Harnessing Edge Informatics to Accelerate Collaboration in BioPharma (Bio-IT World 2016)

Tom Plasterer, PhD.Research & Development Information (RDI)Director, US Cross-Science

Harnessing Edge Informatics to Accelerate Collaboration in

BioPharma

WINNER

The US Cross-Science Team in Research and

Development Information (RDI) is a group of

informaticians, mathematicians, project/

program managers, developers, architects

dedicated to data science—data discovery, data

reuse, data harmonization, analytics and self-describing data

or Smart Data

We strive to create tangible digital and social

artefacts used to accelerate delivering

medicines to patients and improving their impact

once in the clinical setting.

These artefacts include web-based software,

community-driven data models, data sharing best

practices, data science communities of practice and strong advocacy of

Smart Data inside and out of AstraZeneca.

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Sharing & Collaboration: Are you a Data Parasite?

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Sharing & Collaboration: Are you a Data Parasite?

‘A second concern held by some is that a new class of research person will emerge — people who had nothing to do with the design and execution of the study but use another group’s data for their own ends,

possibly stealing from the research productivity planned by the data gatherers, or even use the data to try to disprove what

the original investigators had posited. There is concern among some front-line researchers that the system will be taken

over by what some researchers have characterized as “research parasites.”’

Dan Longo and Jeffrey Drazen, the deputy editor and editor-in-chief, NEJM

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Sharing & Collaboration: Are you a Data Parasite?

‘A second concern held by some is that a new class of research person will emerge — people who had nothing to do with the design and execution of the study but use another group’s data for their own ends,

possibly stealing from the research productivity planned by the data gatherers, or even use the data to try to disprove what

the original investigators had posited. There is concern among some front-line researchers that the system will be taken

over by what some researchers have characterized as “research parasites.”’

Dan Longo and Jeffrey Drazen, the deputy editor and editor-in-chief, NEJM

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Sharing & Collaboration: Are you a Data Parasite?

‘A second concern held by some is that a new class of research person will emerge — people who had nothing to do with the design and execution of the study but use another group’s data for their own ends,

possibly stealing from the research productivity planned by the data gatherers, or even use the data to try to disprove what

the original investigators had posited. There is concern among some front-line researchers that the system will be taken

over by what some researchers have characterized as “research parasites.”’

Dan Longo and Jeffrey Drazen, the deputy editor and editor-in-chief, NEJM

‘The condescension implicit in this statement is deeply

troubling. Drazen and Longo are saying, essentially, that only the people who originally collect a

data set can truly understand it, and anyone else who wants to

take a look is a parasite.’

Steven Salzberg, JHU

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Sharing & Collaboration: Are you a Data Parasite?

‘A second concern held by some is that a new class of research person will emerge — people who had nothing to do with the design and execution of the study but use another group’s data for their own ends,

possibly stealing from the research productivity planned by the data gatherers, or even use the data to try to disprove what

the original investigators had posited. There is concern among some front-line researchers that the system will be taken

over by what some researchers have characterized as “research parasites.”’

Dan Longo and Jeffrey Drazen, the deputy editor and editor-in-chief, NEJM

‘The condescension implicit in this statement is deeply

troubling. Drazen and Longo are saying, essentially, that only the people who originally collect a

data set can truly understand it, and anyone else who wants to

take a look is a parasite.’

Steven Salzberg, JHU

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Sharing & Collaboration: Are you a Data Parasite?

‘A second concern held by some is that a new class of research person will emerge — people who had nothing to do with the design and execution of the study but use another group’s data for their own ends,

possibly stealing from the research productivity planned by the data gatherers, or even use the data to try to disprove what

the original investigators had posited. There is concern among some front-line researchers that the system will be taken

over by what some researchers have characterized as “research parasites.”’

Dan Longo and Jeffrey Drazen, the deputy editor and editor-in-chief, NEJM

‘The condescension implicit in this statement is deeply

troubling. Drazen and Longo are saying, essentially, that only the people who originally collect a

data set can truly understand it, and anyone else who wants to

take a look is a parasite.’

Steven Salzberg, JHU

‘But the science, data, and research results are trapped in silos,

preventing faster progress and greater reach to patients. It’s not

just about developing game-changing treatments — it’s about

delivering them to those who need them.’

Vice President Biden’s Blog

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Public Research, Private Results?

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Public Research, Private Results?

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Public Research, Private Results?

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Public Research, Private Results?

‘Payment of 32 dollars is just insane when you need to skim or read tens or hundreds of these papers to do research. I obtained these papers

by pirating them. Later I found there are lots and lots of researchers (not

even students, but university researchers) just like me, especially

in developing countries. They created online communities

(forums) to solve this problem.’

Alexandra ElbakyanSci-hub operator

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Sharing Clinical Trial Results

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Sharing Clinical Trial Results

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Sharing Clinical Trial Results

Thousands of clinical trials have not reported their results; some have not even

been registered.

Information on what was done and what was found in these trials could be lost

forever to doctors and researchers, leading to bad treatment decisions, missed

opportunities for good medicine, and trials being repeated.

All trials past and present should be registered, and the full methods and the

results reported.

We call on governments, regulators and research bodies to implement measures to

achieve this.

