Lacey leads the Informatics team, which focuses on using integrated multi-omic data analysis to uncover biomarkers, mechanisms of action, and novel therapies from cancer immunotherapy patient data. Lacey's team specializes in interrogating datasets with small N, large P (many data points, few patients). At the Parker Institute, Lacey has also led the development of a best-in-class data platform to store, integrate, and analyze data from 20+ molecular data types with detailed clinical outcomes and annotation. Before joining the Parker Institute, Lacey worked in various roles in industry and academia, creating novel methods and platforms to analyze biological and patient data. She has a PhD from Stanford University, where she developed algorithms for analyzing brain imaging data, and did her bachelors work and cognitive science and AI research at MIT.
Cancer Immunotherapy Biomarkers from Multi-Omic Data
Lessons in finding biomarkers of response and resistance to cancer immunotherapy using multi-omic data, including DNA sequencing, RNA sequencing, high-dimensional flow cytometry, mass cytometry (CyTOF), proteomics. Discussion of data platforms to store, organize, and analyze multi-omic data. Insights and applications in chemoimmunotherapy for patients with Pancreatic Cancer.