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

2

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

3

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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14

Automation Challenges

15

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