Presentation Title Presentation Title Second Line

Taming
Your
Wild
Data
with
Pega
Presentation Title Presentation Title
Second Line
Kalim Saliba
Director Product Management, Information Experience, Pega
Ron Behling
Author
Scott Jennings
Title Director, BMS
Associate
Director of Pharmaceutical Development Informatics, BMS
Nitin Chander
Principal System Architect, Pega
This information is not a commitment, promise or legal obligation to deliver any material, code, or functionality and the development, release and timing of any features or functionality described for our products remains at our sole discretion. 2016. Confidential. Pegasystems, Inc.
©2016 Pegasystems Inc.
Our Speakers
Ron Behling
Scott Jennings
Nitin Chander
Director of Pharmaceutical
Development Informatics
Associate Director
Principal System Architect
Bristol-Myers Squibb
Bristol-Myers Squibb
Pega
3
Agenda
• BMS Pharmaceutical Development
• Lab Data Workflow
• LDW Demo – user POV
• Pega’s Data Capabilities
• How We Built LDW
• Challenges, Lessons Learned
• Business Value
• Q&A
4
Knection @ PEGAWORLD
Forward-Looking and Non-GAAP Financial Information
This presentation contains statements about the Company’s future plans and prospects that constitute
forward-looking statements for purposes of the safe harbor provisions under the Private Securities Litigation
Reform Act of 1995. Actual results may differ materially from those indicated as a result of various important
factors, including those discussed in the company’s most recent annual report on Form 10-K and reports on
Form 10-Q and Form 8-K. These documents are available from the SEC, the Bristol-Myers Squibb website or
from Bristol-Myers Squibb Investor Relations.
In addition, any forward-looking statements represent our estimates only as of the date hereof and should not
be relied upon as representing our estimates as of any subsequent date. While we may elect to update
forward-looking statements at some point in the future, we specifically disclaim any obligation to do so, even
if our estimates change.
This presentation also contains certain non-GAAP financial measures, adjusted to include certain costs,
expenses, gains and losses and other specified items. Reconciliations of these non-GAAP financial
measures to the most comparable GAAP measures are available on the company’s website at
www.bms.com.
6
Bristol-Myers Squibb is a
Global Diversified Specialty BioPharma Company
Europe
includes Russia
and Turkey
United
States
includes Puerto Rico
Rest of World
includes Japan, China
2014 Net Sales:
$15.9 Billion
Other
7
Focused on These Disease Areas
ImmunoOncology
Fibrotic
Diseases
Immunoscience
Oncology
Genetically Defined
Diseases
Cardiovascular
Small Molecules
Biologics
DRUG PLATFORMS
Millamolecules
Antibody Drug
Conjugates
8
Pharmaceutical Development Creates the
Manufacturing Process and Clinical Trial Drug Supply
CLINICAL SITES
PRECLINICAL STUDIES
PHASE 1
HUMAN STUDIES
PHASE 2,3
HUMAN STUDIES
MANUFACTURING
RESEARCH
Primary PD output is knowledge to
manufacture and evaluate the quality of our
drug supply
FILING & APPROVAL
HEALTH
AUTHORITIES
9
What Is the Opportunity for
Pharmaceutical Development (PD) ?
PD Knowledge Management Objectives
Increase PD productivity, speed, and agility
by improving data and knowledge capture and sharing
PD Knowledge Management Scope
• Knowledge is the understanding of relationships and
patterns based on data
• Explicit data and knowledge recorded electronically
• Entire life cycle of knowledge creation and consumption
10
PD Knowledge Management Challenges
Multiple Interacting Groups Create and Use Knowledge
CLINICAL
SITES
CHEMICAL PROCESS DEVELOPMENT
MANUFACTURING
ANALYTICAL and BIO-ANALYTICAL DEVELOPMENT
DRUG PRODUCT DEVELOPMENT
HEALTH
AUTHORITIES
11
PD Knowledge Management Challenges
Multiple Local Process and System Optimizations
RRS
Recipe Review System
Modeling & Simulation
Matlab, CAMO, Dynochem, EDEM, FLEUNT
PI
CLINICAL
SITES
Historian
Delta V
Pilot Plant Automation
RT Reports
eBR
Symyx eLN
Recipe Development
CHEMICAL PROCESS DEVELOPMENT
VQ SmartLab
Compliant Recipe Execution
Symyx LEA
NuGenesis
Lab Automation
Analytical Data Mgmt
ANALYTICAL and BIO-ANALYTICAL DEVELOPMENT
Discoverant
PAT
MANUFACTURING
Empower
Chromatography Data Mgmt
Process Analysis
LabWare
CA SmartSupplies
Analytical Request Mgmt
Supply Chain Forecasting
SAP
Process Analytic Mgmt
Supply Chain Recipe Execution
DRUG PRODUCT DEVELOPMENT
eBatch
Modeling & Simulation
Matlab, NTRL-SAC, FLEUNT, GPlus
QUMAS
HEALTH
Document Mgmt
AUTHORITIES
eBR
RIVRS
Supply Chain Order Mgmt
Rainman
Randomization
LTGA
Label Authoring
ClinPro
Label Printing
12
PD Knowledge Management Challenges
Business Process Varies for Every Drug Program
CLINICAL
SITES
CHEMICAL PROCESS DEVELOPMENT
MANUFACTURING
ANALYTICAL and BIO-ANALYTICAL DEVELOPMENT
DRUG PRODUCT DEVELOPMENT
HEALTH
AUTHORITIES
13
How Will PD Achieve Its
Knowledge Management Objectives?
