Integrated Continuous Biomanufacturing Platform
Addressing Challenges in Automation
Approaches and Gaps
Marina Hincapie, Ph.D.
Aleksandar Cvetkovic, Shawn Barrett,
Marcus Fiadeiro, Lin Huang,
JagdishTewari, Dhanuka Wasalathanthri
Biologics Development, Sanofi
mAbs and Platforms at Sanofi
BATCH PROCESSING: Large Volumes, High CAPEX, Limited Standardization
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Media + Bioreactor Clarify (MF) Capture Purify & polish Filtration Drug substance
KEY BENEFITS
• ↓ Facility footprint
• ↓ CAPEX (40–70%)
• ↓ Tech transfer risk
• Flexible capacity
• Regional access
KEY ATTRIBUTES
• Higher productivity (5– 20X)
• ↓ Residence times
• Process/product control
• Same scales in R&D & mfg
• Amenable to single-use
• Functionally closed • Reduced Volumes (e.g. 10,000L → 500L
bioreactor)
• Elimination of Steps (e.g. bioreactor/clarification
integration)
Current ICB (hybrid)
Perfusion reactor with
continuous capture Purify &
polish
Filtratio
n
Drug
substanc
e
Intensified Perfusion Platform (IPP) Development for mAbs
ICB platform (new cell line, chemically defined medium) gives ~100 fold productivity improvement for RP#1 (10L)
Through development of an in-house chemically defined medium, IPPv1 supports cell densities >100x106 vcells/mL and volumetric productivity (VPR) >4 g/L/day
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mAb#1
100X
4-5X
• Synchronization of upstream perfusion with downstream purification flow rate
• Maintain sterility across the entire process
• Requires PAT for in-line monitoring and Real Time Release
• Adoption of PAT implementation has been slow •Cost, additional equipment, staff dedicated to
PAT
•Requires extensive validation of performance
End to End Continuous Biomanufacturing Challenges
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Proof of Concept demonstrated
at the lab scale
Analytical Off-Line Support for Continuous Manufacturing (CM) is Demanding on Resources
•Long production runs (weeks, months)
• Need to demonstrate ability to maintain product quality over an extended period of time
Investment in PAT development and
implementation will decrease cost over
time
Hypothetical case study:
Assumption: 15 targets/year
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PAT in R&D vs. Manufacturing
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PAT in the R&D Space- A Holistic Approach
• Use Multiple PAT tools simultaneously to aid the development and understanding of the process
• Design a “fit for a purpose PAT” to gather a good understanding of the process
• Define parameters that should be monitored during process development campaigns
• Use data to make connection between the process and the product quality attributes
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Spectroscopy + Chemometrics
Upstream
• Nutrients
• Metabolites
• Cell viability
• Productivity
Downstream
• Aggregation
• concentration
• Charge variants
• HCPs
Bioreactor autosampler + Analyzers
[protein]
Development and Implementing a PAT Strategy for CM Multidisciplinary Approach at Sanofi
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PAT
Where
Why
How
• Currently using in R&D for In-Line Monitoring, building/validating models
• RAMAN and FTIR for Upstream (14 parameters)
• Defining Attributes to control
• Developing Downstream FTIR models for CQA’s (concentration, aggregation, charge )
Select PAT
Tools
• Spectroscopy and Chemometrics
• Process Analyzers (2D-UPLC, Microfluidic devices, Flow VPE)
• Sensors and Probes
PAT Infrastructure
• Data Management and Multivariate Statistical Process Control Platforms
• Building Data Infrastructure
Raman vs. FTIR Comparison Characteristics
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Raman Spectroscopy FTIR Spectroscopy
Both non-destructive
Generates complex spectrum Generates highly complex
spectrum due to high sensitivity
Change in polarizability of a molecule Change in the dipole moment
No interference from water Strong water absorbance
Interference from room light No interference
Fluorescence may interfere with
spectra No fluorescence issues
Slow (15-20 mins) Fast (<20 secs) (Needed for
DSP)
Well established in USP for glucose
analysis Not fully explored in USP and DSP
Some components are not Raman active but FTIR active and vice versa
Development of FTIR for Upstream ICB-hybrid
Diamond ATR probe 4m (MIR) IN350-T
CPC Steam-Thru Connections
Steam-in-place for 30 minutes ~125ºC
Sterile welded directly into harvest tubing
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PROS
• Spectrometer for real-time monitoring
• Operates in the information rich mid-IR region; fast scanning rate
• High scanning rate (sec.)
