Demystifying Analytics and Machine Learning in Clinical Trials
Managing clinical data quality for excellence is more challenging than ever before. The explosion in variety, volume, and complexity of "new" data sources (imaging, eSource, omics, real-world evidence) is often difficult to integrate with "traditional" data sources like EDC and lab data—thus failing to provide a more comprehensive understanding of a patient and/or trial's total quality.
Recent regulatory advancements, combined with sophisticated analytics and machine learning techniques, presents exciting opportunities to change the way we oversee data, achieve a truly holistic understanding of data quality, and gain confidence in identifying data issues throughout the clinical trial process.
In this webcast, a group of subject-matter experts will explore:
- Critical data and processes as a foundation for better data quality
- Leveraging powerful analytics & machine learning to improve data quality
- Proven and effective approaches to improving data quality - one patient at a time, one study at a time or throughout the clinical trial process.
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