megatrends impacting biospecimen management … 1 megatrends impacting biospecimen management and...

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Megatrends Impacting Biospecimen Management and

Ethical Considerations

Kenneth A. Wilke, BioStrategy SolutionsBig Data and the IRB Conference

Hosted ByQuorum Review IRB, MA Society For Medical Research, Boston University

Cambridge, MAOctober 24, 2014

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Ken Wilke Presentation - Big Data and the IRB Conference - 24 October 2014 3

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My Objective Today

Provide a framework to assess the key forces shaping the future of health care and drug development, with particular focus on trends impacting clinical research, biospecimen management and associated ethical considerations

Stimulate further thought and discussion on how various stakeholders in the clinical research community can best leverage and shape the new opportunities provided by these emerging trends


“Megatrend” Defined

General shift in thinking or approach affecting countries, industries and organizations (Naisbitt, 1982)

Global, sustained and macro economic forces of development that impacts business, economy, society, cultures and personal lives thereby defining our future world and its increasing pace of change (Frost & Sullivan)


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Summary of Naisbitt’s Original Megatrends (1982)

(1) Industrial society

(2) Technology “push”

(3) National economy

(4) Short term perspectives

(5) Centralization

(6) Government / institutional dependence

(7) Representative democracy

(8) Hierarchies

(9) Northeastern bias

(10) Seeing things as "either/or”

Information society

“Pull” demand for technology

Global marketplace

Long term perspective

Decentralization

Self-help

Participative democracy

Networking

Southwestern bias

Seeing more choices.


Thinking About How Current Megatrends Impact Biospecimen Management

Focus primarily on changing landscape for drug development /clinical trials and impacts for management of specimens acquired through clinical trials

Theme A

Theme B

Theme C

Trends 1,2,3 …

Trends 1,2,3…

Trends 1,2,3…

IMPACTS


Image credit – commons.wikimedia.org

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Presentation Overview6 KEY THEMES

Demographics

Globalization

Technology

Evolving US Health Care System

Changing Drug Development Paradigms

High Performance (4P) Medicine


IMPACTSON

BIOSPECIMENMANAGEMENT


Demographics

Aging population “explosion” of

chronic disease incidence

cost burden on system

Overall population growth, burgeoning global middle class Increased demand for health care services

Greater need for solutions targeted to diverse populations

Image Credit – The Wisdom Years (wisdom.unu.edu)


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Globalization

Global interconnectedness More global / ex-US clinical trials

Outsourcing / “off-shoring” of work, increase in activity ex-US

Global disparities –differences in: Cultural norms

Regulations

Approach to privacy issues

Image credit – deviantArt

Image credit – Unesco


Technology

Changes in how medicine is delivered, physician roles, skills and expertise required of physicians

Genomics

Mobile Devices

Point-of-Care Testing

Big Data


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Genomics

“Super Moore’s Law” for gene sequencing

“within a decade, I think everyone will have their complete DNA sequenced”

Barry Starr, Director, Stanford at the Tech

Moving toward WGS as a routine diagnostic?

Information management challenges!

As quoted in e-article at www.BioPharmaDIVE.com ”The revolution will be personalized: An interview with two Stanford geneticists” by Sy Mukherjee, October 1, 2014


Mobile Devices (1 of 3) Increasing use – wide variety of technologies and applications

“23 notable FDA clearances of mobile health devices in 2014”*

“100 million wearable health devices to be shipped in next five years…”**

*on-line article-mobilehealthnews.com, September 24, 2014

**on-line article-medcitynews.com, September 12, 2014

Image credit – IBM / ecrim.edu


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Mobile Devices (2 of 3)

Photo credit – Propeller Health

Photo credit – Ginger.io


Mobile Devices (3 of 3)

Technology integration / development of platform technologies Entry of Google, Apple, Samsung in 2014

Linkage of mobile devices to smartphones and EMR systems (e.g. Apple/Epic)


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Point-Of-Care (POC) Testing

DNA Sequencing

Molecular Diagnostics Miniaturized / cartridge-based

systems Provide access to developing world

populations (notably for infectious diseases)

Example Companies/Products: Epistem Genedrive, BioMerieuxBioFire, QuantuMDx Q-POC

Potential for integration of POC devices with mobile technology platforms

Miniaturization of sophisticated testing processes


Big Data Increasing sophistication of “Big Data” solutions to handle increasingly complex problems

Increased volume, diversity of data and number of data sources integrated

Challenge of connecting traditional data “silos” (e.g. pharma discovery research and clinical trial data) as well as legacy data

Need to extract useful, actionable information - customized to an individual patient level.


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Big Data Applied to Biomarker Research and Biospecimens (1 of 4)

Ability to link disparate data sets in a unified structure with harmonized ontologies

Ability to perform complex queries to identify data associations and subject/sample cohorts based on multiple parameters

Ability to perform “in-silico” analyses


Big Data Applied to Biomarker Research and Biospecimens – 2 of 4 (Data Sources)

Bio-repository Facilities

Biospecimen and Biorepository Management System

Clinical Trial MgmtSystem

Data Management

Electronic Data Capture (Inform) and Clinical Data Repository

Database(s)

Treatment


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Big Data Applied to Biomarker Research and Biospecimens – 3 of 4 (Example Query)

1. Identify DNA specimens collected from the MK-XXXX clinical trial, with confirmation that the subject signed the future research consent.

