The document discusses MilliporeSigma's Bio4C ProcessPad software for data management and advanced analytics in bioprocessing. It provides an overview of current challenges in bioprocess data management, describes how ProcessPad addresses these challenges through data aggregation and analysis tools, and provides examples of using ProcessPad for statistical process control and multivariate analysis.

1. The life science business of Merck KGaA,
Darmstadt, Germany operates
as MilliporeSigma in the U.S. and Canada.
Smart Data Management
and Advanced Analytics
with Bio4C™ ProcessPad
Hemant Garg
Product Manager, Analytics

2. The life science business
of Merck KGaA, Darmstadt,
Germany operates as
MilliporeSigma in the U.S.
and Canada

3. Agenda
1
2 Bioprocessing Data Landscape – Current Challenges and
Needs
Data Management Approaches and Solutions –
Introducing Bio4CTM ProcessPad
Next Gen Bioprocessing and the BioContinuum™ Platform
3
4 Statistical Process Control – Case Studies with
Bio4C™ ProcessPad
5 Advanced Analytics with Bio4C™ ProcessPad 4.1

4. Next Gen Bioprocessing and the
BioContinuum™ Platform

5. How do we react to meet the demands of
today and the future?
* Source: BioPhorum (BPOG)
https://www.biophorum.com/category /resources/technology -roadmapping-resources/introduction/
Defining
Capabilities
Maturity
level
✓ Paper-Based
✓ Manual processes
✓ Isolated Unit
operations
Pre-Digital Plant
✓ Islands of
automation
✓ Process Monitoring
✓ Offline analytics
Digital Silos
✓ Vertically integrated
systems
✓ Automated data
analytics
✓ Processing Modelling
& Simulation
Connected
Plant/
Predictive Plant
✓ Prescriptive analytics
✓ “Plug and Play”
Automation
✓ In-line process
control
Fully Digital
Adaptive
Business Drivers
Market Trends
Speed
Reduce new facility build times
by 70%. Compress production
lead time by 80%.
Quality
10X robustness.
90% reduction in
cost of poor
quality.
Flexibility
Reduce product
change-over time by
90%.
Cost
90% reduction in cost
to manufacture and
CAPEX.
Market
Growth
Uncertainty
New Product
Classes
Cost
Pressure
BioContinuum™
Platform Scope
Process Analytical
Technologies
Digital Technologies
& Data Management
Process
Technologies

6. Bio4C™ Software Suite
Specifically conceived by industry experts for bioprocess
professionals, the Bio4C™ Software Suite is comprised of
stand-alone, but seamlessly compatible software products.
Their intuitive interfaces and easy access enable a broad
user base to collaborate with global teams across
geographies and organizational silos to control, monitor
and analyse equipment, processes, results, and data in
near real-time.
Based on our core 4C’s: Control, Connect, Collect,
Collaborate, the Bio4C™ Suite offers a convergent, open
digital environment, adaptable to your changing
productivity, process, and regulatory needs.
The Bio4C™ Suite allows for data transparency
and manufacturing intelligence leading to quick
and efficient data-driven decisions for mastery at
the process and plant level.

7. Addressing customers’ digital transformation needs
Bio4C™ Software Suite

8. Bioprocessing Data Landscape:
Current Challenges and Needs

9. Data captured by disparate systems
Bioprocess Data Landscape
Data Stores
MES
LES
eLN
eBR
Custom DB
Data
Warehouse
Data
Historians
QualityControland
Assurance
QA Batch Fitness For Release
Change Control
Management
Process Test Samples
QC Methods
Results
People FitnessTraining
Management
Corrective Action
Management
Corrective Action
Management
Engineering
Equipment Fitness
Maintenance Record
Work Order
LMS – Learning Management System, LIMS – Laboratory Information Management System, QMS –Quality Management
System, BMS - Building Management System, MES – Manufacturing Execution System, LES – Laboratory Execution system,
Asset Mgmt. – Asset Management
Process
Development
Process Fitness
Development Reports
Process Development Experiments
Process
Execution
Process Excursions
and events
Manufacturing
FacilityManagement
Non-conformance
Management
Environment Fitness
Process Data Batch Report
InvestigationReport
eLN
Asset
Mgmt. BMS
eBR
QMS
LMS
LIMS

10. Data Needs for Investigations and Monitoring
• Integration of data collected from
various work processes
• Paper-based, manual systems
• Other electronic systems
• Process execution workflows
• Process development
• Quality Control and Assurance
• Commercial manufacturing
• Engineering
Engineering
Manufacturing
Investigation
Report
Process Fitness
Experimental Data
Process
Development
Change Control
Management
Test Results
People FitnessTraining
Management
QualityControland
Assurance
FacilityManagement
Process Data Batch Report
Investigation
Report
Equipment Fitness
Work Order

