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Big Data for Breast Cancer: A Patient/Advocate Perspective Jane Perlmutter October 8, 2015 , 1989 Topics • What is Big Data & why is it important? • What are some issues & concerns to patients/advocates? • What can we learn about these issues from examples of Big Data projects? • How can we make a difference? What is Big Data? The Three Vs of Big Data JP View of What Big Data Is (and Isn’t) Types of Data/Examples Quantity/ Quality Inference Method of Data Interventional— Small / Excellent Randomized Clinical Trials Observational— Medium / Fair Registries, Surveys Unstructured— Large/Challenging Social Media, research articles Analysis of Variance Big Data—Combining Large / Poor Multiple Types & Data Sources Multi-dimensional Analyics and Visualization Tools Regression Artificial Intelligence, Natural Language Processing Types of Health Data Patient Records • Patient Charts • Electronic health records (EHRs) Billing/Payment History Patient Provided Input • Patient reported outcomes • Passively collected patient data • Social media Clinical Trials Data ‘omics Data • Mutations • Copy number alterations • INDELs/SNPs • RNA/protein expression • Epigenetics • Metabiome • ... Why Big Data? JP View of Why Big Data Promise • Better predictions about heath risks • Faster development of treatments • More rapid progress toward precision medicine • More efficient use of health resources Risk • Immature methodology erroneous inferences • Breach of security loss of privacy • Hoarding of data slowing progress Patient/Advocate Issues • Patient/Advocate issues are not unique to them • Sponsors & Investigators share these concerns, though they sometime take a backseat to technical & scientific issues • Patients/advocates have a different filter, are more focused on these issues, and can bring them to the forefront Patient/Advocate Issues • Research Priorities • Data Quality & Representativeness • Data Control & Sharing • Who Pays & How is it Sustained • Security & Privacy • Informed Consent & Returning Results OHRP’s NPRM • OHRP--Office of Human Research Protection • Common Rule--Rule of ethics regarding biomedical and behavioral research involving human subjects in the US • NPRM--Notice of Public Rule Making (9/8/15) Announced New Requirements • Written consent is required for all research use of biospecimens, even those that have been stripped of identifiers • Must specify that biospecimens might be used for commercial profit, but not patient profit • Must specify whether and how relevant research results (individual and/or aggregate) will be disclosed to patients • Some exempt and all non-exempt research must provide privacy safeguards for biospecimens and identifiable private information. – Surveys, interviews, educational tests, etc. – Secondary research • Defines data security protections that are required and that they must be described in consent documents Cancer Big Data Examples and Some Issues They Raise • ‘Omics: Visualization, analysis and download of large-scale cancer genomics data sets for research • Learning Systems: Real world data for quality improvement and research • Clinical Trials: Data sharing from clinical trials for research Other Interesting Health Examples • Surveillance: Multi-source data to monitor unidentified toxicities and drug interactions • Infrastructure: For comparative effectiveness research and other patient-centered health research • Patient Entered Data: Patient support and information sharing • Artificial Intelligence Processing: How to Make a Difference? • Ensure patients/advocates are “at the table” and heard when decisions are made about Big Data projects • Inform patients/advocates and the public about potential benefits and concerns associated with health data • Be discriminating in providing support to excellent projects by encouraging patients and researchers to share data • Learn more Take Home Messages • Big Data has lot’s of potential, but its more complicated than we can imagine – Technical issues – Political/economic issues – Patient ethical issues • Including patients/advocates from the beginning will lead to better, faster, and more acceptable results