PredictIQ™

SRI offers a predictive modeling framework that enhances data utility for pharmaceutical clients by integrating large datasets, including claims and EMR, to address complex business questions in oncology. The approach overcomes data hurdles like missing tumor stage information by developing innovative proxy rules, validated across diverse data sources for accuracy.

Key applications include improved patient targeting, dynamic call plans, segmentation, patient journey tracking, and payor insights, all driven by machine learning and business rule analytics. Case studies highlight the solution’s effectiveness at accurately identifying target patient groups, measuring treatment outcomes, persisting rates, and supporting market sizing for specific cancer stages. The process emphasizes close validation steps, agile analytics, and real-world evidence to drive actionable strategic decisions for clients.

This modeling enables optimized product positioning, campaign targeting, and comprehensive competitive benchmarking across physician and patient cohorts.