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New CLSI Document for the
Validation of Methods Preformed by Flow Cytometry –
Sneak Peek and Update
Virginia Litwin, Ph.D.
Vice President, Immunology
2
CLSI H62 – Validation of Methods Performed by Flow Cytometry
Sneak Peek Overview
Document Writing Committee
Process and Timelines
Content Highlights
H62 Document Writing Committee
Leadership• Virginia Litwin, Chair
• Teri Oldaker, Vice Chair
• Raul Louzao, Secretary
• Dave Sterry, CLSI Standards Director
Voting MembersDavid Barnett, Jacqueline, Cleary, Tom Denny, Cherie Green, Wolfgang
Kern, Natalia Kokorina, Jennifer Stewart, Lili Wang
Contributors and ReviewersElena Afonina, Ahmad Al Samman, Tony Bakke, Fiona Craig, Bruce Davis,
Lorella Di Donato, Steve Eck, Nancy Fine, Ben Hedley, Shuguang Huang,
Jerry Hussong, Andrea Illingworth, Cassie Jiang, Mike Keeney, Natalia
Kokorina, Sarah Maremont, Laura Marszalek, Kathy Muirhead, Andy
Rawstron, John Schmitz, Alan Stall, Maryalice Stetler-Stevenson, Horacio
Vall, Alessandra Vitaliti-Garami, Paul Wallace, Brent Wood, Yuanxin Xu
3
Document Writing Committee Composition
Affiliations
• Academia
• Biopharmaceutical
• CRO
• Clinical Laboratories
• Reagent/Instrument
Manufacturers
• Government
- FDA
- NIST
4
Scientific Societies
• AAPS
• CAP
• ESCCA
• ICCS
• ISAC
Provenance• Canada
• Germany
• Switzerland
• UK
• USA
Special Reviewers
ICCS, Advocacy Committee
AAPS, Flow Cytometry Action Program Committee
5
Ruth Barnard, Steve Eck, Catherine Fleener, Fiona
Germaschewski, Christele Gonneau, Cherie Green, Chris
Groves, Michael Hedrick, Shuguang Huang, Shibani Mitra-
Kaushik, David Lanham, Virginia Litwin, Thomas
McCloskey, Thomas McIntosh, Maxime Moulard, Sam Pine,
Kruti Shah, Ulrike Sommer, Soren Sonder, Jennifer Stewart,
Yongliang (Steve) Sun, Alessandra Vitaliti, Dave Williams,
Sam Witherspoon, Yuanxin Xu, Chelsea Xue
Thomas Denny, Pranav Dorwal, Jeannine Holden, Jerry
Hussong, Wolfgang Kern, Virginia Litwin, Sara
Monaghan, Teri Oldaker, Andy Rawstron, Stephanie
Toney, Christopher Trindade, Paul Wallace
Process and Timelines
Document publication (Word/InDesign), December 19
Final Draft, August 19 Final CLSI vote (20 days), September 19
Circulate right to appeal (30 days), July 19
Prepare responses and finalize comments , June 19
Circulate Draft / Open Comment (60 days), February 19
Final Draft Approved by Voting Members November 2018
Face-to-face Kick-off (Kansas City, MO) September 2017
6
Impact
• Extensive review process
• American National Standards Institute (ANSI)compliant
• Alignment with International Organization for Standardization (ISO)
- CLSI serves as the ANSI-appointed Secretariat for the ISO
Technical Committee 212 (ISO/TC 212)
• Regulatory agencies often recognize CLSI guidelines
Document Outline
Chapter 1 Scope
Chapter 2 Quality System Essentials
Teri Oldaker
Chapter 3 Fit for Purpose / Iterative Approach
Fiona Craig
Chapter 4 Instrument Qualification, Setup, and Standardization
Cherie Green
Chapter 5 Assay Development and Optimization
Ben Hedley
Chapter 6 Assay Validation
Steve Eck
Chapter 7 Examination Phase/ Post-Examination Phase
Raul Louzao
Pre
-Exa
min
atio
n P
ha
se
Chapter 1Scope
Scope
• Recommendations and Practical Instructions- One-stop shopping
- Current best practices
- Summarize recent white papers and scientific advances
• Target Audience- Basic research laboratories (non-regulated)
- Clinical (regulated US and ex US)
- Drug discovery, development, and manufacturing (regulated and non-regulated)
- Reagent, assay, and instrument manufacturers
- Regulatory agencies
Out of Scope
• Out of Scope- Individual cell type-specific assay development
- The validation of flow cytometric assays for soluble analytes
- Third-party software and LIS interface validation
Chapter 4Instrument Qualification, Setup, and Standardization
Chapter 4 Outline
