(CPV) Program at Baxter BioScience

Implementing an Operations
Intelligence System to Automate a
Continued Process Verification
(CPV) Program at Baxter BioScience
Marco Arocha, Eng.
Manager Information Systems
Baxter Bioscience
Justin O. Neway, Ph.D.
Vice President and Senior Fellow
Accelrys ADQM
Presentation Outline
•
•
•
•
•
Essentials of CPV
Software technology requirements
The Discoverant solution
Baxter Bioscience case study
Summary & conclusion
Elements of Successful CPV
CPV originated with the GMPs (21CFR211.110):
• “Such control procedures shall be established to monitor the
output and to validate the performance of those manufacturing
processes that may be responsible for causing variability in the
characteristics of in-process material and the drug product.”
Recently highlighted in Stage 3 of the updated FDA Validation
Guidelines:
• “The goal of the third validation stage is continual assurance that
the process remains in a state of control (the validated state)
during commercial manufacture.”
Software Technology Requirements for CPV
• Provide a self-service, on-demand data access environment for all process
and quality data including paper records
• Provide a validated environment requiring no second person verification
• Require no changes to existing source data systems
• Provide access to all types of data, including continuous and discrete
• Provide automated data contextualization for automated process
monitoring updates with alerts for review-by-exception
• Provide the ability to follow-up with deviation investigations in the same
validated environment
Why is it So Difficult
to Meet These Requirements?
The Manufacturing Data Landscape
Raw Materials
Raw
Materials
ERP
Process
Process
Step 1
Process
Step
Step 1
1
Process
Process
Process
Step 3
Process
Process
Step 2
Process
Step
Step 2
2
LIMS
Step
Step 3
3
HIST
Paper Records
CAPA
Process
Process
Steps…
Process
Steps…
Steps…
MES
Final
Final
Product
Final
Product
Product
Eng
Maint
The Manufacturing Data Landscape
Raw Materials
Raw
Materials
Process
Process
Process
Step 1
Process
Process
Process
Step 3
Process
Process
Step 2
Process
Step
Step 2
2
Step
Step 1
1
Step
Step 3
3
Process
Process
Steps…
Process
Steps…
Steps…
Final
Final
Product
Final
Product
Product
PAT
PAT
PAT
PAT
ERP
LIMS
HIST
Paper Records
CAPA
MES
Eng
Maint
Manual Contextualization: The Biggest Time Sink
Contextualization is the organization of related data elements
that enables analysis and interpretation
Other examples of useful contexts for data analysis:
–
–
–
–
–
Data type context: enables specific types of data analyses
Batch context: enables batch-to-batch comparisons
Process context: enables process-to-process comparisons
Site context: enables site-to-site comparisons
Genealogy context: enables upstream / downstream correlations
The Discoverant Solution
Discoverant for Operations Intelligence
Quality
Monitor
3D-4D
Plotting
Plotting
Stability
& Exp
Dating
External
Applications
Stats
Multiphase
Analysis
External
Applications
Browser
Outputs to
Dashboards,
Portals, etc.
JMP, Umetrics, Mintab,
SIPAT, Word, Crystal,
Matlab
InVision
Authoring Environment
SharePoint,
Dashboards,
Word, Crystal
KnowledgeNet
Collaboration Environment
Nexus: Data Access, Aggregation & Contextulization
Direct Connects
Oracle, jdbc, OPC-HDA, Web Services
PRIMR: Paper Records
Paper Data Capture
MES/
EBR
ERP
LIMS
HIST
CAPA
Process Databases
ELN
LES
Other
The Process Data Landscape
Raw Materials
Raw
Materials
Process
Process
Step 1
Process
Step
Step 1
1
Process
Process
Process
Step 3
Process
Process
Step 2
Process
Step
Step 2
2
Step
Step 3
3
Process
Process
Steps…
Process
Steps…
Steps…
Final
Final
Product
Final
Product
Product
Nexus: Data Access, Aggregation & Contextualization
ERP
LIMS
HIST
Paper Records
CAPA
MES
Eng
Maint
Paper Record Data Capture
Data Sources
Mfg.
Paper Records
CMO
Process Dev.
Quality
Paper Record Data Capture
Data Sources
Mfg.
Paper Records
CMO
Process Dev.
Quality
Data Access and Contextualization: Bioprocess
Data Sources
RIF
LIMS
Mfg.
HIST
CMO
HIST
Dynamic
Mapping Engine
Process Dev.
