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14th June 2017 ISSCR ISSCR Annual Meeting’s Industry Focus Session“From the Bench to the Clinic: How to Manufacture Your Cell Product”
Marc-Olivier Baradez, PhDLead Scientist Analytical Development
Product testing and release criteria: The importance of analytical method development and validation, including potency assays
The Cell and Gene Therapy Catapult
£70m Development Facility
• 1,200m2 Custom designed cell and gene therapy
development facility
• Prime location in the heart of the London
clinical research cluster
• 120 permanent staff
£55m large scale manufacture center
• 7,200m2 manufacturing centre designed specifically
for cell and gene therapies
• Located in the Stevenage biocatalyst
• Opening 2017
Range of Cell and Gene Therapy products
Who we work with
In this presentation
1) Cell and gene therapy characterisation
2) Case study 1: in-process inferential analysis
3) Case study 2: real-time potency assay
Cell and gene therapy characterisation
Why is cell & gene therapy characterisation important?
Control of the
manufacturing process
Ensure quality and
lot-to-lot
consistency of
the final product
Anticipate sub-optimal manufacture runs
Assess product integrity
and stability
Towards automated manufacture
Manual
• Established
• Open
• High risk
Automation –Modular
• Reproducibility
• Robustness
• Integration
Automation –Integrated
• Reduce labour
• Containment
• Efficiencies
Automation –Step Change
• High-throughput
• Integrated PAT
• Small footprint
Industrial realisation
Cost of goods
Requirements and challenges for cell product characterisation
• Knowing product characteristics is critical for the development of cell therapies
• Critical Quality Attributes (CQA’s): biological aspects of a cell therapy product • Potency
• Mechanism of action (MoA)• Product comparability
• Characterisation, composition• Product quality
• CQA’s are very difficult to measure during manufacturing • They can change during the life cycle of the product• They can be difficult to measure directly, surrogate markers offer more flexibility• Limited shelf-life at end-point• On-\in-\at-line monitoring strategies?
• What to measure? How to link end-point to in-process features ?
bio
log
ym
ea
su
rem
en
ts
Wish list
Hurdle
T Cell
Ideal scenario
Upstream Downstream Monitoring
Characterisation
Purity
Potency
Identity
In Process Testing CGT monitoring
Safety
Identity
Persistence
Distribution
Potency
Purity
Identity
Safety
Purity
Identity
Safety
Release Testing
T Cell
T Cell
T Cell
T Cell
T Cell
T Cell
Cells
Product knowledge Manufacture design space
Flexible manufacture
ProcessControl
ProductConsistency
ProductSafety
ProductEfficacy
An
aly
tic
al
Inp
uts
Pr
oc
es
s O
utp
uts
T Cell
Current status
Upstream Downstream Monitoring
Characterisation
Cell count
In Process Testing CGT monitoring
PersistenceCell Count Identity
Safety
Release Testing
T Cell
T Cell
T Cell
T Cell
T Cell
T Cell
Cells
An
aly
tic
al
Inp
uts
Pr
oc
es
s O
utp
uts
Variable startingmaterial
Sub-optimalprocessing
Limited control High productVariability
Limited product characterisation
Case study 1 Case study 2Potency
Case Study 1
In-process characterisation:
Inferential methodology
Inferential measurements
• Indirect assessments of a product’s critical quality attributes measured through a surrogate parameter
• Require direct links between characteristics to be validated
• Should support opportunities for real time process adjustments, maintaining optimal operational conditions and increasing process consistency –
• Enable real time product release
Glu
cose
Co
nce
ntr
ati
on
(%
)
Cel
l N
um
ber
x10
6
Inferential technologies
Technology Measurement
In-lineNIR spectroscopy
Glucose/Glutamine/Lactate/AmmoniaVCD/TCD/osmolality
Raman spectroscopyGlucose/Glutamine/Lactate/AmmoniaVCD/TCD/osmolality
Fluorescent sensors pH and DORefractive index Compositional changesmultiwavelength Fluorimetry Amino acidsHolographic imaging Cell shape/size, cell viabilityImpedance Biomass / call viabilityTurdibimetry Biomass
On/At-lineHPLC
Media components (amino acids, sugars, proteins, metabolites)
LC-MSMedia components (amino acids, sugars, proteins, metabolites)
Coulter counter Biomass / call viabilityImaging Cell size/shape, cell viabilityPhotometric analysers Glucose/Glutamine/Lactate/Ammonia
How do these technologies fit with cell therapy manufacture?
