As AI becomes embedded in pharmaceutical research and development, its relationship with data is more critical than ever. AI algorithms are only as effective as the data they are trained on - making data quality, structure and harmonization foundational to success.
In the pharmaceutical industry, where innovation hinges on complex, high-volume datasets, curating and integrating clean, consistent, and comprehensive data is a strategic imperative.
This presentation will explore how high-quality data fuels AI-driven breakthroughs across drug discovery, clinical trials, and personalized medicine. It will address the persistent challenges of data silos, inconsistencies, and biases that hinder AI performance. Attendees will gain insights into how a disciplined approach to data management not only enhances predictive modeling and decision-making but also accelerates the path from research to real-world patient outcomes.
Key Takeaways:
Check out the incredible speaker line-up to see who will be joining Ayelet.
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