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Five Critical Aspects for Successful RIM Adoption
29 October 2019
Webinar:
PAUL ATTRIDGESr. Director, Vault RIM
Veeva Systems
NIELS BUCH LEANDERPh.D., Global Head of
Regulatory Affairs
ANNE POUZETSenior Advisor
33Copyright © Veeva Systems 2019
AGENDA
Five critical aspects for successful RIM adoption1. Building a Business Case
2. Managing Data
3. Governance
4. Organizational Change
5. Continuous improvement
4Copyright © Veeva Systems 2019
Leading Provider Cloud Solutions to the Global Life Sciences Industry
Founded in 2007 2,800+ Employees HQ in Pleasanton, CA
5Copyright © Veeva Systems 2019
Global IT power house supporting the Life Sciences Industry
- and a key Veeva implementation partnerFounded in 1994 3,300+ Employees HQ Copenhagen, Denmark
6Copyright © Veeva Systems 2019
Building a Business case
Data Quality & Data Management
Governance & Data exchange
Organizational changes
Continuous business improvement
Building a Business Case
Poll #1
Building Business Case
10Copyright © Veeva Systems 2019
Building Business Case
RA Business Case
STAKEHOLDERSIdentify roles and responsibilities for
both project and operation
PROJECT BRIEFDetailed description
and timelines
RISKSIdentify problems
and set risk measures
BENEFITSWhat are the
advantages and what benefits will
they bring?
COSTSWhat are the
expected costs on project elements
and later operation?
SCOPE & ASSUMPTIONS
Identify scope and list assumptions
for the project
11Copyright © Veeva Systems 2019
NNIT RIM scope definitions and benefits
Building Business CaseBusiness Case: Example
NNIT business case template
RA Capabilities
Program and Project approach
Benefits
Transformation Strategy
12Copyright © Veeva Systems 2019
RA Transformation Strategy and Business case
Year 0 Year 2 Year 3 Year 4 Year 5
Year 5
Year 4
Year 3
Year 2
Year 1
FO
5:
Aff
ilia
te S
etu
p
FO
4:
Syste
m
In
teg
rati
on
FO
3:
Au
tom
ati
on
FO2: Regulations Readiness
FO1: Information Model
Year 1
Evaluate current RA capabilities and as-is maturity assessment
Identify future capabilities to support business strategy, reg. requirements and tech trends
Workshops with RA: maturity, success factors and business impact of key capabilities
Consolidation of capability heat maps across RA and set digital KPIs
Proposal on strategic projects and roadmap across RA. Adjustment of organization.
0
1
2
3
4
5
1 2 3 4 5
13Copyright © Veeva Systems 2019
Building Business CaseNNIT RA Strategy and Benchmarking
RA Maturity Assessment
3.3
4.74.4
4.1
0
1
2
3
4
5
Systems Processes People Total
Business Impact Economics Resources Quality
Functional Capability Scor
e
Stra
tegi
c Va
lue
Busi
ness
Val
ue
Flex
ibili
ty N
eed
Redu
ced
Com
plex
ity
Cost
Eff
ectiv
enes
s
Reso
urce
O
ptim
izat
ion
Redu
ced
Trai
ning
N
eed
Incr
ease
d Pr
oduc
t Q
ualit
y
Incr
ease
d Pr
oces
sed
Qua
lity
Ease
s Leg
al o
r Reg
. Co
nstr
aint
s
Remarks
XYZ 48 5 4 5 3 2 2 4 4 4 3 Long-term target
XYZ 55 5 5 2 1 5 5 5 5 2 5 Legal & regulatory requirements
XYZ 38 3 4 1 4 3 2 4 4 3 3
XYZ 22 2 3 4 2 1 1 1 1 1 3
XYZ 40 5 5 2 3 2 3 1 1 5 5 Complex set-up
XYZ 30 2 5 4 2 5 3 1 1 1 1 Interfaces with HR, Cross-functional
XYZ 22 3 3 2 1 5 2 1 1 2 2 Interfaces with finances
XYZ 39 5 5 3 4 5 1 1 1 3 3 Interfaces with production
Color Agenda:
Positive Weighing Factor x 2
Negative Weighing Factor x 2
Number Agenda:
1
5
= Lowest;
= Highest
RA RoadmapYear 0 Year 2 Year 3 Year 4 Year 5
Year 5
Year 4
Year 3
Year 2
Year 1
FO5:
Col
labo
ratio
nA
ffilia
te S
etup
FO
4: D
ata
and
Inte
grat
ion
FO3:
A
utom
atio
n
FO2: Regulations and Intelligence
FO1:Organization
Year 1
Managing Data & Data Quality
Poll #2
Building Business Case
18Copyright © Veeva Systems 2019
Why focus on data quality?Data Quality &
Data Management
Challenge; consolidation of silosWhen moving from legacy systems to new solutions, issues and concerns regarding data quality and readiness may occur. New data models have new requirements to structure and consistency, challenging the move from legacy systems
Reason 1: Secure Data Readiness and Compliance
Challenge; data trustThe ability to trust data and the information it provides is crucial. We often blame reports and people, when in fact changes to systems and processes over time is at fault. Information is key and the information is no better than the data foundation
Reason 2: Reporting correctness and internal KPIs
VS
19Copyright © Veeva Systems 2019
Establish Data model and ownershipData Quality &
Data Management
• Based on solution data model, define a holistic RA data model
Data Model
• Establish levels of data ownership with defined responsibilities:
Data Ownership
Data Migration Preparation Data Maintenance
AI-managed data quality
• Strategic level responsible • Tactical level
responsible • Operational
Business OwnerData Owner
Data Steward
Data Quality
PROCESSES
DATA MODEL
SYSTEMS DATA
20Copyright © Veeva Systems 2019
NNIT’s Data quality frameworkData Quality &
Data Management
Preparation Quality Analysis Execution Remediation
• Source Data for Analysis• Target Data Model• Mapping Specification
• Extract Data from Source Systems
• Scope Target Data Model• Map Source Data to Target
Model
• Data Quality Rule Book• Automated Data Quality
Flows• Data Quality Results
and report• Gap plan
• Define Quality Rules• Configure Data
Quality Flows• Execute Data Quality Flows• Analyze Results
