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1GLOBALPRODUCTDEVELOPMENTCLINICAL ASSAYGROUP
GLOBALPRODUCTDEVELOPMENTCLINICAL ASSAYGROUP
Considerations for Successful Biomarker Bioanalysis in Regulated Environment
Darshana Jani, M.Sc.Darshana.Jani@pfizer.com
10th European Bioanalysis ForumNovember 15, 2017
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Disclaimer
The contents of this presentation reflect the personal opinion of the author and may not represent the official perspectives of the affiliated organization
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Scope
§ Biomarker Basics§ Core Validation Challenges and Solutions
§ Case Studies§ Sample Analysis
§ Pre-analytical Factors§ Data Handling
§ Summary
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"Almostanythingyoucanmeasure"
BiomarkersDefinitionsWorkingGroup(2001)Clin PharmTher 69(3):89RFrankandRHargreaves(2003)NatureRevDrugDisc2:566.
What is a Biomarker?
Type 0: Markers of natural history of disease and that
correlate longitudinally with known clinical
indices.
Type I: Markers that demonstrate mechanism of action of a drug.
Type II: Markers that predict a clinical benefit (surrogates).
DIFFERENT TYPES
A characteristic that is objectively measured and evaluated as an indicator of normal biological processes, pathogenic processes, or pharmacological responses to a therapeutic intervention.
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Translational Lab Development Lab Clinical Study Clinical UtilityResearch/
Discovery
Key
act
iviti
es a
nd d
eliv
erab
les
Identification of Biomarkers
Generate a reasonable proposalEvaluate appropriate technology platforms
• Relevance to human subjects and target disease population
• In-house assay performance?
• Commercial Reagents?• Method transfer from
preclinical matrix to human matrix
• Assay optimization-Single assay vs multiplex format?
• Ensure operational feasibility-sample type, volume, throughput
• Fit for Purpose Method validation
• Data Generation • Control/sample• Performance and
trending• Review the
challenges-Fit for purpose
• Successful data generation
• Confirm assay utility
• Assay maintenance
• Establish or revise clinical utility based on intended use of the data
Biomarker Assay Flow from Research to Clinical Study
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What are the biggest challenges?
Scientific
Technical
Regulatory
What are the common accepted approaches??
Concept appears simple!
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Key Questions for Successful Biomarker Assay Development
Crystal City Report Bioanalysis 2016(8)
What is the purpose of the study?
Are we measuring what we intended to measure?
What is the anticipated modulation?
How much variability is acceptable?
How does sample handling conditions impact analytical procedures and conditions?
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Focus on Ligand Binding Assays, Principles Apply to Other Formats
Method Development and Validation - Fit for Purpose Approach
§ Matrix§ Reference Standards§ Sensitivity§ Reproducibility§ Specificity/Parallelism§ Robustness§ Stability
Sample Analysis
Assay Maintenance
Core Challenges in Biomarker Measurement
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Matrix
PROBLEMS POSSIBLE SOLUTIONS
• Commercial kits supply diluents as a surrogate matrix - do not reflect the complex biological matrix
• Calibration matrix must be devoid of target analyte
• Must demonstrate analytical equivalency between surrogate and control matrices (e.g. during parallelism)
• Must account for influence of binding partners
• Requires additional QCs and stability assessment
• Use pooled plasma/serum from healthy volunteers
• Assess background levels of analyte
• Consider possible assay interference from biological metabolites
• Consider assay format based on relevant matrix
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Case Study: Matrix is Important Consideration!
IL-17A Assay
§ Ultra sensitive measurements are required for circulating cytokine concentration
§ Cytokine profiles are altered in disease tissue§ Matched set of samples collected from Psoriatic
patients
§ Serum, Lesional tissue and Non-Lesional tissue
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Serum vs Tissue
Donor
PASI Serum (pg/mL) Skin biopsy (pg/mL)
Score IL17A IL17A normal IL17A lesion
101 26.0 0.210 nd 179
102 21.6 0.114 nd 3.70
103 23.9 0.267 nd nd
104 24.3 0.266 nd 3.50
105 23.9 1.93 nd 59.7
Serum analysis requires ultrasensitive assay• IL17A LLOQ <0.05ng/mL
Skin biopsy could have been tested using one of the many commercial assay (MSD, R/D assay)nd=not detected
Consider Assay Format Based on the Matrix!PASI=Psoriasis activity and severity index
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Reference Standards
PROBLEMS SOLUTIONS
• No consistency between commercial standards even when calibrated to WHO/NIBSC standards
• Variation in reagent production creating discrepancies in quantification between different kits
• Incomplete characterization• Available standards do not always
depict circulating form• Biology not well understood
• Use the same sourced standards • Perform batch-to-batch
comparisons to ensure consistency between own results
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Biomarker Stability
• Clinical biomarker sample analysis doesn’t occur real time except for point of care devices
• Problem: Altered amount of analyte in matrix during sample collection, short term and long term storage
• Problem: Altered immunoreactivity in a matrix • Problem: Reference material spikes are often used for
biomarker stability, quite often not indicative of endogenous markers
• Solution: Incurred samples may provide better understanding of analyte stability
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Biomarker Stability – Case Studies
TGF-β1 Stability
§ Spiked TGF- β1 into buffer and pooled urine samples§ Also fresh frozen diabetic urine samples
IL-13 Stability
§ Established using incurred samples from ongoing clinical studies
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TGF- β1 Stability
Stabilitysamples Sampleconcentrationvalues
Sample1 Sample2 Sample3
Replicate1 Replicate2 Replicate1 Replicate2 Replicate1 Replicate2
PurifiedTGF-β1spikesinbuffer
Prefreeze–thaw 108 108 251 340 981 937
Postfreeze–thaw 119 94 257 296 966 1021
%recovery† 110 87 102 87 98 109
PurifiedTGF-β1spikesinurine
Prefreeze–thaw 133 119 124 1260 1280 1250
Postfreeze–thaw 93 78 76 921‡ 871‡ 892‡
%recovery 30 34 39 27 32 29
Diabeticurinesamples
Prefreeze–thaw 151 172 196 147 51 282§
Postfreeze–thaw 8 70 7 141 19 15
%recovery 5 41 4 96 37 5
Use Individual or Pooled Clinical Samples for Stability Testing
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IL-13spikedsamplestability.QCconcentration
(pg/ml)%recoverymonth4
%recoverymonth5
20.3 112 571.1 94 379
% recovery: (concentration at time/initial concentration) × 100.
