Big Data for Breast Cancer: A Patient/Advocate Perspective Jane Perlmutter October 8, 2015.

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Big Data for Breast Cancer: A Patient/Advocate Perspective Jane Perlmutter October 8, 2015

Transcript of Big Data for Breast Cancer: A Patient/Advocate Perspective Jane Perlmutter October 8, 2015.

Page 1: Big Data for Breast Cancer: A Patient/Advocate Perspective Jane Perlmutter October 8, 2015.

Big Data for Breast Cancer: A Patient/Advocate Perspective

Jane PerlmutterOctober 8, 2015

Page 2: Big Data for Breast Cancer: A Patient/Advocate Perspective Jane Perlmutter October 8, 2015.

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1989

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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?

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What is Big Data?

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The Three Vs of Big Data

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JP View of What Big Data Is (and Isn’t)Types of Data/Examples

Quantity/ Quality of Data

Inference Method

Interventional—Randomized Clinical Trials

Small / Excellent Analysis of Variance

Observational—Registries, Surveys

Medium / Fair Regression

Unstructured—Social Media, research articles

Large/Challenging Artificial Intelligence, Natural Language Processing

Big Data—Combining Multiple Types & Data Sources

Large / Poor Multi-dimensional Analyics and Visualization Tools

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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• . . .

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Why Big Data?

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JP View of Why Big Data

Risk• Immature methodology erroneous inferences

• Breach of security loss of privacy

• Hoarding of data slowing progress

Promise• Better predictions about heath

risks• Faster development of

treatments• More rapid progress toward

precision medicine• More efficient use of health

resources

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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

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Patient/Advocate Issues

• Research Priorities• Data Quality &

Representativeness• Data Control & Sharing• Who Pays & How is it

Sustained• Security & Privacy• Informed Consent &

Returning Results

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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)

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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

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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

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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:

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• 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

How to Make a Difference?

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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