Syapse experts Anna Berry, Mary Tran, and Michael Italia share how to establish high quality, real-world datasets by using a multi-source strategy.
A single source of data is often not enough to generate meaningful real-world evidence. Have you recently made an investment in a large raw real-world dataset, and are now drowning in data but lacking in evidence?
Watch as experts highlight strategic approaches you and your organization should consider as you invest in RWD to best capture the comprehensive patient journey needed to answer your most challenging questions, or seek to validate real-world endpoints.
Key Topics Include:
- Awareness on various RWD sources and their attributes, and how they are used to fill in the gaps to ensure your study design best reflects what is happening in the real-world
- Understanding whether artificial intelligence (AI) is a magical cure-all, or is it perpetuating inconsistencies or biases already in the data?
- How to take unstructured lab and pathology reports (including biomarker data) using NLP to ensure your study design best reflects what is happening in the real-world to generate more robust data
Molecular Pathology, Genomics and Laboratory Medicine