Xingyu (Luna) Li has been working in HEOR Analytics at Alexion, Astra Zeneca. She is a master student in Biomedical Informatics at Harvard Medical School with a MBBS degree from Sun Yat-sen University. Her previous research includes modeling of oncolytic virus, clinical decision support and representation learning of EHRs. These experiences made her realized that efficient clinical transformation of biomedical research should be guided by data-driven studies, and she wishes to bridge the gap between bench and bed in her future informatics studies.
Day 1: Dec 2, 2020
2:40 pm
2:40 pm
CASE STUDY: RARE DISEASES
Evaluation of Real-World Data Assets on Rare Diseases
There are many existing data sources that could be potentially used for real-world evidence generation purposes. However, majority of them are broad datasets with limited focus on rare diseases. This study gathers information on existing data sources in the indications and geography of interest, and compares the coverage, time span and capabilities of datasets. Evaluation of data quantity and quality in terms of rare diseases of interest is then performed to estimate potential bias in rare disease analysis by comparing demographics across datasets. Gain deeper knowledge to;
- Evaluate real-world datasets to provide assessment for fit for RWE generation in rare diseases
- Gather information on coverage, capacities, and characteristics of 10+ real-world datasets
- Provide insights on potential bias of broad datasets for rare disease analysis
Day 2: Dec 3, 2020