AG
Analysis
Group
Quality
Data Access and Contextualization: Bioprocess
Data Sources
RIF
LIMS
Mfg.
HIST
CMO
ERP
HIST
Dynamic
Mapping Engine
Process Dev.
AG
CAPA
Analysis
Group
Quality
MES
SAP
EG
Data Access and Contextualization: Bioprocess
Data Sources
RIF
LIMS
Mfg.
HIST
CMO
ERP
HIST
Dynamic
Mapping Engine
Process Dev.
AG
CAPA
Analysis Group
Quality
MES
SAP
EG
Using Process Data Within Discoverant
Trending & Alerts,
Trouble-shooting,
Plotting,
Univariate &
Multivariate
Statistics,
Fermentation &
Synthesis,
Chromatography &
Multi-phase,
Stability &
Expiration Dating.
AG
Analysis
Group
Dynamic
Mapping Engine
Case Study: Implementing an Automated Continuous
Process Verification (CPV) Program at Baxter BioScience
BioAnalytics Program lead by Global Information Technology
World Trade Group (WTG) Biomanufacturing Summit 2014
January 29-31, 2014 │San Diego California
Marco Arocha,
Manager Information Systems
Global Information Technology
Baxter Healthcare Corporation / BioScience
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Business Overview
Healthcare
Corp
Baxter
BioScience
Baxter
Medical Products
• Baxter's BioScience business continues a 60-year legacy of
providing life-saving and life-sustaining specialty therapies. The
products and therapies Baxter's BioScience organization produces
are varied, but they share the common connection of improving the
lives of patients with rare conditions, chronic diseases or limited
treatment options.
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Automated CPV Program
The program for automating CPV consist of integrating Operations Intelligence
and guided input from Manufacturing Operations and Quality. Our program is
know as BioAnalytics in Baxter BioScience Division.
Our vision:
Enable our customers to produce high quality products for the
patients and establishing efficient manufacturing processes
To create an automated analytical capability based on a unified view
of products and critical parameters harmonized across sites to
improve process knowledge and control
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Operations Intelligence Vision
Operations Intelligence (OI) is the process of bringing together operations
data from many sources to generate process knowledge that will drive
improved results…
Operations Intelligence consists of several elements:
• Automated transfer of data from the shop floor.
• Aggregation of data from multiple sources.
• Providing context and structure to the data.
• Providing capabilities for standard and ad hoc analysis and reporting.
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Guiding Principles
FDA Guidance on Process Validation
Process Validation is defined as the collection and evaluation of data, from the process
design stage throughout production, which establishes scientific evidence that a process
is capable of consistently delivering quality products. Process validation involves a
series of activities taking place over the lifecycle of the product and process. This
guidance describes the process validation activities in three stages:
•
Stage 1 – Process Design: The commercial process is defined during this stage based on
knowledge gained through development and scale-up activities.
•
Stage 2 – Process Qualification: During this stage, the process design is confirmed as being
capable of reproducible commercial manufacturing.
•
Stage 3 – Continued Process Verification: Ongoing assurance is gained during routine
production that the process remains in a state of control.
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Where do we want to get
Real Time Design Space Control
Control multiple process parameters
to maintain process at optimum
in real time
PAT
Real Time Online Monitoring
Implement PAT, Electronic Batch Management, Historian
Software for retrieving real time data from underlying
Process Control Systems and connect to BioAnalytics for
real time monitoring and active process adjustment
(manually or automated)
Monitoring of Process Steps
Aggregates process parameters of complete process
steps after run to simplify control and monitoring
and to support internal release
Process
Monitoring
Process
Validation
Problem
Resolution
Monitoring of Single Outputs
Standardize Process Monitoring and Control for selected
process parameters offline
Access to Data
Automated access to process data
based on a unified view of products
and critical parameters harmonized
across sites
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Process
Control
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Software Support Systems Requirements
Implement a global system that provides:
• Access to all manufacturing data, including but not limited to process control
systems, in-line device recordings, laboratory results, manufacturing execution
data and other batch record data.
• Analysis and reporting which includes: the creation of Control Charts, Product
and Stability trending, and other Statistical Analysis based upon selected data.
• The ability to compare results across all plants and at the overall divisional
level.
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Expected Business Benefits of BioAnalytics Program
 Improved Access
Access to data now is generally through a few SMEs that know where and what the data is, and how it relates to the
process. BioAnalytics will formalize this knowledge so that more people will have access to the data. BioAnalytics will
provide common data dictionary for reference and guiding access to the data.
