CAR-T therapies present major challenges for patient prediction due to niche populations and limited data, with treatment costs reaching up to $1M per patient. A research team initially built models using IQVIA claims data, achieving 60% precision in identifying eligible patients. By enriching these models with IQVIA Audience Identity Manager XR (AIM XR) behavioral insights on HCPs, precision improved to 65%—an 8% gain over claims alone. The integrated AI/ML approach not only enhanced targeting of CAR-T–treating physicians but also drove stronger ROI, showing the value of combining behavioral and clinical datasets for oncology modeling.

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