I am currently an Assistant Professor at University of California San Francisco in the Department of Surgery. My group develops computational models using machine learning to derive adverse event signatures linked to genotype and phenotype for the Athena Breast Health Network and I-SPY clinical trial (adaptive trial for high-risk breast cancer patients). We also develop predictive algorithms for biomarker discovery in our treatment-resistant cancer patients using gene expression and other omics data. I am also in charge of the clinical and molecular biomarker repository for the UCSF Breast Care Center and Clinical Trials. The goal of this initiative is to bridge clinical and genomic data of patients including 10 different data types (lifestyle, sequencing, her, etc.) to develop cohort-specific tools for investigators to access for research purposes.
As a strong proponent of transparency and research sharing platforms, I have built tools to share with the scientific community including PredMod, a post-translational modification prediction tool, CTRP (Cancer Therapeutics Research Portal), a cancer target discovery tool and most recently, PROBE, a clinical and biomarker discovery tool for clinical trials (paper submitted to AMIA). During my postdoctoral studies at the Broad Institute I led a large study of cancer cell line profiling and developed pipelines to automate predictive modeling of cancer line responses, and biomarkers of sensitivity. This highly collaborative project involved other internal Broad groups such as RNAi, the Cancer Cell Line Encyclopedia, and pharmaceutical companies such as Novartis.
I chair the Data Science Working Group, and the Patient Reported Outcomes Working groups for the I-SPY Trial. Recently I was awarded the Interstellar Award for my contributions to biomarker discovery in cancer and aging, and previously I was a White House Presidential Innovation Fellow.