 Improved Control
Data is frequently extracted into uncontrolled spreadsheets or other applications. When validation is required (e.g.
PAR), the effort is quite high to track back to the original data and source. The number of different sources also
contribute to inconsistency in the data. BioAnalytics would result in the reduction of the number of data sources and
formalize control processes (where required).
 Integrated Data
Data must be integrated with its context (i.e. Lot number, date, process step, etc.) in order to be understood. Most
frequently this is provided from the knowledge of the SME. BioAnalytics will formalize this knowledge. Additionally,
there is a desire to relate the information from different sites and systems (e.g. Lab Records Management Systems,
Material Management Software). BioAnalytics will optimize this integration in one location.
 Data Re-use
Data is frequently extracted for a single use. Each time the data is needed (by different people) it is extracted again.
Calculations / derivations are made repeatedly. BioAnalytics will store the data and key calculations / derivations for reuse.
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Expected Business Benefits of BioAnalytics Program
 Implement a global management approach across multiple sites.
 Improve process understanding and controlling process variability
 Limit the potential yield losses while aiding in the identification of yield improvement opportunities
through process comparison within a site and/or different manufacturing sites.
 Better understanding of the correlation between the process parameter and the quality indicating
outputs especially the Critical Process Parameters (CPP) and Critical Quality Attributes (CQA).
 Allow trending of parameters to take action before the specific factor becomes a problem, thereby
avoiding product discards.
 Switch from a data collection and reconciliation mode to an analyzing and decision mode within Baxter
 Enabling future Real Time process monitoring and control (Future)
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Roadmap and Scoping of Monitoring and Control
An incremental approach for each product / site will meet short-term
challenges while working toward long-term goals…
• PPs – Less Important
• Priority-driven
Full Monitoring
Cost & Complexity
+
• PPs – Important
• Full Hierarchy
Extended Monitoring
(Automated)
+
• CQAs, CPPs – License Parameters
• Partial Hierarchy
• Interface to data sources for applicable
parameters + Batch Record Data capture
• Multi-site harmonization
Monitoring
(Automated)
+
• CPPs – License Parameters
• No interface to data sources
• Minimal multi-site harmonization
Monitoring
(Manual)
Time for Implementation
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BioAnalytics; Our Tools Portfolio
Our program is
responsible of
implementing the global
harmonization of these
tools
Process Monitoring: Operational
Intelligence Software
Data
Capture:
Real Time
Data
Historian
Software
Dash
boarding:
Collaborati
on Portal
Software
Advanced Analysis:
MVDA, Modeling and
DOE software
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Integrate Operations and Define Technology Enablers
Stage 1
Process Design
Process
Validation
Guidance
Quality
By
Design
Stage 2
Process Qualification
• Building and Capturing Process
Knowledge and Understanding
• Design of a Facility and Qualification of
Utilities and Equipment
• Establishing a Strategy for Process
Control
• Performance Qualification
• Prospective definition of CQAs & CPPs
through Pre-Clinical and Clinical studies.
• Definition of qualification based on
CQAs and CPPs
• Retrospective definition of CQAs and
CPPs though analysis of production
data.
• Definition of continued verification
strategy based on CQAs and CPPs.
Stage 3
Continued Process Verification
• Ongoing program to collect and analyze
product and process data that relate to
product quality
• Statistical process control
• Implementation of continued verification
strategy by collecting and analyzing data
of CQAs and CPPs.
Enabling Technologies
• Operations Intelligence Software
Global IT
Supporting
Technology
• Operations Intelligence Software
• Store in “electronic batch records”
collected data from Process Qualification
and provide analytical tools.
• Store in “electronic batch records”
collected data from Production and
provide analytical tools.
• Provide data from Process Qualification
and Production for comparison.
• Provide data from Product Development
and Production for comparison.
• Provide data from Product Development
and Process Qualification for
comparison.
• Data Historian Software
• Capture Data from process.
• Electronic Batch Management
Software
• Manage and record actions of
operators (EBR).
• Enforce control strategy.
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• Operations Intelligence Software
• Store in electronic batch records
collected data from Product Development
Runs and provide analytical tools.