2. Given this sample set, identify which of these subjects experienced an adverse event during the clinical trial.

3. From this, provide the list of available specimens / subjects, with DNA quality indicated along with indication of whether or not this subject was on the drug or placebo treatment arm

Data From Three Separate Sources Required:

Specimen Inventory System (external vendor)

Adverse Events (Clinical Data Repository)

Treatment Schedule


Big Data Applied to Biomarker Research and Biospecimens – 4 of 4 (Graphical Query)

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Evolving U.S. Health Care System

Focus on prevention More diagnostic tests

Consolidation of provider market, greater points of leverage with remaining providers

Performance-based approaches

Accountable-care organizations (vs. fee-for-service)

Enabled by EMR’s

Evidence-based medicine (“value-mining”) vs. hypothesis driven trials

Payer-Provider-Pharma collaborations

Efforts to expand access, improve outcomes, and control costs

Image Credit – taxpol.blogspot.com


Changing Drug Development Paradigms

Blockbuster to Targeted

Response to global shifts in market share (toward developing / emerging countries)

Greater emphasis on partnerships, collaborations, sharing of “pre-competitive” information Cross-industry partnerships pharma as a “health care partner” (e.g. Merck, Regeneron

partnerships with Geisinger)

Biopharma sharing of clinical trial data Collaborative trials including public / private (e.g. I-SPY2)

Development of “Holistic Open Learning Networks” (Ernst & Young)


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Examples of New Innovation and Collaboration Models

• Collect• Consume• Curate• Connect

“Crowdsourced” clinical trial protocol development

Non-profit organization enabling collaboration via open systems and redefined incentives and norms

Wiki-like model with an open app store.



4P - Preventative, Predictive, Personalized, Participatory

Increased Patient Engagement in Medical Research PatientsLikeMe – database of 250,000

patients Collaborations with pharma to improve

trial design, recruitment, collection and analysis of “real-world data”

Faster answers to clinical research questions?

Increased Patient Access To and Control of “Their” Data Patient-managed return of results Patient controlled biospecimen use

and release of medical info


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Evolving Social, Legal, and Regulatory Environment for Genomics Research and Associated Privacy Protection Myriad Supreme Court Decision

23 And Me FDA Ruling

New (Draft) EU Data General Data Protection Regulation

Improving DNA Sequencing and Analysis Technology - Inherent “Identifiability” of DNA

Should Privacy Protection Laws Focus More on Penalizing Improper Data Use vs. Reliance on De-Identification?


Image credit – commons.wikimedia.org

Ethical Considerations – Informed Consent For Biospecimen Research

Drawbacks of Traditional Consent Model for Biospecimen Research

Static Site/IRB/country variations – may limit future use value of

specimens, difficult to track Pharma owns specimens and data De-identification adds complexity and prevents direct

contact back to patient (e.g. to communicate when/how samples are used or for return of results)

New Consent Models Not limited by the boundaries of an individual trial or

institutions (how to ensure appropriate oversight?) Allows for broad future use (with patient consent) Dynamic vs. Static – Envisions re-use of existing data Portable Legal Consent (Sage)


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Additional Ethical Considerations

How to find the right balance between testing “because you can” vs. only to provide a clinically useful result - and when should it be mandatory to communicate findings to patients?

Pros and cons of allowing research subjects to be compensated for use of their genomic data?

How do traditional IRB and GCP oversight functions adapt to “patient community” based clinical research?

How to resolve conflicts between individual country data protection laws / regulations and the desire for trans-border data sharing?


Additional Ethical Considerations –Ongoing Harmonization Efforts

The Global Alliance For Genomics and Health 100+ partner orgs. across 15 countries

Working groups in Regulatory & Ethics, Data, Security, and Clinical

Public Population Project In Genomics and Society (P3G) Non-profit corporation

Provides tools and resources to support biobanking community

Supports “ELSI 2.0” – building the Ethical, Legal, and Social infrastructure necessary to the support the rapid changes in technology.

Proposed “Safe Harbor Framework for International Ethics Equivalency” (Dove, Knoppers, Zawati)


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Potential Impacts of Megatrends

on Biospecimen Management (1 of 4)

More complexity, particularly around data management and informatics

Continued / increasing needs for standardization to support broader collaborations, data integration, and data sharing (as well as ethics harmonization).




Changing demand for biorepository services

- increased demand from demographics

- reduced demand from more targeted trials?

- reduced demand from routine availability of WGS testing?

Need to develop expertise to operate in a more networked / collaborative environment - future with specimens collected by patients, tested on a mobile device and data uploaded to cloud for analysis?


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Need to develop operational and logistical solutions to support new clinical research structures and consent models that extend across multiple institutions/organizations.

More reliance on 3rd parties to provide sophisticated specimen management capabilities and expertise, allowing drug development organizations to focus resources on core research activities




Potential for new industry players …

will we see the biobank in the future?


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Questions / Discussion



Changing Drug Development

Paradigms

Evolving US Health Care System

Demographics

Technology

GlobalizationImpacts on Biospecimen Management

Ethics Consideration

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