Tools to Address the Challenges of Preserving Privacy in Sharing and Analysis of Biomedical Data

Project Summary Understanding a single disease or condition requires large-scale mining of genetic, epigenetic, environmental, and clinical observations from large amounts of human data. Widespread and easy access to such data is imperative to decipher the vast trove of data that has been collected at the individual and population level. However, there is a direct conflict between protecting the privacy of patients and research participants and sharing genetic, epigenetic, and clinical data for biomedical advances. This conflict is partly due to a disconnect between the fields that generate and analyze personal biological data and the fields that establish theories and implementations for data privacy and security. The goal of this project is two-fold: 1) to quantify private information leakages from various types of human-derived biological data in a systematic manner to inform data-sharing efforts and 2) to develop privacy-enhancing analysis software for data at various molecular levels (genomics, transcriptomics, phenotype data) at scale. We will create an evolving and modular tool suite to both quantify and preserve privacy; this suite will have the ability to be adopted to new data modalities and analysis needs as they arise. The proposed tools will help prevent future catastrophic privacy leaks, which may result in a loss of access to all medically actionable data; democratize data access for all researchers; and create trust between patients and researchers, thus increasing participation in studies.