11. Regulatory Expectations for Bioprocess Monitoring and Control
https://www.fda.gov/regulatory-information/search-fda-guidance-documents/process-validation-general-principles-and-practices
https://www.ich.org/page/quality-guidelines
Pharmaceutical companies should plan and execute a system for the
monitoring of process performance and product quality to ensure
a state of control is maintained
-ICH Q10
An ongoing program to collect and analyze product and process data
that relate to product quality must be established. The data collected should
include relevant process trends and quality of incoming materials or
components, in-process material, and finished products.
-FDA Process Validation Guidance, Jan 2011

12. Data Management Approaches
and Solutions: Introducing
Bio4C™ ProcessPad

13. Bio4C™ ProcessPad Software
A browser-based platform for data acquisition,aggregation,
and process analytics. Built by bioprocess engineers to
manage and analyze your disjointedand complex process
information for a deeper understandingof your biopharma
processes across the process and product lifecycle in near
real-time.
Master your bioprocess
through profound data
insights

14. Through data aggregation, management, visualizations, and analysis,
Bio4C™ ProcessPad makes all critical bioprocess data readily available.
Easy on-demand access to biopharma manufacturing data
Browser-based Platform

15. Toolset for Efficient Process Troubleshooting

16. Bio4CTM ProcessPad Software Modules
Trending, Reporting, and Analytics of Machine Data
• Bioreactors
• Chromatography Systems
• CIP Skids
• Buffer Systems
Capture, Trending, Analysis and Reporting of Offline Data
• Offline Batch/Run Data
• Analytical Test Results Data
• SQC, Out-of-trend and Continued Process Verification
Capture, Trending, Analysis and Reporting of Stability Data
• Profile Trending
• Reporting
• Shelf-life prediction
ProcessPad RT
ProcessPad
offline
ProcessPad
stab
Our Software Reliance Program support is provided with all Bio4C™ ProcessPad modules.

17. How Bio4CTM ProcessPad Software Helps
Through data aggregation, management, visualizations, and analysis,
Bio4C™ ProcessPad makes all critical bioprocess data readily available.
Process lifecycle management
▪ Capture all development, scale-up, and commercial data
on one platform
▪ Simplify tech transfer process
▪ Access to the latest version of process map
Reporting
▪ Generate process summary reports
▪ Create ad-hoc reports required in root cause investigations
▪ Batch excursion reports, equipment utilization
Continued Process Verification and analytics
▪ Aggregate real-time and offline process data
▪ Statistical process control (SPC) and process capability
▪ Preconfigured trending rules to aid process monitoring
▪ Process analysis tools to aid investigations & process troubleshooting
▪ Control limits management

18. Common Applications for Bio4C™ ProcessPad
18
Continued
Process
Verification
CDMO data
Management
Investigations
Process
monitoring

19. Sponsor 1
Organization
CMO hosts the
Bio4C™ ProcessPad
platform on cloud or
internal IT Network.
CMO provides specific
product data access to
respective sponsor
CMO
Bio4CTM
ProcessPad
Contract Test
Lab A
Sponsor login to
CMO’s Bio4C™
ProcessPad portal
to access or
monitor data
CMO IT Network or Cloud
Sponsor 2
Organization
Sponsor 3
Organization
CMO Hosted Platform with
Access to Multiple Sponsors and Contract Labs
Source: http://processpad.simplyfeye.com/blog21.html

20. Statistical Process Control –
Case studies with
Bio4C™ ProcessPad

21. Setting Up a SPC Based Monitoring Program
Identify CPP, KPP
and MP from
performanceand
operating parameters
fromprocess
characterization/
validation documents
1
Evaluate the root
causeof each rule
violation and is impact on
productand process.
Initiate appropriateCAPA
if needed.
8
Publish quarterly
process summary reports
(can feed APRs). Will
haverecommendations
for process
improvements and limit
updates
9
Identify parameters thatneed
to be trended periodically
2 Get validation ranges and
specification limits (if any) for
these parameters respectively
3 Establish a technique for
statistical controllimits and
frequency to update the
controllimits
4
Monitor parameters against
set limits
7 Publish an in-process control
and monitoring document for
each commercial process
6
Establish trending rules
(Nelson Rules)
5
Update controllimits in the
systemupon every limit
update via a change control
11
Update
ControlLimit
10