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• Advance Analysis Software
• Advanced Multivariate Analysis and DOE
• Collaboration Portals Software
• Data Dash boarding and Visualization
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Organizational Requirements
Define the requirements
“What”, also Roles and
Responsibilities
Quality
Operations
Provide the Operating
Systems and Global
Logistics for
Implementation
Continuous
Process
Verification
Global
Information
Technology
Manufacturing
Operations
Owns the Process and
provide resources for
Implementation
Define the procedural
“How to” Application of
Stat Rules
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Technical
Services and
Process
Experts
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Integration of departments on local sites
Local Quality, Tech Services
Analysis
Local Statistical
Black Belt
Hierarchy
• Product
• Process Step 1
• Parameter 1
• Parameter 2
• Parameter 3
• Process Step 2
• Parameter 1
• Parameter 2
• Parameter 3
Local
EPC
(OE)
Local
SME
Data Sources and Process Context Mapping
Local IT
Local IT
pH value
Conductivity
Sample test results
Lot Genealogy
Quantities
Lot Profile info
LIMS
Local Quality
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Analytical Tools
Hold Duration
Calculations
Quantities
enterprise
resource
planning
software
Others not in
other systems
Pressure
Temperature
pH Values
Electronic
Batch
Management
Data
Historian
Local
SME
Parameters
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PCS
Local
electronic
batch
records
Batch
Records
Manufacturing
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Readiness Criteria: Change Management
• Objectives:
– To prepare the sites for the BioAnalytics Implementation, by assessing the
current readiness and define actions to sustain and utilize the systems
and processes that accompany this implementation.
• Introduction:
– All improvements to how we operate as a business require change, and all
change causes a predictable resistance by those people who are affected
by the change. Unfortunately, this tendency – the lack of acceptance of the
change – often causes a project to fail, even if the desired change is
perfectly logical and necessary.(1)
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Change Management Roadmap recommendation
Change Model to Make Change work .(1)
Current State
Leading Change
Creating a Shared Need
Shaping a Vision
Mobilizing Commitment
Transition State
Improved State
Monitoring Progress
Finishing the Job
Anchoring the Change
(1) Making Change Work, By Brien Palmer.
ASQ Quality Press
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Key Roles and Responsibilities for Project Implementation
Implementation
Sponsor
Product SME
Understands the business value of the Most critical role that is responsible
project, involved in setting the strategy
and accountable for building the
for the project.
hierarchy,
Local Project
Coordinator/Project
Manager
Helps on follow ups on local activities
during all phases,
Networks within the organization
leadership for open communication and
helps the champion to remove
obstacles.
Needs to liaison with other plants for
consistency,
will liaison with the global project
management team on a regular basis,
It is accountable for the ultimate
delivery of the project as schedule and
has the veto power.
Defines the parameters and its
expected results, will test the solution
during UAT,
coordinates local meetings, tests
cycles and document creation
Responsible for writing SOPs and also
responsible for conducting PQ
validation
Roles Depending on the
Phase of the Project
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Readiness Criteria for the Sites
Logistics and Project Planning:
• Site stakeholders:
– Educated on BioAnalytics Implementation cost & complexity vs. time
– Have viewed BioAnalytics Awareness presentation
– Site sponsor is identified and has buy-in, product SME’s are identified.
• Product Manufacturing Process Control Plan (MPCP) must exist
– MPCP must be provided to BioAnalytics Team from the QbD team
– Defines the Initial Scope of the implementation parameters
– Product-level analytical goals must be established (Global QbD, Global Tech Services)
• Funding is in place (CPA, or OPEX)
• Tech considerations are addressed (e.g. application/server licenses are
obtained, scaling considerations - Global IT assessment)
• Data sources/processes are validated and ready
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Readiness Criteria for the Sites
• The implementation of BioAnalytics
relies on the availability of the
validated underlying systems that
contain the data, as an example;
– Online Data / Historian
– Enterprise & resource planning
software
– Process Control Systems
– Electronic Batch Management
(EBM) Batch Release Workflow
– In Process and Final Product
Quality Record Management
Software
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Readiness Criteria for the Sites
Additional Items that dictate the pace
and scope of the implementation;
• Process Failure Mode and Effect
Analysis (PFMEA), – Risk
Assessment and Control Table
(RACT) – Manufacturing Process
Control Plan (MPCP)
– Approval of these documents for
the selected product
• Global Alignment Workshop of the
product to be implemented
– All plants, Parameter names, UOM,
etc..