4 InstrumentQualification,Setup,andStandardization
4.1 InstallationQualificationandOperationalQualification(IQ,OQ)
4.2 Performancequalification(PQ)
4.2.1 LinearityandDynamicRange
4.2.2 ElectronicNoise
4.2.3 Resolution
4.2.4 Carryover
4.3 Cross-instrument,cross-sitestandardization
4.3.1 ExamplesofCross-standardization
4.4 Compensation:
4.4.1 Generalfactorstoconsiderforcalculatingcompensation:
4.4.2 Typesofcompensationcontrols
4.4.3 CompensationandLinearity
4.5 LongitudinalPerformance
4.6 Qualificationandverificationofinstrumentforintendedpurpose
Chapter 4--Take Home Message
• Instrument qualification is often neglected
• The foundation of good data
Goals of Instrument & Software System Qualification
Establish and maintain a controlled environment that can produce reliable data over a long period of time
Ensure integrity and reconstruction of data
Support lifecycle of the system by establishing procedures from installation to decommission
Installation Qualification
INSTALLATION
PARAMETER
PASS/FAIL
CRITERIA
DOCUMENTATION NOTES
Environment
Benchtop and
associated lab
space meet
vendor
specifications
Checklist with
vendor
requirements,
positive
notation of
Pass/Fail and
initial and date
Consider space
requirements for
instrument/computer
footprint and
additional clearance fo
future maintenance
Utilities
Temperature
and humidity
of lab space
meets vendor
specification
Checklist with
vendor
requirements,
positive
notation of
Pass/Fail and
initial and date
Equipment used to
perform verification
should be documented
in report appended to
the checklist
Electrical
Electrical
requirements
meet vendor
specifications
Checklist with
vendor
requirements,
positive
notation of
Pass/Fail and
initial and date
Equipment used to
perform verification
should be documented
in report appended to
the checklist
Hardware
Verify all
components
are installed
Document
instrument
specifications
(model, serial
number,
manufacturer
date)
Include all associated
components, if any,
including automated
sample acquisition
modules,
uninterrupted power
supplies, etc.
Operation Qualification
OPERATIONAL
PARAMETER PASS/FAIL CRITERIA DOCUMENTATION NOTES
Software
functionality
Perform automated
system functions
(startup, QC)
Screenshot and/or
report with positive
notation of Pass/Fail,
initial and date
Include automated
maintenance procedures
System alerts
Stress the system to
demonstrate that
system detects
problems and displays
appropriate warnings Document warnings
displayed with
screenshots, initial
and date
Visual cues can also be used
to prompt user to change
fluids
Example: Attempt to
acquire data with low
fluidics level or
disconnected
computer cable
Example: Fluidics icons
change color when low levels
are detected. System should
have warning and not allow
further acquisition until
fluidics issues are addressed
Optical
precision
Run calibration beads
to verify %CVs,
detector sensitivity
and laser power
output meets vendor
specifications
Checklist with
vendor
requirements,
positive notation of
Pass/Fail and initial
and date
Include any automated QC
report,
all testing reagents should be
documented in a report
attached to the checklist
Automated
sample
acquisition
Acquire triplicates of
testing material
(beads or cells) in
randomly distributed
locations in carousel
or plate
Checklist with
positive notation of
successful sample
acquisition, Pass/Fail
and initial and date
There is some overlap in PQ;
replicate samples could also
be used to demonstrate
precision. OQ can be
performed using beads
whereas PQ requires
intended use biological
samples.
Performance Qualification
Optical alignment
Linearity and dynamic range
Detection efficiency (Q)
Electronic noise (SDen)
Background signal (B)
Overall resolution of the detection system, which is impacted by efficiency, background, electronic noise
Acquisition carryover
Look What’s New!
