Standardization of Flow Cytometry Workflows for Cell

Standardization of Flow Cytometry Workflows for
Cell Therapy Applications
Novartis Cell and Gene Therapies Unit (CGTU)
Sadik H. Kassim, Senior Fellow
ISCT-Las Vegas (May 27, 2015)
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and expressly disclaims: (a) any representation or
warranty (express or implied) with respect to the
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information.
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Flow Cytometry is a Keystone
Analytical Platform for Cell Therapy: cGMP Setting
D0 Composition
Product Release: CoA
In Process: Transduction
1. Porter DL, et al. N Engl J Med. 2011;365(8):725-733.
2. Porter DL, et al. J Cancer. 2011;2:331-332.
3. Kalos M, et al. Sci Transl Med. 2011;3:95ra73.
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Flow Cytometry is a Keystone Analytical Platform for
Cell Therapy: Research and Development Setting
Lead CAR selection involves choosing the optimal
ScFv/Signaling Domain Configurations
Alfred Garfall et al. Discovery Medicine, 2014
Marc Cartellieri et al. JBB, 2010
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-Phenotype
-Function
Flow Cytometry Assays:
Cell Based Cancer Immunotherapies
1)
2)
3)
4)
5)
Multi-parameter immunophenotyping of cells.
Intracellular cytokine staining (ICS).
Cytotoxicity assays.
Proliferation assays.
Cell-free cytokine analysis.
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Flow Cytometry Workflows:
What Needs to be Standardized?
1. Sample Preparation
4. Data Analysis
2. Instrument Setup
3. Data Acquisition
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Flow Cytometry Workflow Requirements
Regulatory and Quality
Standards
Throughput
Drug Discovery
Target
Identification
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Target
Validation
Preclinical
Pharmaceutical
Formulation
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Clinical
Toxicity
Evaluation
Clinical Trials
Automating Flow Cytometry Workflows
 Automation can potentially address the analytical challenges
on the path to commercialization.
 Automation is not just about increasing throughput.
• “Automation” means “walkaway” sample prep, acquisition, and analysis
 Key benefits:
• Rigorous management/tracking of multi-patient, multi-assay sample flows
• Reproducibility and robustness of notoriously variable cell-based assays
• Ease-of-transfer of analytical methods
• Applicability across portfolio.
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Flow Cytometry Workflow Standardization
Solutions: GNF High Throughput Flow Cytometry
 Industry-first, fully automated screening
system dedicated to processing and
reading cells using flow cytometry
Incubators
• 1536- or 384-well plates
• 50,000 wells per day, <1 FTE
GNF Sampler
Beckman
Coulter
CyAn
V-spin / seal /
de-seal
Chilled
incubators
Bravo Pipettor
Washer/dispenser
Flow Cytometry Workflow Standardization
Solutions: Commercial Options
Hypercyte-Autosampler
MSP Flow Cytoprep
BD SPAIII
IntelliCyt iQue Screener
Beckman Coulter
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CGTU Solution: Automation of Flow Cytometry
FlowSPAAA / FlowSPA3
Flow Cytometry Sample Prep Automation, Acquisition, and Analysis
Run Software
Sample Prep Automation
Acquisition
Analysis
• TRD prototype commissioned
• Protocol development ongoing
• Next: Test prototype and
optimize workflow
• Assessing multiple vendors
• Focus on validated BD equip.
• Next: establish timeline for
main & backup prototype paths
• TRD leading development
• Prototype analyses established
• Next: implement in research
workflows in CA and MP
Sample Prep Automation
Acquisition
• TRD prototype commissioned
• Assessing multiple vendors
• Protocol development ongoing
• Focus on validated BD equip.
