We leveraged AI and ML based predictive modeling on real-world evidence data to identify diagnosed and undiagnosed IgAN patients and optimize HCP targets for the client.
- EVERSANA created patient clusters with unique characteristics and identified the treating HCPs for targeting.
- We also provided the client with a full-service launch solution including a prelaunch commercial model design.
THE RESULTS
The predictive model proved impressive results:
High-Accuracy Patient Targeting
EVERSANA developed a highly accurate predictive model, achieving a 94% success rate in distinguishing between IgAN and non-IgAN patients with statistically significant precision.
Patient and HCP Identification
The model identified 4,868 undiagnosed IgAN patients and approximately 3,000 Nephrologists and Internal Medicine healthcare providers who were treating these undiagnosed patients.
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