19
• The National Institute for Standards and Technology (NIST)
o Fluorescence calibration beads with traceable equivalent
number of reference fluorophores
• Enable us to speak the same language
Traceable ERF Value Assignment to Commercial Microparticlesnt to Commercial Microparticles
FC Bead Ex Laser (nm) SRM 1934
FITC 488 Fluorescein
PE 488 Fluorescein
BB515 488 Fluorescein
PerCP 488 Nile Red
PerCP-Cy5.5 488 Nile Red
PE-Cy7 488 Nile Red
APC 633 APC
APC-R700 633 APC
APC-H7 633 APC
APC-Cy7 633 APC
V450 405 Coumarin 30
BV421 405 Coumarin 30
V500-C 405 Coumarin 30
BV510 405 Coumarin 30
BV605 405 Coumarin 30
Six Peak Hard
Dyed Micro-
particles
Ex Laser (nm) SRM 1934
Intensity 2-6 488 Fluorescein
Intensity 2-6 488 Nile Red
Intensity 2-6 633 APC
Intensity 2-6 405 Coumarin 30
Cytometry Part A ●●●● 73A: 279-288, 2008; Flow Cytometry Protocols: Third Edition, p53-65, 2011Current Protocols in Cytometry, 75:1.29.1-14, 2016; Flow Cytometry Protocols: Fourth Edition (in press)
Traceable ERF Value Assignment to Calibration Beads. Flow Cytometry Quantitation Consortium 81 Federal Register 136 (15 July
2016), pp. 46054-46055 ERF Value Assignment to Cytometer Calibration Beads Submitted by Consortium Members
Two step process:
Aim: Provides evidence of linear
range/proportionality and resolution, provides
evidence of comparability within experiment
and between experiments on single
instrument
Aim: Transforms fluorescence scale to ABC
scale, provides reasonable instrument
independent transferable scale
1. Establish linear range in
fluorescence scale using beads
assigned with “Equivalent number
of Reference Fluorophores (ERF)
values
2. Anchor the fluorescence scale
(FS) to a benchmark cell material
with a known protein expression in
the unit of Antibodies Bound per
Cell (ABC)B
en
ch
ma
rk s
ca
le
Lili Wang
Building Measurement Assurance in Flow Cytometry
CYTO Workshop 13
ERF for Benchmarking Instrument Scale
Instrument Standardization
• Why standardize?- Inter-instrument variation
- Major source of variability
o Within the same lab
o Between experiments
o Multicenter clinical trials
• Goal of instrument standardization- Reproducibly set gains (PMT voltages) to achieve equivalent
fluorescence measurements (MFIs)
o Experiment to experiment
o Instrument to instrument
o Lab to lab
o Platform to platform
- Accurately measure / assign fluorescence spillover values which are used for fluorescence compensation
- Maintain consistent longitudinal fluorescence measurements
21
Instruments Compatible for Standardization
• Similar excitation lasers and collection optics
• Have stable fluidics
• Be sufficiently sensitive to discriminate dim fluorescence signals
• Give reasonably low background (photon and/or electronic noise)
• Produce linear signal across dynamic range for intended use
• Produce data conforming to the current Flow Cytometry Standard (FCS) data format
22
Instrument Standardization
Recent Advances
• New instrumentation- Built-in, automated processes for setup and between
instrument standardization
• Existing instruments- Processes for reducing between instrument/platform variability
o Peer reviewed publications Cytometry Part A 73:279, 2008
Cytometry A 81:567, 2012
Cytometry Part A 85:1037, 2014
Cytometry B 90:159, 2015
o Vendor derived process M. Ettinger. A New Method For QUANTITATIVE STANDARDIZATION of Flow
Cytometry Instruments. Contract Pharma. 2015
I. Athanasiadou and C. Gonneau. Challenges of flow cytometry for global clinical trials. ESCCA, 2017
23
Case Study
Inter-instrument variability is reduced when instruments are standardized
Standardization ProcessTwo Identical Instruments
Fluorescence intensity readout
Best Detector Worst Detector
None
Manufacturer’s setup process
Daily Setup passed
17.9 %CV 37.4 %CV
Standardized Instrument
(hard dyed beads)9.36 %CV 0.93 %CV
Standardized Instrument
(true fluorescence)<5%CV <5%CV
M. Ettinger. A New Method For QUANTITATIVE STANDARDIZATION of Flow Cytometry Instruments. Contract Pharma.
2015
I. Athanasiadou and C. Gonneau. Challenges of flow cytometry for global clinical trials. ESCCA, 2017
Want More Details???
