The document discusses the challenges in drug discovery and development, emphasizing that despite technological advancements, the time from discovery to approval is increasing due to inefficiencies in systems and processes. It highlights the necessity for innovative technologies, flexible architectures, and improved data integration to streamline regulatory submissions and enhance collaboration among organizations. Additionally, it underscores the importance of cloud-based solutions to facilitate these transitions and improve operational efficiency within the life sciences industry.

1. December 14, 2017
Getting to Approval
Faster through
Technology Innovation

2. © 2017 DIA, Inc. All rights reserved.
Speakers Bio
Page 2
Paul Slater
Director, and Worldwide Industry
Strategist, Pharmaceuticals
Educational Background:
• BSc (Hons) in Mathematics, King’s College London
Career Overview:
• Defines Microsoft’s strategy in life sciences,
including regulatory compliance approach for the
organization
• Author of multiple position papers on hybrid, private
and public cloud, platform modernization and IT
Portfolio Management
• Defined cloud and virtualization strategies across
multiple corporations
• @paul-slater

3. © 2017 DIA, Inc. All rights reserved.
Speakers Bio
Page 3
Matt Neal
Senior Director, Product Management –
Regulatory & Clinical Solutions
Educational Background:
• MA Communications, Temple University
Career Overview:
• Defines PAREXEL product strategy in Regulatory for
Life Sciences
• 20+ years in Industry (Amgen & GSK) Regulatory &
Safety Operations and electronic submissions pioneer
• Lifelong learner with a focus on disruptive innovation
and exponential technologies
• Knowledge Management expert and author
• Regulatory & Safety Operations Key Opinion Leader
• Frequent Conference Speaker andAuthor
• @matthewjneal

4. © 2017 DIA, Inc. All rights reserved. Page 4
Meredith Sewell
Executive Director, Allergan
Global Regulatory Affairs Submissions
Educational Background:
• BA, English Literature, University of California, Irvine
Career Overview:
• Defines Allergan’s Global Ops Submission Strategy and Process
• Drive Allergan’s partnership with Parexel to implement a cloud-
based, vendor-hosted RIM and Publishing system
• Reg Ops M&A integration and assimilation expert
(20+ companies in 2 years)
• Change management champion and optimizer of systems,
resources and processes

5. Describe factors that lead to inefficiencies in the
drug discovery and development process
Describe new technologies that will remove
those inefficiencies
Describe simplified powerful architectures
designed to enhance specialized regulatory
systems
Recognize how organizations will be simplified
as tools merge and become more intuitive
© 2017 DIA, Inc. All rights reserved.
Learning Objectives
Page 5

6. Introductions
Roundtable Discussion
Questions and answers
© 2017 DIA, Inc. All rights reserved.
Agenda
Page 6

7. © 2017 DIA, Inc. All rights reserved.
Question 1
Page 7
Why is time from
discovery to approval
going up?

8. Drug discovery is becoming slower and
more expensive over time, despite
improvements in technology (such as high
throughput screening, biotechnology,
combinatorial chemistry, and computational
drug design)
© 2017 DIA, Inc. All rights reserved.
Eroom’s Law
Page 8

9. © 2017 DIA, Inc. All rights reserved.
Where we are today
Page 9

10. Two years ago, Allergan became the
conglomeration of 4 large companies: Allergan,
Actavis, Watson, & Warner-Chilcott
Each had an Investigator Payment system
implemented and people to support them
Narrowed down to iMedidata, and IMPACT
iMedidata was not a “global” system but used
widely – large amt of trials + large team to
support
IMPACT also needed to sustain global trials
Sunshine Act requirements need to be met
© 2017 DIA, Inc. All rights reserved.
Allergan Investigator Payments - CTMS
Page 10

11. Technology and money are part of the problem
• Technology, people and process are entwined for both
Medidata and IMPACT
• Expert users and number of trials
• Expensive to integrate into one system
• Contracts, data migration, new training
• More expensive to retain two systems
• IT resources
• People + Process differences
• No central/single source of information
• Reporting and metrics are difficult
• New technology could bridge the gaps and create effective
opportunities for staff
© 2017 DIA, Inc. All rights reserved.
Allergan Investigator Payments (Cont’d)
Page 11