AllTrials.Net Petition(2015)

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Sharing Clinical Trial Results

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Sharing Clinical Trial Results

• Maximize the benefits while minimizing the risks of sharing clinical trial data

• Respect individual participants whose data are shared

• Increase public trust in clinical trials and the sharing of trial data

• Conduct the sharing of clinical trial data in a fair manner

IOM Report: Sharing Clinical Trial Data: Maximizing Benefits, Minimizing Risk

(2015)

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Edge InformaticsInterfaces within the Drug Development Process

Target Discovery

NGS Exome analysis

Pathway Analysis

StructureAnalysis

Lead Discovery

RNAi

Assay Development

HTS

Lead Optimization

SAR

In vivo non-human testing

Exploratory PK

Exploratory Tox

Pre-Clinical Development

GLP Tox

Formulation

ADME

PK

Efficacy

Clinical Development

IND

Safety, Tolerability

Phase I-III

Registration

NDA/BLA

MAA

Marketing & Sales

PMRREMS

PSUR

Observational Research

Pathway Enrichment

Disease Contextualization

Seamless information connectivity (an EDGE) needed across domain NODEs

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Integration Quandary: Content Does Not Combine Easily

Fit-for-Purpose to “Standards”

Models

Structured

Triplestores

Semi-StructuredUnstructured

Content

Lack of Compatible

Containers → the ”Plumbing

Problem”

Lack of Compatible

Semantics→ the ”Meaning Problem”

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What’s Needed?Linked Data!

LOD Cloud 2014Schmachtenberg, Bizer, Jentzsch and Cyganiak.http://lod-cloud.net/

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What’s Needed?Linked Data!

LOD Cloud 2014Schmachtenberg, Bizer, Jentzsch and Cyganiak.http://lod-cloud.net/

“Smart Data” means information that actually makes sense.

Wired Magazine, April 2013

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Thanks to: Eric Little, VP Data Science, Osthus

The Emergence of Smart DataStandards Driven at Container Interfaces

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Competitive Intelligence 360 (CI360) ApproachFlexibly Addressing Key Questions

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Capture Business Questions and

Sources

Domain Expert Concept Map

Build Formal Ontology

Challenge with Linked Data

Examine with a Faceted Browser

Share insights with a Knowledge

Base

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Capture Business QuestionsCapture Business

Questions and Sources

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Translate Questions into ConceptsDomain Expert Concept Map

“Where are the key clinical studies in NSCLC and who are the principle investigators?”

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Challenge with Data“Where are the key clinical studies in NSCLC and who are the principle investigators?”

(one example)

Challenge with Linked Data

Source: https://clinicaltrials.gov/ct2/show/NCT02027428

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Refine the AnswerExamine with a

Faceted Browser

“What are the open trials in metastatic breast cancer and what drugs are being tested?”

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Share Insights as a Community“Can a biomarker defined population be added to a trial record?”

Share insights with a Knowledge

Base

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Data FAIRport

To be Findable:F1. (meta)data are assigned a globally unique and persistent identifierF2. data are described with rich metadata (defined by R1 below)F3. metadata clearly and explicitly include the identifier of the data it describesF4. (meta)data are registered or indexed in a searchable resource

To be Accessible:A1. (meta)data are retrievable by their identifier using a standardized communications protocolA1.1 the protocol is open, free, and universally implementableA1.2 the protocol allows for an authentication and authorization procedure, where necessaryA2. metadata are accessible, even when the data are no longer available

To be Interoperable:I1. (meta)data use a formal, accessible, shared, and broadly applicable language for knowledge representation.I2. (meta)data use vocabularies that follow FAIR principlesI3. (meta)data include qualified references to other (meta)data

To be Reusable:R1. meta(data) are richly described with a plurality of accurate and relevant attributesR1.1. (meta)data are released with a clear and accessible data usage licenseR1.2. (meta)data are associated with detailed provenanceR1.3. (meta)data meet domain-relevant community standards

InteroperabilityInvestment

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Naming ThingsUse Resolvable URIs

InteroperabilityInvestment

http://purl.uniprot.org/uniprot/P30453

http://www.uniprot.org/uniprot/P30453

http://purl.uniprot.org/uniprot/P30453.ttl

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Describing DataReuse, Reuse, Reuse (build only if essential)

InteroperabilityInvestment

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Describing DataReuse, Reuse, Reuse (build only if essential)

InteroperabilityInvestment

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Describing DataReuse, Reuse, Reuse (build only if essential)

InteroperabilityInvestment

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Finding DataVocabulary of Interlinked Datasets (VoID)

InteroperabilityInvestment

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Cross-BioPharma Data Standardization EffortsInteroperability

Investment

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Open Data, Open Science Efforts

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Open Data, Open Science Efforts

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Open Data, Open Science Efforts

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Open Data, Open Science Efforts

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Open Data, Open Science Efforts

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Open Data, Open Science Efforts

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Get your plumbing right• And your data won’t be stuck in a silo

Leverage working public solutions• Don’t reinvent the wheel

Use Edge Informatics• Consider handoffs—you don’t know how your data will be used in the

future

Invest in Data Stewardship• Small tax to future-proof your efforts

Data and Collaboration ARE Business Assets