A pharma client with oncology therapies sought to promote earlier adoption of first- and second-line maintenance indications. IQVIA developed machine learning models predicting patients likely to transition to maintenance or fail later-line therapies within three months. Predictions were linked to treating HCPs, generating timely field alerts. Compared to rules-based methods, precision improved 15x for patient identification and 10x for HCP linkage. Treatment initiation rates rose from 4% to 28% over three months, demonstrating the power of AI to accelerate adoption of innovative therapies.

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