Logo Linguistic harmony in the Tower of Babel; how Amgen joins reference data from bench to bedside The challenges associated with managing reference data create complexity and expense across all industries - in Life Sciences, Financial Services and Manufacturing, the problem is particularly acute. Amgen – an American multinational biopharmaceutical company – tackles the reference data issue by creating a linked vocabulary that is leveraged across the Pharma pipeline to streamline processes and enable faster time to market.

1. 1
LINGUISTIC HARMONY
IN THE TOWER OF BABEL
HOW AMGEN JOINS REFERENCE DATA FROM BENCH TO BEDSIDE

2. 2
WHO’S SPEAKING TODAY?
Anne Lapkin
SVP Global Strategy
Smartlogic
Dr. Alice “Clare” Augustine
Vocabulary Management Lead
Amgen

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A FEW HOUSEKEEPING ITEMS

4. 4
The reference data problem
A bit about Amgen
Amgen’s approach to reference data
Amgen business uses
A bit about Smartlogic and Semaphore
Summary
Q & A
AGENDA

5. 5
• Every industry has a reference data problem
– Keeping reference data synchronized across all systems is difficult, time consuming and expensive
– Different systems use different representations of reference data, leading to further confusion
– Accenture estimates that in the Investment Banking sector, the total cost of reference data
management in 2015 was more than $6 billion, with an average CAGR of 9% until 2020
– Industry bodies work on standard reference data vocabularies, but integrating them into enterprise
systems is the responsibility of individual organizations
• Master Data Management (MDM) has been positioned as a solution, but has not
been very successful
– Rationalizing the different vocabularies in use across the enterprise is difficult
– It does not take into account the valid business reasons that different parts of the organization have
for using different words to describe the same concept
– Mapping different system representations makes the problem more complex
Reference data – a problem across all industries

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ABOUT AMGEN
Oncology/
Hematology
Cardiovascular
Disease
Inflammation
Bone Health
Neuroscience
Nephrology

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Join data using consistent vocabulary across the pipeline
Bench to Bedside connectivity of data enables faster time to market
BUSINESS OPPORTUNITY: CONNECTED PHARMA PIPELINE

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WHY IS IT SO DIFFICULT
• Domain knowledge and
context are not included
• Different words describe the
same thing
• Sodium bicarbonate
• NaCLO3
• Alkali
• Salt
• E500
• So many sources, so little
time…

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AMGEN KNOWLEDGE CAPTURE METHODOLOGY
MODULAR AND LINKED
The Modular & Linked Methodology:
• Maximizes cross- functional and public data
integration
• Enables cross-domain search functionality
• Provides consistent vocabulary via
independent modules benefiting a localized
function (when desired).
• Knowledge captured in a way that is useful
for machine learning
• Empowers users to do sophisticated
querying and higher quality analytics

10. 10
Search
Final model
AMGEN
UBERON
SharePoint
DOWNSTREAM
SYSTEMS
Search
Independent model
Dependent model
Amgen Uber
Product
Amgen
Relationship
and Structure
Dependent model
Amgen Uber
Location
Independent model
Pipeline Candidate
independent model
Active
Pharmaceutical
Ingredient
Internal/External
source of terms
Source of terms
Independent model
Commercial
therapeutic product
Dependent model
Amgen Uber Party
Independent model
Amgen Uber Party-
Company
independent model
Amgen Uber Party-
Product Origin
Independent model
Amgen Uber
Geopolitical Area
Public source of
terms
Source of terms
SEMAPHORE
publish process
linking
linking
LINKED MODEL STRATEGY FOR AMGEN
Business
Systems

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BENCH TO BEDSIDE CONNECTIVITY OF DATA USING
PRODUCT THESAURUS
Research Development Manufacturing/Operations Commercialization
Generic
Name
Pipeline
Name
Target
Name
Indication
Device
Type
Device
Mechanism
Company
Name
Trade Name
1
Trade Name
2
Activation
Method
Device
Name
Company
Name
Modality
Therapeutic
Area
Mechanism
of Action
Developed By Has Modality
isDeliveredUsing
isEngineeredBy
isActivatedBy
isA
isApprovedIndicationFor
isApprovedIndicationFor hasDeviceInjectionMechanism
Has Active
Pharmaceutical
Ingredient
Has Active
Pharmaceutical
Ingredient
Targets
Has
Discovery
Molecule
Has MOAAffects Therapeutic Area

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Product Portfolio
Management
What drugs are delivered
using this delivery device
and which company
manufactures them?
Drug Delivery
Technology
Which drugs and delivery
methods are impacted by
this regulation?
Quality Systems
What are all the
regulations and patents
that are relevant to this
drug using this delivery
technology?
Translational
Sciences
Are there uncovered
pathways that specifically
impact a particular trait?
Regulatory/LAW
What are all the
indications for this drug
using a specific delivery
technology and what are
the attributes?
VALUE OF THE MODULAR LINKED REFERENCE DATA STRATEGY

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Drug, Drug Delivery, Modality, Company, Therapeutic Area
REFERENCE DATA IN ACTION

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Who we are
 Makers of Semaphore – the enterprise
class, W3C standards-based semantic
platform built on graph technology
 Global customer base of 250 organizations
 Solving business problems in many
industries, including Life Sciences, Financial
Services, Media and Entertainment,
Manufacturing, Aerospace and Defense
and Public Sector
 On-premises, in the cloud and hybrid
deployment
SMARTLOGIC SEMAPHORE INC.
We transform enterprise information
into actionable intelligence