• Detail workshop (product/process) at
the sites
– Define Data sources,
understanding manufacturing
operating mechanism, etc…
Together we can make things work
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BioAnalytics Work Environment
System
Knowledge
Management
(PKM)
Continuous
Improvement
(EPC)
Validation
Implementation
(QbD)
Support
Strong Communication
EPC= Enhanced Process Control Program
PKM = Process Knowledge Management
Program
Minor Communication
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Key Roles and Responsibilities Post Implementation
Operation & Continuous Improvement
BioAnalytics Champion
(Local System Owner)
Understands the business value and
Is the responsible of the deployment
of BioAnalytics within the product or
facility, also has Veto Power.
Is responsible for maintaining the
gains achieved by process monitoring
and the implementation of BioAnalytics.
EPC Champion
Works with the site teams Technical
Services, Quality, Operational
Excellence, Manufacturing, and
understands their needs and
objectives and helps to prioritize the
work for process monitoring efforts on the
site.
Define the needs from the sites for
Manufacturing Process Control
Local System
Administrator (IT)
Needs to follow the global IT team
through all phases and is knowledge
carrier of the system within the plant,
Will be responsible for Local electronic
batch records pages in future
Removes Barriers for the Local Teams in
the continued support and deployment of
Process Monitoring efforts and BioAnalytics
use at the site.
Links the local IT, engineering, TS,
Quality and Manufacturing needs and
options to improve manufacturing
process knowledge and control towards
higher supply reliability.
Will be responsible for capturing and
submitting request from the site to the
global team through the SharePoint
System
prioritize changes to the system from
local perspective
Member of the Divisional EPC team to
provide feedback from the site and to
distribute information from other sites
back to the site
Will be the IT owner of the system and
understands and coordinates the
local efforts to maintain the system
running
support local BB on prioritizing and
defining local needs
Support the teams on selecting the
correct statistical tools for process and
product monitoring
being the single point of contact for the
global IT Team
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Program Support: Integration between local and global teams
Due to increasing demand increase local organization resources to ensure
continuity of BioAnalytics after implementation
Local Site (Plant
Management)
• Increase local flexibility by having a local
IT rep and local Black Belt
• Empower local IT rep by letting him
support local change management
activities and allowing him to develop
changes or fixing bugs
• Enable local organization to estimates
efforts independent from global team
Division
Global
IT
Local
EPC
Global
EPC
Local
Technical
Services
Global
Technical
Services –
MPO/QPO
• Controlling changes by global approval and global
policies (especially for additional parameters)
• Establish global peer reviews of code
• Balance out resources between sites, external
vendors and internal developers
• Steer changes through operational Steering
Committee on a quarterly basis
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Continuous Improvement
To further capture
requests and sustain the
CPV Automated system
an online form was
created
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Accomplishments
• Recent Implementations of BioAnalytics
– Successfully Implemented the BioAnalytics Program on three products
• Eight Sites world wide have begin to benefit from the implementation
• Three Sites world wide for product manufacturing
• Thousands of Parameters are mapped for either product development,
process monitoring or investigational purposes.
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Realized Business Benefits Overview
Additional to the fulfillment of regulatory
requirements it is expected by experts that
following efficiency gains and opportunities
are enabled by the Implementation of
BioAnalytics.
Opportunities due
to BioAnalytics
Time
Projects
TPS, CAPA
Yield
Process Monitoring
Data
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Opportunities to
reveal unknown/
new CPPs
Routine
Early trend
detection –
avoidance of OOS
Non Conformance
Reports
~80% of time
saved
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Lessons Learned Summary and Action Plans
• Ensure Sponsors are more engaged & Identification of process champion to
drive project.
– AP; Early on the project ensure the team is well defined and utilize the Change
management tools and assessment to make any necessary corrections and support
the implementation
• Limit the number of parameters and scope
– AP; The initial scope of the site implementations must be targeting 150 parameters,
(+/- 10%)
• Realistic time commitments from SME’s, focus resources on the project and not
be distracted by multiple competing priorities.
– AP; Using the Change management assessments determine if project is ready to
continue or more time should be allowed to begin its implementation.
• Use resources that can make a difference and are willing to work
– AP; Target the key beneficiaries of the use of the product, rally the team and follow up
with consistent messages to ensure a vision and common goal is always present.
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Bibliography and references
• (1) Making Change Work, By Brien Palmer. ASQ Quality Press
• FDA Guidance for Industry , Process Validation: General Principles and
Practices , January 2011, Current Good Manufacturing Practices (CGMP) ,
Revision 1
• ASTM E2537-08: Standard, Guide for the Application of Continuous Quality
Verification to Pharmaceutical and, Biopharmaceutical Manufacturing;
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