Sample availability
Stirred Tank Bioreactor
In-line:pH, DO, biomass (probes)Metabolites (spectroscopy)Morphology/viability (In-situ imaging)
On-line:Biomass (coulter counter)Viability (holographic imaging)
At-line:Metabolites (photometric analysis)Media components (LCMS/HPLC)
Planer culture
In-line:pH, DO, (fluorescent sensor)
At-line (during media change):Metabolites (photometric analysis)Media components (LCMS/HPLC)
Rocking motion culture
In-line:pH, DO, (fluorescent sensor)Biomass (capacitance probe)
At-line:Metabolites (photometric analysis)Media components (LCMS/HPLC)
Hollow Fibre Bioreactor
At-line:Metabolites (photometric analysis)Media components (LCMS/HPLC)
Connecting PAT to CQA’s: CGT strategy for inferential measurements
Fully deployed, this approach is powerful
Useful to identify• Identity markers• Quality markers• Potency markers• Process-related markers• Surrogate markers
The implementation is adaptable to budgeted constraints
Robust inferential markers by LC-MS
Raman spectroscopy for inferential on-line monitoring
50
60
70
80
90
100
0 2 4 6 8 10 12 14
run 1 - viability
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run 1 - viable cells
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run 2 - viability
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run 2 - viable cells
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“cell number”cell number viability “viability” “proliferation status and inverse correlation with
viability”
“donor specific marker”
cell counter 5 Raman peaks
Case Study 2
Potency Assay Development
Introduction 20
Potency assay
An assay which measures the clinical biological function of a cell therapy product (mechanism of action known)
FDA and EMA expect potency testing with defined acceptance criteria to be in place before the
start of pivotal clinical trials
It is expected that validation of the potency assay will have been
completed before submission of a market authorization
Potency assay for a TCR Immunotherapy
Current T-cell potency assay:- Surrogate measurement of cell activity- measure cytokine stimulation in the transduced T-cells in response to target
peptide (IFNγ, TNFα and IL2)
New assay development:- direct measurement of cell killing by T-cells- replace commonly used assay for cell killing (Cr51 assay)
A B C
Impedance Spectroscopy based potency assay
0
1
2
3
4
5
6
2 4 6 8 10 12 14 16
Impedance (
CI)
Time (Hours)
Initial Cell Attachment
ContinuedAttachement
Max Attachment
No Cells
18
Cell Death
Impedance killing assay
0%
20%
40%
60%
80%
100%
120%
4 6 8 10 12 14 16 18 20 22 24
0:1 1:1 2:1 5:1
No killing
Maximum killing
E1:T1 killing stops between 8-12h, never reaching 50% cell death
50% cell death (‘EC50’) observed for E5:T1.
EC50 reached within 4h of adding effector cells.
Killing Specificity
0.5
0.6
0.7
0.8
0.9
1
1.1
0 5 10
5:1 effector/target
0.5
0.6
0.7
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0.9
1
1.1
0 5 10
5:1 effector/target
Non Specific 1
Non Specific 2
0.5
0.6
0.7
0.8
0.9
1
1.1
0 5 10
5:1 effector/target
Specific Peptide
Unpulsed
Effector only
Via
bili
ty %
100%
80%
60%
40%
20%
time (h)
Image analysis
26
Summary
Optimisation
Qualification(gain
confidence and learn
about assay limits)
Formal Validation
ICH(demonstrate suitability for
intended purpose)
Technology transfer
Future challenges for cell and gene therapy characterisation:
Assays/methods flexible to changing processing methods
Known mechanism of action
Real-time readout
Rapid
Robust (limited operator variability, automated sampling)
Data integration across platforms
Acknowledgements
Damian Marshall
Beata Surmacz-Cordle
Alex Chan