• Connections for 6 fiber-optic probes
CONS
• Can only record one probe at a time
• Requires direct contact with liquid stream
• Liquid N2 to cool detector
Bruker MATRIX-MF® FTIR
FTIR inline Probe Housing
Assembly at the Harvest Tank
Glucose
Real time trending
Time
Trending
In-Line Real Time FTIR measurement in the harvest line
Excellent correlation with off-line measurements
FTIR Promising Technology for Continuous Biomanufacturing
mAb
10 L bioreactor
In-line probe in harvest tank
FTIR spectra (2 min.)
y = 0.987x - 0.0004 R² = 0.9973
0
1
2
3
4
5
6
0 1 2 3 4 5 6
Correlation
Ced
ex
FTIR
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Single spectrum= Multiple Attributes
Prediction of 14 parameters in-line harvest tank
Excellent Predictions for Titer, Glutamine,
Glutamate and Lactate using in-Line FTIR
Lactate g/L Glutamine mM Glutamate mM
Prediction
Bio HT data
Titer mg/mL
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• Data collection, automation, storage and tracking
• Data/information/knowledge: interactions between different units need to be extracted and understood
• Need Advanced analytics (IA) translate it into useful information to inform the process
Lots of Data is Acquired !!!
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What data to collect?
How often to collect?
integrate an automate
Data Mining?
Model Mintenance?
Future Mindset
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• Need improvements in autoclavable SU sensors, probes and analytical equipment with fast scanning properties
• New advancement in miniturazation of instrumentation for on-line and in-line analyzers, e.g. micro-chip devices etc.
• Integrated solutions for bioburden (adventitious agents) and process impurities detection for “near” real time or real time measurements
• Robust Liquid sensors for buffer identification (e.g. pH sensors)
Analytical Instrumentation Gaps For Detection and Quantitative measurements
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Automation Challenges
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Took ~ 4 months for
instruments integration
Due to a variety of
communication errors
Software
• Inability to trigger UPLC data acquisition from MAST system
Hardware
• Fine tuning of sample volume delivered from Gilson to Waters
• Injection volume restrictions due to design (fixed loop injection)
IT
• Requirement of permanent administrative rights for successful
workflow
• Corporate security requirements
Resources
• Ongoing use of MAST/Gilson by process development during
integration
• Next-generation manufacturing requires hardware, software, data analytics, and infrastructure , which can not be provided by a single vendor.
• No Plug and Play solutions
• Advancing automation solutions specifically for bioprocessing requires coordination as well as cooperation among vendors
• Skilled personnel at each activity
Connection, Integration and Data Automation is not a Straightforward Operation
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Concluding Remarks..
PAT platforms are key to implement end to end CM for In-line Monitoring (ILM) and real
time release testing
PAT will be widely accepted once the Biopharma industry Implements and demonstrates
improved efficiencies, cost reductions, and higher quality process/product
Groups like BPOG, The Open Group, and other industry associations are addressing
challenges and promoting a transparent and effective communication
“To meet the future requirements of controlling quality in real time, inferential models and
adaptive algorithms will be required that can make use of the significant volumes of data
being generated by future systems.”
Bio manufacturing Technology Roadmap, BPOG, 2017
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Acknowledgements
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Continuous Manufacturing
Skill Center
Shawn Barrett
Jared Franklin
Wenqin He
Xuezhen Kang
Marcus Fiadiero
BPD Leadership
Claire Davies
Rebecca
Sendak
Kripa Ram
BioProcess Analytics
Jagdish Tewari
Lin Huang
Dhanuka
Wasalathanthri
Victoria Berger
THANK YOU