When it comes to building the ideal patient cohort, the breadth and variety of demographic and clinical criteria available to select from is critical. The more you have to choose from, the more specific and targeted you can get in selecting the patient group most aligned with your therapy.
With many of today’s pharmaceutical brands treating second-line, third-line, or later stage patients as well as those with or without a certain biomarker, lab data is a key RWD asset. Making lab data “analytics-ready” at scale requires machine learning (ML), natural language processing (NLP), artificial intelligence (AI) and other significant domain expertise to harmonize unstructured and unstandardized diagnostic results.
Join Prognos’ Chief Medical Information Officer, Jason Bhan, M.D., Chief Data Scientist, Adam Petranovich, and Su Huang as they share:
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