The adaptable nature of artificial intelligence (AI) and machine learning algorithms allows researchers to implement these methods across many stages of pharmaceutical development, from drug synthesis to biomedical testing. However, it is challenging to standardize storage and management of complex clinical data such as medical imaging data. To successfully prepare imaging data for AI projects, researchers need centralized and curated data storage. 

Download this white paper from Flywheel to learn how to make imaging data AI-ready for drug development.

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