• Next: Test prototype and
• Next: establish timeline for
11optimize
| ISCT Flow
Cytometry Workshop | Sadik
Kassim|
May 27,
2015 | paths
workflow
main
& backup
prototype
Analysis
• TRD leading development
• Prototype analyses established
• Next: implement in research
workflows in CA and MP
Output result
Free, Open Source R Based Statistical Programming
Aghaeepour et al. Current Topics in Microbiology and Immunology (2014)
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Novartis Custom Solution for Automated Flow
Cytometry Analysis
Drag and drop
data folder
Better control
over script
Progress Indicator
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Select Script
from Script folder
Automated Flow Cytometry Analysis
Panel 2 FMO
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Automated Flow Cytometry Analysis
Combination of data driven gates and FMO-based gates
Data
Driven
FMO
Based
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Automated Flow Cytometry Analysis
Panel 2 Gating Strategy
Data
split into
sections
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•
Plots
•
Descriptions
•
Code
Automated Flow Cytometry Analysis
Panel 2 Analysis
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Typical experimental setup
Automated prep and analysis of 10 color panel
 Samples: Various process development samples (healthy donors)
 Panel: 10 Color Differentiation/T Cell Subset Panel
Panel Composition
Lineage Marker #1
Lineage Marker #2
• Software analyzes control samples to set FMObased gates
Lineage Marker #3
• Dynamic gates generated where appropriate
Product Specific Antibody
• 175 gates of data are generated
Differentiation Marker #1
Differentiation Marker #2
Differentiation Marker #3
Activation Marker #1
Activation Marker #2
Viability Dye
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• 29 key populations of interest returned in report.
Data from two early experiments in aggregate
Manual vs Automated sample prep
 All analysis
automated (v1)
 Each point shows the
manual
manual and
automated prep
values for 1
population from 1
sample
 Strong correlation
across data in
aggregate
• r2 = 0.991
automated
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Looking at Each Population Individually
Manual vs Automated sample prep
 All analysis
automated
 Strong correlations
within populations as
well
• 24/29 w r2 > 0.9
manual
• Exceptions under further
investigation (small
values, etc)
automated
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Manual vs Automated sample prep
 All analysis
automated (v2)
 Each point shows the
manual
manual and
automated prep
values for 1
population from 1
sample
 Overall correlation
improved
• r2 = 0.998
automated
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Manual vs Automated sample prep
r2 = 0.999
manual
automated rep 2
r2 = 0.998
automated
automated rep 1
 Replicate samples processed in same plate present the “best case scenario”
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Automated Flow Cytometry Analysis
Manual Analysis
Variability – 3 FlowJo Users
UPCC04409-29G1
100
80
60
Mean
+/- SD
CV
40
4.55
1.76
20
1.79
12.69
5.33
37.37
42.70
0
CAR+
CAR+CD4+
Easy
23
CAR+CD8+
CD45RA+CCR7+
CD45RA+CCR7–
CD45RA–CCR7+
CD45RA–CCR7–
Naive
EMRA
Central Memory
Effector Memory
Messy
Conclusions and Future Directions
-Standardization of flow cytometry workflows, in research,
development, and manufacturing/QC will be important for
commercialization of cell therapies.
-Automation provides a potential cost-effective and reproducible
solution.
-In house data demonstrates that automated and manual flow
cytometry workflows produce similar results.
-Instrument qualification and assay validation will be critical for
the effective deployment of these approaches.
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Acknowledgements
Arnaud Colantonio
Chelsea Xue
Sean Garrity
Andrew Beavis
Viraj Tyagi
Joe Sieling
Brian Gismonde
Margit Jeschke
Nebojsa Milovic
Marty Giedlin
Mark Dudley
John Scott
Amy Shaw
Jeannine Larrieux
Lana Parent
Erik Rutjens
Olja Pulluqi
Poonam Vaidya
Piotr Pierog
Junxia Wang
Rod Rietze
Joe Chin
Ted Manley
Brian Duffy
Olivier Graf
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Dan Sipes
Dan Rines
John Scott
Jen Brogdon
Boris Engels
Fay Dufort