22. SPC Case Study
Problem Discovery Investigation
1
High viability overall and
lower DS yield observed
recent batches
2
3
Step yield before DS
step shows a trend
An inverse trend also
observed in an
upstream parameter
Yield variability

23. SPC Case Study
Yield variability
Analysis Confirmation
4 Strong inverse correlation
between 2 and 3 suggest
potential cause of variability
from upstream feed strategy
5 Lower protein leads to lower loadability which
seems to be inversely proportional step yield,
indicating that there is a threshold range of
operating space of loadability

24. SPC Case Study
Yield variability
• Investigation revealed the main root cause to be variability in feed strategy
• Erratic behavior of DS yield was correlated to loadability issue in the
penultimate chrom step before final DS stage
Analysis and Confirmation CAPA
6 Loading going down with
batches
7
Suggested space of loading
quadrant for maximizing
yield
CAPA 1
CAPA 2
Upstream to investigate the
feed strategy and its impact
on final yield

25. InstrumentMaintenance

26. Advanced Analytics with
Bio4C™ ProcessPad 4.1

27. What’s New with Bio4C™ ProcessPad 4.1
Advanced analytics capabilities
1. Multivariate analytics – inter-batch Principal
Component Analysis (PCA) for batch performance data
2. Anomaly Detection - Pattern Search for machine
streaming data
3. Other improvements and bug fixes (as a part of
regular software release life-cycle management)

28. Applications for Multivariate Analytics Using Bio4C™ ProcessPad
28
Campaign
analysis
Investigations
Process
monitoring

29. Multivariate Analytics
The need for inter-batch PCA for batch performance data
Case study - Identification of outlier batch amongst multiple media lots. These media lots are being tested for more
than 50 critical to quality attributes (such as amino acids peak areas, purity estimates, etc.) with associated statistical
limits.
Analyzing >50 CQA control charts and further identifying
the outlier, contributing factors is not only time
consuming but a never-ending task…

30. Multivariate Analytics
Inter-batch PCA to the rescue – executing algorithm
1 Automated data assembling using Bio4C™ ProcessPad
2 Remove categorical columns and click on Run ‘PCA’ using
Culture Media Batch ID as Observation column

31. Multivariate Analytics
Inter-batch PCA to the rescue – analysis of results
3
Analyze the score and loading plots from the PCA
output. It shows 52% of the variation captured by
PC components. Click on batch CSR010 as it seems
to be an outlier batch
4
Alanine and Glycine
peak areas seems to
be major variability
contributors

32. Multivariate Analytics
Inter-batch PCA to the rescue – associating output with control charts
5
Clearly the
parameter value for
this batch is on the
higher side in both
CQA control charts

33. Advanced Analytics
Pattern search on machine profiles – identifying anomaly patterns
Bio4C™ ProcessPad’s new “Pattern Search” feature provides process engineers this ability to
easily extract an anomaly profile from a time series for a time-range or within a batch. These
can then be annotated, saved and searched with historical profiles for similarities

34. Advanced Analytics
Pattern search on machine profiles – overlaying anomaly patterns
The matches are overlaid and can be ranked based on percentage match. Further insights may
be gained with the start and end times of the matches by drilling down into the profile searches
for other sensors from the same machine during the time anomaly detected.

35. Collaborative and intuitive
manufacturing intelligence
tool for process understanding
Out-of-the-box statistics and
data analysis tools mean you
don’t have to be a data scientist to
get the information you need
Significantly increase employee
productivity with increased focus on
process insights and less time
hunting for data
Adaptable to any complexity
in batch manufacturing
process/products
(biologics, vaccines, small
molecules, gene therapies, etc.)
Minimal learning curve – easy to
use, intuitive browser-based
interface
Low maintenance, easy to
deploy, scalable browser-
based platform
Trusted single source of
truth for all process
execution data
Purpose built for the
biopharma industry
designed by bioprocess
engineers
Promote data-driven decision
making culture within
manufacturing and quality
organization
Tool to promote unified
process communication
language at all levels of
the organization
Key Product Highlights
Accessibility to all PD and MFG
data – on a single platform
Vendor agnostic with ability to
connect to multi brand process
equipment and electronic databases

36. Bio4CTM ProcessPad Software Resources
Questions?

37. The vibrant M, Millipore, MilliporeSigma, BioContinuum, and Bio4C are trademarks of Merck KGaA, Darmstadt, Germany or its affiliates. All other trademarks are
the property of their respective owners. Detailed information on trademarks is available via publicly accessible resources.
© 2021 Merck KGaA, Darmstadt, Germany and/or its affiliates. All Rights Reserved.