Speaker Profile

M.D., Ph.D., Director of Product Management, Flatiron Health
Biography

Vineeta is a physician-scientist who is passionate about the intersection of data science and health care. As a director of product management at Flatiron Health, she works with a cross-disciplinary team to build national-scale, research-grade databases that integrate electronic health records and genomic data for translational/outcomes research and drug development in oncology. Previously, Vineeta conducted genomics research at the Broad Institute of Harvard & MIT. She has also been a data scientist at the Boston-based health tech startup Kyruus, and a management consultant for biotech, pharmaceutical, and medical device clients at McKinsey & Company in New York. Vineeta has a B.S. in biophysics from Stanford University. She earned M.D. and Ph.D. degrees from Harvard Medical School and MIT.

Talk

Real-World, EHR-Linked Clinico-Genomic Datasets to Accelerate Cancer Research
As cancer patients receive care in the real world, electronic health records (EHRs) create an ever-growing, rich digital footprint of symptoms, treatments, and outcomes. Concurrently, tumor molecular profiling is being conducted to identify optimal therapies as part of routine care. How can these “real-world” data be harnessed to enable faster learning in oncology?

We describe a new paradigm for creating a continuously refreshing, real-world clinico-genomic database (CGDB) that overcomes traditional data flow barriers. We developed HIPAA-compliant processes to link patient-level clinical data from EHRs across the U.S. (in the Flatiron Health network) with patient-level tumor sequencing data from Foundation Medicine. These data were strictly de-identified for research.

The CGDB includes >20,000 patients (>3000 with lung cancer, >2000 with colon cancer, >2000 with breast cancer) and grows quarterly. Genomic alterations (SNVs, CNVs, rearrangements) across >300 genes, tumor mutation burden (TMB), and microsatellite instability (MSI) status are included, alongside treatment history and response data. The dataset recapitulates known survival trends for biomarker-defined sub-populations receiving targeted therapies (EGFR+, ALK+), and supports recent observation that high-TMB predicts response to checkpoint-inhibitor immunotherapies. The CGDB enables rapid queries for translational science, outcomes research, and trial design, and could ultimately extend even to the point-of-care.

Don't Miss Important Precision Medicine Updates

PMWC is the most comprehensive precision medicine conference. To receive the lastest news and updates from the field, subscribe to the newsletter here.

View the top 3 talks from PMWC here (password: top-videos).