Validation the Key to Translatable Flow Cytometry a Three Part Series:
Instrument Qualification
29 October 2018
cytou.org
Chapter 5Assay Development and Optimization
Chapter 5 Outline
Chapter5:Pre-examinationAssayDevelopmentandOptimization
5.2 Assay Evaluation
5.2.1 Steric hindrance 5.2.2 Tandem Fluorochrome interactions
5.2.3 Differences in affinity
5.2.4 IgG dependence
5.2.5 Fc Binding
5.3 Assay Optimization
5.3.1 Premade Cocktailed Antibody Combinations
5.3.2 Preliminary Stability: Reagent/Cocktail stability
5.3.3 Specimen Stability
5.3.4 Controls 5.3.5 Data Acquisition
5.3.6 Data Analysis
5.3.7 Documentation
5.1.1 Assay Development
5.1.2 Define the Assay
5.1.3 Considerations
5.1.4 Matrix 5.1.5 Viability
5.1.6 Antigen and Antibody Selection
5.1.7 Fluorophore Selection
5.1.8 Other Reagents 5.1.9 Sample Cell Concentration
5.1.10 Sample Lysis 5.1.11 Antibody titrations
5.1.12 Blocking
5.1.13 Fixatives
5.1.14 Gating Strategies
5.1.15 Incubation Temperature
Process Map
Assay Objectives
Assay Design
Optimization
Initial Characterization
• Precision
• Stability
Initial Considerations
• What do you want to measure?
• How will you define your population of interest?
• Positive selection antigens
• Negative selection antigens
• In what matrix?
Establish the Assay Objective
• Number and type of lasers
• Number of detectors
• Number of markers
• Number of tubes
• Filter configuration
• Fluorophore selection
What instrument do you have?
Assay Types
• Immuno-phenotyping assays- mAb
- Multimers
• Leukemia/Lymphoma diagnostic assays
• Minimal residual disease (MRD) monitoring
• Phos flow assays
• Receptor occupancy (RO) assay
• Functional assays - Intra-cellular cytokine detection
• Pharmacokinetics (PK) assays - CAR-T
- Other cell-based therapies
Data Output
• Relative percentage of a parent population
• Cell concentration (cells/unit volume)
• Fluorescence intensity
• Percent bound, percent free for RO assays
• Phenotypic description
Matrix
• Whole blood (anticoagulant choice)
• Bone marrow aspirates/cores (anticoagulant choice)
• Other body fluids (CFS, sputum)
• PBMC/BMMC
• Tissues
• TILs
• Cell lines
• Other (marine, bacteria, ….)
Blood Collection Materials
Anticoagulant Description Pros Cons
EDTA- -
Sodium Heparin - - -
ACD- - -
Sodium Citrate- - -
Stabilization Tubes-
-
Assay Design
• Reagents- Antigen/Fluorophore pairing
- mAb clone evaluation
- Reagent titration
Goals of Titration
• Determine specificity and staining intensity of an antibody
• Minimize compensation requirements
• Determination of quantity of new antibody to be used
- Signal should provide adequate room for evaluation of dim or
bright expression
• Quality control of new antibody lots
- Antibody performance should compared to known lot
1 mL 2 mL 3 mL 5 mL 8 mL 10 mL
Optimal Titer
Volume MFI+ MFI- SDneg S/N SI%
Gated
10uL 160.088 2.178 1.215 73.5 100.3 70
8uL 127.259 1.537 1.055 82.8 113.0 70
5uL 92.462 1.075 0.859 86.0 117.4 70
2.5uL 52.466 0.61 0.502 86.0 117.4 70
1uL 32.016 0.492 0.492 65.1 88.8 70
0.5uL 19.258 0.422 0.274 45.6 62.3 70
Staining Index =(������� − ������ ��)
2 � (�� ��)
������ �� ���� = ������!� − ������ ��
Assay Design
• Wash/lyse/fix sequence and buffer evaluation
• Acquisition Templates- Number of events to acquire
- Thresholds
- Voltage Settings
• Gating Strategy- The population of interest should be included in the gate
- Other cell subsets/non-specific events should be excluded
Lymph PC Blasts Monos Grans Debris
Lyse A 62% 0% 27% 0% 6% 3%
Lyse A 60% 0% 30% 0% 3% 5%
Lyse C 27% 0% 15% 0% 3% 54%
Lyse D 11% 0% 6% 0% 1% 81%
Lyse E 29% 0% 17% 0% 2% 51%
Other Reagents
• 7-amino-actinomycin D (7AAD)
• 4’6-diamidino-2-phenylindole (DAPI)
• Propidium Iodide (PI)
• Detergents and Solvents
• Lysis Reagents
• Fixatives
• Blocking Reagents
Want More Details???