Transform Knowledge Creation (TKC)
Strategic Initiative
Strategy
Step 1
• Define TKC vision,
objectives, and plan
• Identify and organize PD
Knowledge = KRM
Step 2
• Create processes and
tools to manage PD
knowledge = Knection
14
The PD Knowledge Road Map (KRM)
Organize PD Knowledge
Strategy
KRM
Knection
15
PD Knowledge Roadmap (KRM)
Strategy
KRM
Knection
16
Where Do We Go from Here?
Strategy
KRM
Knection
Look for Patterns:
Organize
Simplify
Repeatable
17
TKC
Strategy
KRM
Knection
Solve the Correct Knowledge Management Problem
Assess
Risk
Develop
Strategy
Define Problem
Statement
Develop and
publish report(s)
Find historical
information
Make Decisions
Define and
perform studies
Evaluate Results
18
TKC
Strategy
KRM
Knection
Solve the Correct Knowledge Management Problem
Pharmaceutical Development
Produces Knowledge
Assets (KA)
KA created in
a hierarchy
KA exist in a
network of
related KA
Small number
of KA classes
Each KA has a
creation Activity
All Activities
have a
recurring set
of tasks
The Activity
business
process is not
prescriptive
19
Knection
Implementation
Workspaces
Organize and Manage
data and knowledge
Functionality
Search
Collaborate
Log
Navigate
References
Knowledge
Asset Library
Workspaces
Activity
Experiment Group
Analysis
Author
Status
Automatic
Context
20
Knection
Implementation
Find
Find Everything with Context
21
Knection
Implementation
Lab Data Workflow
Data Workflow
Samples
Results
Requester
Analyst
22
Knection
Implementation
Functionality
Search
Collaborate
Workspaces
Activity
Log
Navigate
Experiment Group
Analysis
References
Knowledge
Asset Library
Find
Status
Find Everything
with Context
Automatic
Context
Author
Lab Data Workflow
Data Workflow
Workspaces
Organize and Manage
Data and Knowledge
23
Knection
Implementation
Pega
Functionality
Search
Collaborate
Workspaces
Activity
Log
Navigate
Experiment Group
Analysis
References
Knowledge
Asset Library
Find
Status
Find Everything
with Context
Automatic
Context
Author
Lab Data Workflow
Data Workflow
Workspaces
Organize and Manage
Data and Knowledge
24
LAB DATA WORKFLOW
Problem Statement
Current Sample Workflow Concerns to be Addressed
• Systems by-passed because they are too difficult to navigate (ex. PDLIMS)
• Poor system performance via integration points
• Non-fluid workstream (Many paths to obtain the same result!)
• Rework being performed because there is no record of the work being
performed previously
• No metrics being maintained (Who is assigned to what project and test)
• Poor communication on sample status (ex. In-Process, Under Investigation)
• No sample custody during all phases in the sample workflow
• High-Level Employees doing sample aliquoting and delivery
• Non-harmonized processes within PD (ex. Labeling)
26
What Is Laboratory Data Workflow (LDW)?
LDW is an intuitive, seamless, and robust software platform
developed to help manage the sample and information flow
throughout an experimental workstream
Sample Request
Sample Delivery
Assignment
Analysis / Results Posting
A Requester will
submit samples
via ELN, LDW,
Workspace or LIMS
in an automated
workflow approach
Couriers will
help split and
deliver samples
between labs
Scientists can
see their
assignments and
manage their
workloads
Results of experiments
can be easily found and
viewed in LDW
27
What Are the Key Benefits?
Benefits That PD Employees Will Receive from Lab Data Workflow:
Automation and Monitoring:
Enabling automated execution and monitoring that improves business process
for experimental workflow
Sample Custody Workflow and Sample Status Tracking:
Facilitating the development of a complete Sample Custody workflow eliminating high-level
employees doing low-value added work and allowing for Sample Status Tracking
Metrics Capture and Data Centralization:
Capturing metrics on all aspects of the experimental workflow and centralizes searchable data
Global Harmonization:
Harmonizing practices globally across PD including Sample Labeling, Sample Submission,
Assignment of Work, and Results Posting
28
Why Choose Pega as the BPMS?