and Adjust• Report with
recommendations
• Plan for execution• Data corrections• Data validation• Setting up automatic checks
• Data governance execution• Data stewardship
assignment• Change management and
SOPs
Governance & Data Exchange
Poll #3
Building Business Case
25Copyright © Veeva Systems 2019
Governance areasGovernance & Data exchange
Implementation
Risk
Define roles & responsibilities
Progress overview
Timelines
Define data quality rules
Continuous Business Improvement
Secure compliance
Move change requests to implementation
Assess changes to system impact to business processes
Assess changes to business processes impact to system
Advise on implementation of changes
Operation
System admin and support
Perform data quality measures
Maintain security
System is available at all times
26Copyright © Veeva Systems 2019
Impact on the submission processGovernance & Data exchange
Phase 1 Phase 2 Phase 3 Assessment Post-Approval Ph. 4
Investigational Products Authorised Products
Substance (API and Excipients)
CTA/IND xEVMiPD DSURINN
request eAF MAA/NDA eCTD xEVMPD PSUR and
variationsSPL
Device registration
Research NC, Clinical and CMC Safety Safety
FMD
ManufacturingRegulatory Affairs
Labelling development
Finalise Filing plan
Labelling development(Target product profile)
Clinical trial application
Scientific Advice
Clinical trial application
Submission planning
Pre-Submission meetings
Response To questions
Authoritymeetings Approval
Pricing &Reimbursement
Approve Promotionalactivities
Lifecyclemanagement
MAA submission Final label
Clinical trial application
27Copyright © Veeva Systems 2019
Exchange of dataData Quality &
Data Management
Challenge:Receiving manufacturer information from production systems
Failed alignment with CTD requirements, and issues on scope limitation
Strict governance will allow for mapping of data i.e. using IDs delivering oversight/ one truth and trust in data
Case 1: Data import
Challenge: Submitting data for XEVMPD requires adherence to EMA specific requirements
Data harmonization can happen in RIM or outside of the system. Submitted data should be captured to secure oversight and ability to correct data if requested by the agency
Proper governance will secure the right level of control and ability to map back to data in RIM if needed
Case 2: Data export
Organizational changes
30Copyright © Veeva Systems 2019
Changing the daily work in RAOrganizational
Changes
01Collaboration between affiliates and HQ, working on content plans
02Increased end-to-end understanding of process and data
03Working only in the system
31Copyright © Veeva Systems 2019
Changing the support modelOrganizational
Changes
BUSINESS
End usersService desk /
Screening
APPLICATION SUPPORT
Application
Product & BackendSIN
GLE
PO
INT
OF
CON
TACT
Technical & Functional
32Copyright © Veeva Systems 2019
Changing the IT and business collaborationOrganizational
Changes
BACKLOG ASSESSMENT- What is the business need?- What are the benefits?- What is the effort?- How fast to implement?- Impact?
Veeva General Release features
Business & Regulatory
Requirements
General releases (3 annual releases, auto-on)
Customer Releases
BACKLOG
Change Advisory Board / Product Owner
DEFER
IMPLE-
MENT
DO NOT
IMPL
E-M
ENT
PROTO
TYPE
PRIORITY
EFFO
RT
THEME
USER
STORY
Continuous business improvement
35Copyright © Veeva Systems 2019
Essential Ingredients To Success Continuous business
improvement
Application Services
Continuous Improvement
Customer Business Life-Cycle
Mgmt.
ApplicationSupport
Org. changes
Regulatorychanges
New markets Change in application landscape
New best practices
Example: EU Medical device regulation
36Copyright © Veeva Systems 2019
Maximizing the investment
Customer Release”Configurable” features
General Release”Auto-on” features
Stay validated Maximize business value
1 2
Continuous business improvement
37Copyright © Veeva Systems 2019
Doing a Customer Release Example plan and role distribution
Customer
Production - Change freeze
WK-6 WK-5 WK-4 WK-3 WK-2 WK-1
V P
SPRINT 1
WK 0
Prepare Change Document
Re-assess features and scope Estimation Configuration and Implementation Testing & Validation
QA Approval
Develop test protocols Test Integrations Update System documentation
Update and approve Validation report
Release announcement to system users
Final End user announcement
User Training
Releasego-live
Clone PROD to DEV and VAL
Transfer Configuration from DEV to VAL
Transfer Conf. from VAL to PROD
Config TransferConfig Transfer
Conf
ig T
rans
fer
Hypercare
Veeva Customer Success and Managed Services Support
Backlog Management
Continuous business improvement
Call-to-action• A business case is to guide you
through from initiation to operation• A business case should address
business benefits, not just IT benefits• A business case should be aligned
with a RA strategy • Prepare for organizational change• IT and business to work closely
together• Data quality needs a constant focus and a plan
• Data quality cannot be solved without governance/data ownership
• Know your data model• Operation not just to focus on
keeping the system validated & operational, but on continuous improvement (DevOps)
• NNIT and Veeva collaborate on support
• Increase in data exchange with externals
• Increase in data exchange with other business units within the company
Questions
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