Step-by-Step Multi-parameter Panel Design
Jennifer Wilshire
Tomas Baumgartner
15 October 2018
cytou.org
Chapter 3 Outline
Chapter3:FitforPurposeApproachtoAnalyticalMethodValidationfor
FlowCytometricMethods
3.1 Considerations
3.1.1 BioanalyticalDataCategoriesandCalibrationCurves
3.1.2 ReferenceStandardsforFlowCytometry
3.2 ApplicationofStandardValidationParametersforFlowCytometricMethods
3.2.3 Accuracy/Trueness
3.2.4 Linearity
3.2.5 SpecificityandSelectivity
3.2.6 Sensitivity
3.2.7 Precision
3.2.8 Stability
3.2.9 Assaycarryover
3.2.10 ReferenceIntervals
3.3 Fit-for-PurposeApproach
Fit-for-Purpose Validation Concept
• Fit- All data must be reliable
• Purpose- Any purposes
• Fit-for-Purpose- Analytical validation requirements
o Specific to the current intended use of the data
o Specific to the regulatory requirements, if any, associated with that use
• Practical, iterative approach
Lee et al. Pharmaceutical Research, 22:499, 2005
Iterative Validation Approach
Assay Development /Optimization
InitialValidation
• Assess required parameters for INITIAL intended use
Assay Implementation
Extended Validation
• Assess additional parameters appropriate to NEW intended use
42
Challenges for Validation in Flow Cytometry
• The complexity of cellular analytes/measurands
- Increase complexity of cellular analytes in disease state samples
• The technology
- Highly complex
- Highly flexibility
• The reagents
- Highly complex
- mAb, fluorescent tags, tandem dyes
• The rate of technological advances
- Technology
o New instruments
o New software
- Reagents
o New fluorophores
• The rapid rate of biological discoveries
- New subsets identified
- Phenotypic definitions of existing subsets change
• The lack of TRUE reference material
• The fact that data are not derived from a calibration curve43
Validation Parameters and Flow Cytometry
ALWAYS
• Specificity
• Precision/Robustness
• Sensitivity
• Limit of Detection
• Limit of Quantitation
• Stability
• Reference Intervals
SOMETIMES
• Interference (Matrix, Drug)
IT'S COMPLICATED
• Accuracy
• Linearity
• Selectivity
“NEVER”
• Range of Quantification
• Incurred Sample Reanalysis
• Normal Signal Distribution
• Prozone Effect
What are the Validation Parameters?
Can they be evaluated in Flow Cytometry?