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3 FUNCTIONAL CAPABILITIES OF SEMAPHORE
ENRICHMENT
Enrich the asset with tags defining what
it’s about
HARMONIZATION
Harmonize disparate information sources
against a canonical model
EXTRACTION
Extract facts, entities and
relationships
For example
• In the data analyzed for targeted marketing
campaigns is a sales receipt for item # 123-
456/elsa
• The model knows that item numbers in this
family are keychains and that Elsa is a
character in the movie Frozen
• By enriching the data element (the cash
register receipt) with additional context
(this is an Elsa keychain and connotes an
interest in the movie Frozen), additional
valuable information about the interests of
the customer can be used to tailor a
marketing offer that will attract him or her
For example
• A data lake contains measurements from
different sensors
• Different sensors use different vocabularies
– one might report tolerance in increments
of ¼”, while another might report in
μmeters
• The model knows that a sensor with an ID
from a particular family uses a specific unit
of measure and that the relationship
between that unit of measure and another
is in a specific formula used for conversion
to a common unit of measure for analysis
For example
• Banks must demonstrate to regulators that
they have sufficient assets to survive in
unfavourable conditions – a process known
as “stress testing”
• The data elements that they need to
analyse are buried in information assets
such as real estate investment agreements,
stock and bond portfolios and others
• The various information elements are
semantically modelled and the model used
to extract the critical entities, facts and
relationships
• The extracted data elements are analysed in
simulation of different economic conditions
to determine whether the assets are
sufficient

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• Easy to use
– SMEs directly participate
– Task based workflow and governance
• Flexible
– Model-driven rule generation
– Leverage linked vocabularies
– Full editorial control
• Precise and auditable
– Rule-based classification
– Supported by AI, NLP and machine learning strategies
– Full suite of analysis tools to track and audit results
• Enterprise grade
– Scalable
– Integrates with existing technology investments
– Cloud, hybrid, on-premises deployments
WHY IS SEMAPHORE BEST IN CLASS?
Ease of
use
Precision and
accuracy
Enterprise grade
Cost effective
New data
opportunities
Regulatory
Business user IT manager
Chief Data
Officer
Management

17. 17
We keep pace with our customers’ changing needs and market demands while maintaining an unwavering
commitment to quality
Product Development
& Maintenance
Semaphore Suite:
• Usability/workflow features
• New integrations
• Advances from R&D
• Maintenance
• 24x7 software incident Customer
Support
• Software patch access
• Software upgrade access
• Documentation
Semaphore Software
Enterprise semantic platform
• Easy to use
• Accurate
• Advanced graph architecture
• High performance
• OOTB integrations
• Enterprise scale
• Cloud, Hybrid, On-premises
Maintenance
• 24x7 software incident
customer support
• Software patch & upgrade
access
• Documentation
• Life with Semaphore portal
Semaphore Suite:
• Usability/workflow features
• New integrations
• Advances from R&D
• Maintenance
• 24x7 software incident
Customer Support
• Software patch access
• Software upgrade access
• Documentation
Professional Services
Our professional services team
works with customers to accelerate
deployments, avoid mistakes and
maximize their return on
investment with Semaphore.
Specialist knowledge in:
• Information science
• Ontology management
• Classification
• Triple/graph store
• Integration
• Content management
• Enterprise search
• Semantically-powered user
experience
Training
Semaphore Suite:
• Usability/workflow features
• New integrations
• Advances from R&D
• Maintenance
• 24x7 software incident Customer
Support
• Software patch access
• Software upgrade access
• Documentation
Self-paced training, short videos
and student exercises delivered
online or customized for your
enterprise.
• Model creation and
management
• Rule management
• Auto-classification
• Testing and mitigation
strategies
• Systems administration &
integration
Partners
Semaphore Suite:
• Usability/workflow features
• New integrations
• Advances from R&D
• Maintenance
• 24x7 software incident Customer
Support
• Software patch access
• Software upgrade access
• Documentation
We partner with:
• Industry leading technology
organizations
• System implementation
specialists
• Expert industry consultants
To deliver enterprise-grade
solutions to organizations around
the world.
SMARTLOGIC PRODUCTS AND SERVICES

18. 18
• Reference data is a problem across all industries
• Creating centralized, linked vocabularies that span the enterprise is the
key to solving the reference data problem
• Incorporating linked vocabularies supports local governance
• Solving the reference data problem positions you to streamline
operations and improve speed to market
SUMMARY

19. 19
FURTHER READING
Dr. Alice “Clare” Augustine
Vocabulary Management Lead
Amgen
Amgen Proprietary - Internal Use Only
www.gopowernutrition.com
OVER 175,000 HAPPY
BARS HAVE BEEN GIVEN
AWAY TO CHILDREN IN 18
MONTHS.
Alice Clara Augustine 2015 Integrating Agricultural data using Semantic Technologies to help farmers feed the world @
MarkLogic World 2015 Chicago, June 2, 2015.
Alice Clara Augustine 2015 Integrating Agricultural data using Semantic Technologies to help farmers feed the world @
DAMA @ St Louis
Alice Clara Augustine 2015 Integrating Agricultural data using Semantic Technologies to help farmers feed the world @
Wells-Fargo 9th April 2015 .
Alice Clara Augustine et al., 2006 Ontology development and use for efficient information input and retrieval (5th Conference
of the Asian Federation for Information Technology in Agriculture (AFITA- 2006) organized by the FAO – Johannes Keizer and
Gauri Salokhe
Alice Clara Augustine et al., 2004 Linguistic harmony in the tower of Babel. Plant and Animal Genome conference XII, San
Diego. USA

20. 20
Q&A
Thanks for joining the webinar
We’ll be taking questions now
Q A&

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