• Industry Leader in BPMS
• Intuitive Interface
• Ease of transforming requirements to code – DCO
• Speedy Development
• Ease of Integration
• Some familiarity of BMS work practices from previous projects
29
Lab Data Workflow Demo – User POV
• What we will be demoing
– This
– That
30
Lab Data Workflow Demo – User POV
• What we just saw
– Major point #1
– Major point #2
–…
31
PEGA DATA
CAPABILITIES
Pega Live Data Overview Video
Pega Live Data allows business users to quickly and
easily define and use the data they need to build apps …
Website video
Local file
33
Pega Application Components
Case Management
Live Data
Logical Data Model
(Data Virtualization Layer)
Integration
Physical Data Model
(MDM, ERP, SOA, etc.)
34
Pega Application Components
Case Management Layer
Data Virtualization Layer
Data Process Orchestration
Data Source Integration Layer
Logical Data Model
Physical Data Stores (MDM, ERP, SFDC, etc.)
35
Live Data Creates a Virtualized Data Layer
Orchestration Layer
•
•
•
•
Data Processes, Workflows
Control & Visibility
Routing and Authorization
Context and History
Virtualized Data Layer
Live Data
•
•
•
•
Logical Data Model
Mapping to Physical Data Models
Conditional Data Source Selection
Intelligent Caching
Integration Layer
• Connection to Data Sources
• Authorization & Authentication
36
Live Data
Implementation &
Maintenance Costs
Reusable
Efficiencies, ROI,
& Trust
On-Demand
Data Access
Powerful
Tooling
Built for Change
Live Data
Caching &
Performance
37
Live Data
Source Aggregation
Use Case
Record Type = 360
Master Data Store
Customer Dashboard
Customer
Cloud Store
On-Demand
Data Access
38
Live Data
Source Selection
Use Case
Record Type = Master
Master Data Store
Customer Search
Customer
On-Demand
Data Access
Reusable
39
Live Data
Source Selection
Use Case
Record Type = Sales
Customer Sales Account Creation
Customer
Cloud Store
On-Demand
Data Access
Reusable
40
Live Data
Source Acquisition
Use Case
New Master
Record Type = 360
Master
Customer Dashboard
Customer
On-Demand
Data Access
Reusable
Built for Change
Cloud Store
41
IMPLEMENTATION
Lab Data Workflow Demo – Developer POV
• What we will be demoing
– Implementation of Lab Data Workflow
– How Pega supports data virtualization
– Using simulated data
– Considerations when using data virtualization
43
Lab Data Workflow Demo – Developer POV
• What we just saw
– Implementation of Lab Data Workflow
– How Pega supports data virtualization
– Using simulated data
– Considerations when using data virtualization
44
ADDITIONAL DATA
CAPABILITIES
Live Data
Powerful
Tooling
46
Live Data
Mapping Between Your Logical Data Layer and
Your Physical Data Sources
Logical data type
“Activity Journal “
mapped to physical
data source “Fitbit “
Powerful
Tooling
Drilldown to
see the data
pages used by
the data type
Simple visual
indicators
of simulated
and actual
data sources
47
Integration
48
Integration
REST API
49
Case Management
Live Data
Integration
49
Integration
50
Integration
51
Achieving the Vision with Pega
Tying It All Together
Live Data
Case Management
On-Demand
Data Access
Processes orchestration
Automatic routing
Automatic validation
Business decisions & rules
Intent-driven UI
Integration
Powerful
Tooling
Reusable
Built for Change
Caching &
Performance
Read & write data
REST / SOAP / SAP / SFDC
Direct DB access
Pega API
Pega Mashup
52
BUSINESS VALUE
Business Value for BMS
• Improve scientific insight
• Improve business process insight
• Engagement and Cooperation
– Integration within and across teams working on same project
– Easy to use processes and applications
– Collaboration embedded in tools
• Transparency
– Visibility into current state of scientific understanding
– Visibility into workflow execution
• Return on Assets
– Increase use of PD knowledge
– Easier to use existing PD systems and applications
• Improve Productivity
54
Knection Plan Going Forward
Quarter 1
Quarter 2
Knection Find Launch
Searches:
• Regulatory Documents
• Internal and team documents
• Initial Electronic Lab Notebooks
Quarter 3
Quarter 4
Knection 1A Release
• Knection Find
• Lab Data Workflow
• Dashboard
Knection 1B Release
•
•
•
•
Workspaces
Connectivity to KRM
Additional document sources
Additional Electronic Lab Notebooks
55
Q&A
twitter.com/pega
linkedin.com/company/pegasystems