44
Bioanalytical Data Categories
Definitive Quantitative
Relative Quantitative
Quasi-quantitative
Qualitative
Lee et al. Pharmaceutical Research, 22:499, 2005
45
Definitive Quantitative Data
• Calibration curve
- Reference Standards
o Well defined
o Fully representative of the endogenous analyte
• Numeric results are interpolated from the calibration curve
• Intended use of the data
- Determine the absolute quantitative values for unknown samples
• Example
- LC-MS assay for PK
• Accuracy demonstrated by spike/recovery with well defined standard
Talanta 70.4 (2006): 678-690 46
Relative Quantitative Data
Image from proteintech
• Calibration curve
- Reference Standards
o “Less” well defined
o Not fully representative of the endogenous biomarker
• Numeric results are interpolated from the calibration curve
• Intended use of the data
- Estimate the quantitative values for unknown samples
- Emphasis on temporal changes in concentrations rather than absolute concentrations
• Examples
- Cytokine enzyme immunoassays
• Accuracy demonstrated by spike/recovery with standards
47
Quasi-Quantitative Data
• Intended use of the data
- Estimate the quantitative values
- Emphasis on temporal changes in concentrations rather than absolute concentrations
• Examples
- Flow cytometric assays
o Population frequency
o MRD
• Quasi
- Having some resemblance to
- Possession of certain attributes of
• Does not use calibration curve
- No reference standards
• Numeric data are reported
- Results are expressed in terms of a characteristic of the test sample
Image from Clinical Laboratory News, 12: 8, 2013
CD4CD4CD4
48
Qualitative Data
• No calibration standards
• Non-numeric data are reported
- Results are expressed in terms of a characteristic of the test sample
- Categorical data are reported
o nominal (yes/no) format
o ordinal (+, ++, +++) format (semi-quantitative) (EP12)
• Intended use of the data
- Characterization of the samples
• Examples
- Leukemia/Lymphoma characterization for diagnosis
- Anti-nuclear Antibodies
- Genetic marker/SNP
AML example from Paul Wallace
49
Impact of Type of Data on Validation Design
Validation Parameter
Definitive Quantitative
Relative Quantitative
Quasi-Quantitative Qualitative
Accuracy √ √ - -
Precision √ √ √ -
Sensitivity √ LLOQ √ LLOQ √ √
Specificity √ √ √ √
Dilutional Linearity √ √ - -
Matrix Stability √ √ √ √
Bioanalytical Data Category vs Validation Parameter
Lee et al. Pharmaceutical Research, 22:499, 2005
50
Assay Risk Categories
Clinical risk Purpose / Intended use of assay
Low Basic research assay
Drug discovery assay
Clinical trial biomarker assay (exploratory end point)
Moderate Laboratory developed test used as an aid to diagnosis
Clinical trial biomarker assay (secondary endpoint)
High
Clinical trial biomarker assay (primary endpoint)
Clinical trial biomarker assay (enrollment criteria endpoint)
Complementary diagnostic
Combination product / Companion diagnostic
Want More Details???
Validation the Key to Translatable Flow Cytometry a Three Part Series:
cytou.org
Method Validation Overview, Concepts
13 August 2018
Chapter 6 Outline
Chapter6:AnalyticalMethodValidation
6.1 ValidationPlanningPhase(SayIt!)
6.1.1 ValidationPlan
6.1.1.1 AcceptanceCriteria
6.1.2 QuantitativeData/Methods
6.1.3 QualitativeData/Methods
6.2 ValidationExecution(DoIt!)
6.3 ValidationReports(ProveIt!)
6.4 Fit-for-PurposeValidationPlans
Quantitative Data/ Methods
• Accuracy/Trueness • Specificity and Selectivity • Sensitivity
- Sensitivity – Analytical (LOB/LOD)
- Sensitivity - Functional (LLOQ)
• Precision - Experimental Design
- Precision acceptance criteria
• Linearity - Linearity for Relative Quantitative Data
- Linearity for Receptor Occupancy (RO) Assays
- Linearity for Quasi-Quantitative Data
• Stability- Specimen Stability
- Processed Sample Stability
• Assay carryover (instrument)• Reference Intervals
Qualitative Data/ Methods
• Accuracy/Trueness
• Specificity
• Sensitivity
• Precision
• Stability
• Assay carryover (instrument)
• Reference Intervals
Validation Test Menus
*International Medical Device Regulatory Forum
Regulatory
Setting Intended Use of Data Assay Type
Validation
Recommendation