12. 1999 – 2010s – Process of adding hyperlinks
was manual
Proper template use helped; rendered styles to
bookmarks, internal hyperlinks (cross-
references) retained
Touch up for bookmarks and hyperlinks were
produced with pdf plugin tools
Drawbacks: Time-consuming, people-driven,
last minute work
© 2017 DIA, Inc. All rights reserved.
Regulatory Submission Publishing – Evolution
of Bookmarking & Hyperlinking
Page 12

13. © 2017 DIA, Inc. All rights reserved.
Question 2
Page 13
Can we reverse the
trend?

14. © 2017 DIA, Inc. All rights reserved.
Where we are today
Page 14

15. © 2017 DIA, Inc. All rights reserved.
What is needed
Page 15
Applications
Data
Self-improving productsFlexible Architectures
As Is
To Be

16. © 2017 DIA, Inc. All rights reserved.
Question 3
Page 16
What do flexible
architectures look like?

17. © 2017 DIA, Inc. All rights reserved.
POLL
Page 17
Where are you in your cloud journey?
 Fully on-premise (no cloud)
 Dev/Test in the cloud
 At least one Prod environment in the cloud
 All environments in the cloud

18. © 2017 DIA, Inc. All rights reserved.
POLL
Page 18
What is your biggest concern in adopting cloud
computing?
 Maintaining Security
 Maintaining Data Integrity
 Loss of Control
 Disaster Recovery
 Regulatory Compliance

19. New view of Line of Business Architectures

20. Data Architecture for Life Sciences

21. Flexibility from Cloud Based Architectures
Old World New World
IT department has to plan upgrades

22. Flexibility from Cloud Based Architectures
Old World New World
IT department has to plan upgrades No more upgrades, new features roll
into product on an agreed schedule

23. Flexibility from Cloud Based Architectures
Old World New World
IT department has to plan upgrades No more upgrades, new features roll
into product on an agreed schedule
High maintenance costs to maintain
and integrate the platform

24. Flexibility from Cloud Based Architectures
Old World New World
IT department has to plan upgrades No more upgrades, new features roll
into product on an agreed schedule
High maintenance costs to maintain
and integrate the platform
Maintenance built into the architecture.
Simplified data integration through
common data architecture

25. Flexibility from Cloud Based Architectures
Old World New World
IT department has to plan upgrades No more upgrades, new features roll
into product on an agreed schedule
High maintenance costs to maintain
and integrate the platform
Maintenance built into the architecture.
Simplified data integration through
common data architecture
“Feature drop” to meet version
deadlines

26. Flexibility from Cloud Based Architectures
Old World New World
IT department has to plan upgrades No more upgrades, new features roll
into product on an agreed schedule
High maintenance costs to maintain
and integrate the platform
Maintenance built into the architecture.
Simplified data integration through
common data architecture
“Feature drop” to meet version
deadlines
Features developed according to
customer demand, and rolled into
product according to agreed schedule

27. Flexibility from Cloud Based Architectures
Old World New World
IT department has to plan upgrades No more upgrades, new features roll
into product on an agreed schedule
High maintenance costs to maintain
and integrate the platform
Maintenance built into the architecture.
Simplified data integration through
common data architecture
“Feature drop” to meet version
deadlines
Features developed according to
customer demand, and rolled into
product according to agreed schedule
No benefit to adding new products and
services

28. Flexibility from Cloud Based Architectures
Old World New World
IT department has to plan upgrades No more upgrades, new features roll
into product on an agreed schedule
High maintenance costs to maintain
and integrate the platform
Maintenance built into the architecture.
Simplified data integration through
common data architecture
“Feature drop” to meet version
deadlines
Features developed according to
customer demand, and rolled into
product according to agreed schedule
No benefit to adding new products and
services
Data insights enhanced as new
services are added

29. Vivli – Data Sharing Platform
29

30. CORE STRATEGY
DIGITAL TRANSFORMATION – SOLUTIONCONVERGENCE