Non-regulated Basic research Novel assay Fit-for-Purpose
Validation Level 1
Non-regulated Drug discovery Novel assay Fit-for-Purpose
Validation Level 1
Non-regulated Exploratory endpoint in clinical development
Novel assay Fit-for-Purpose Validation Level 1
Non-regulated Secondary endpoint in clinical
development Novel assay
Fit-for-Purpose
Validation Level 2
Clinical
Laboratory Patient care/treatment
IVD/CE Approved
Kit
Verification per
CLIA
Clinical
Laboratory
Patient care/treatment clinical
risk LDT
CLIA/IMDRF*
Validation
GLP??? Primary endpoint in clinical
development Novel assay
Full Validation
Level 1
Manufacturing
(GMP)
Regulatory submission for new
diagnostic test Novel assay
Full Validation
Level 2
Manufacturing (GMP)
CDx Novel assay Full Validation Level 2
Test Menu Structure
Parameter Comments Samples Replicates Analytical Runs
Accuracy/Trueness
Specificity
Selectivity
Sensitivity
LOD
LLOQ
Precision
Repeatability (Intra-assay)
Reproducibility (Inter-assay)
Inter-operator
Inter-instrument
Linearity
Stability
Specimen
Processed Sample
Carryover
Reference Intervals
Documentation Validation PlanValidation
ReportQA Review
✓ ✓ ✓
Parameter Comments Samples Replicates Analytical Runs
Accuracy/Trueness
Specificity
Selectivity
Sensitivity
LOD
LLOQ
Precision
Repeatability (Intra-assay)
Reproducibility (Inter-assay)
Inter-operator
Inter-instrument
Linearity
Stability
Specimen
Processed Sample
Carryover
Reference Intervals
Documentation Validation PlanValidation
ReportQA Review
✓ ✓ ✓
Want More Details???
Validation the Key to Translatable Flow Cytometry a Three Part Series:
cytou.org
Method Validation
Planning and Execution
10 September 2018
Additional Resources
Guidelines for the use of flow cytometry and cell sorting in
immunological studiesVolume47, Issue10Special Issue: Featuring the Guidelines for
the use of flow cytometry and cell sorting in
immunological studies
October 2017
Pages 1584-1797
Additional Resources
Special Issue: Validation of Cell‐‐‐‐Based Fluorescence Assays: Practice Guidelines from the International Council for Standardization of
Haematology and the International Clinical Cytometry Society
Volume 84, Issue 5Pages: 279-357
September/October 2013
Additional Resources
• Recommendations for the Validation of Flow Cytometric Testing During Drug Development: I Instruments. JIM, 363:104-119, 2011.
• Recommendations for the Validation of Flow Cytometric Testing During Drug Development: II Assays. JIM 363:120-134, 2011.
• Validation of Cell-Based Fluorescence Assays: Practice Guidelines from the International Council for Standardization of Haematology and International Clinical Cytometry Society. Cytometry Part B: Clinical Cytometry Special Issue volume 84B:2013
• Recommendations for the Evaluation of Specimen Stability for Flow Cytometric Testing During Drug Development. JIM, 418:1, 2015.
• Recommendations for the development and validation of flow cytometry-based receptor occupancy assays. Special Issue: Receptor Occupancy by Flow Cytometry, Cytometry Part B: Clinical Cytometry, 90B; 141, 2016.
• Best practices in Performing Flow Cytometry in a regulated environment: feedback from experience within the EBF. Bioanalysis 9:1253, 2017.
• ISAC CYTO University Webinars (available for download at cytou.org)
- Validation, the Key to Translatable Flow Cytometry
o Part 1: Method Validation- Overview, Concepts, August 13
o Part 2: Planning and Executing, September 10
o Part 3: Instrument Qualification, October 29
Summary
• Flow cytometric methods provide high quality, reliable data
• Validation parameters appropriate for soluble analytes are not appropriate
• Validation guidelines….coming soon!
62
Acknowledgment
• CLSI H62 Document Writing Committee
• Teri Oldaker, Co-chair
• Slide Sharing- Cherie Green, Genentech
- Jennifer Stewart, FCS Labs
- Ben Hedley, LHSC
63
64
Figure courtesy of Ira Schieren, Columbia University
Questions?
64
Contact Information
Virginia Litwin, Ph.D.
Vice President, Immunology
Caprion Biosciences Inc.
Montreal, Quebec
Canada
WWW.CAPRION.COM
LinkedIn: https://www.linkedin.com/in/virginia-litwin-99869511/
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