Unanticipated loss of stability at 5 months
IL-13 Stability (1/2)
IL-13 stability was established using serum spiked reference material
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IL-13 Stability (2/2)
Sample Initial concentration (pg/ml)
Reassay concentration
(pg/ml)
% difference from original
conc.
Months in storage
1 7.5 0.3 183 9
2 0.3 0.3 -1.7 8
3 0.5 0.4 26.7 14
4 5.8 0.4 175 9
5 0.4 0.4 23 14
6 0.8 0.8 0.91 15
7 0.9 0.7 29 8
8 0.9 0.9 -2.02 15
6 of 8 met ± 30% criteria
Stability extendedto 15 months
Samples were stored beyond established stabilityIncurred samples were tested to confirm validated QC sample stability
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Cross-reactivity
Cross-talk
MRD, Selectivity
Failed analyte(s)
VALIDATION
• Test with “missing man” technique
• Test with single analyte if possible
• Use highest MRD based on parallelism, reproducibility results• Confirm final conditions for all analytes• Test early on, prior to pre-validation/validation experiments
• Consider alternatives pre-validation• Rerun and evaluate failed analyte(s) data only
METHOD
Multiplex Method Validation
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Samples that are most relevant to the intended clinical application based on biology
Adequate attention in specimen handling
Adequate attention for specimen integrity
§ Shared samples for various analyte § Shipping challenges§ Sample collection and processing§ Storage conditions
Range of samples/time points
Attention to Pre-analytical Factors
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Data handling (work list preparation, data management, assay approval, data reporting)
All pass – if you must rerun one analyte, what do you do with data for other passing analytes from
1st run?
Identical curve fitting
Lack of regulatory performance recommendations
VALIDATION
• Possible use of macros, built in templates• Contract IT resources• Work with instrument/software vendors to assist with solutions
• Report data for analytes that pass, repeat run for analytes that do not pass (2nd run should mask results for passing analytes). Analyte that does not meet sample analysis acceptance criteria (if repeat analysis fails) should not be included in final analysis.
• Use best fit approach• It is acceptable to use different curve fits/weighting for different
analytes, however, for a single analyte continue using same curve fitting after validation
• Utilize regulatory requirements that most closely meet the study requirements
• FDA Draft Guidance on Bioanalytical Method Validation includes a discussion on biomarkers
METHOD
Data Analysis in Regulated Environment - Multiplex
Recommendations for Use and Fit-for-Purpose Validation of Biomarker Multiplex Ligand Binding Assays in Drug Development. The AAPS Journal (# 2015) DOI: 10.1208/s12248-015-9820-y
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Assay Maintenance
Recommendations for Use and Fit-for-Purpose Validation of Biomarker Multiplex Ligand Binding Assays in Drug Development. The AAPS Journal (# 2015) DOI: 10.1208/s12248-015-9820-y
Variability in reagent lots
§ Implement a defined process to investigate lot-to-lot variability
§ Apply a correction factor
§ Screen multiple lots§ Acquire sufficient volumes of an original lot with expiration dating that
allows completion of the programAvailability of critical reagents
§ Use surrogate molecules, if needed§ Initiate an analyte/antibody production program in anticipation starting the
project§ Contact vendors to assist with sourcing
§ Review research literature for possible academic sources
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• Study design and assay methodology determines bioanalytical strategy
• Diverse assays require multidisciplinary team execution
• Bioanalysis is only one piece of the puzzle – consider overall biology
• Biomarker assays are not PK assays
• Use scientific judgement as appropriate
Summary
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ReferencesCritical Path Institute
• Points to consider topics
AAPS NBC 2014, 2015, 2016
• Biomarker themes, topics
Crystal City V 2013
• FDA draft guidance discussion
Crystal City VI 2015
– Biomarker assay discussion
– Lowes, Ackermann 2016
– 2nd Upcoming publication
WRIB 2014, 2015, 2016
– Biomarker assay discussions
Lee et al. 2005, 2006, 2009
• Biomarker assay validation
O’Hara et al. 2012
• Critical Reagents characterization
King et al. 2014
• GBC Harmonization white paper on critical reagents for LBAs
Bower et al. 2014
• Commentary paper on reference standards and reagents in BMV
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Regulations Examples
Ø FDA BMV Guidance, 2001 (US) Ø EMA BMV Guideline, 2011 (EMA)Ø ANVISA BMV Guideline 2012 (Brazil)Ø MHLW BMV Guidelines 2013 + 2014 (Japan)Ø cFDA BMV Guidelines 2015 (China)Ø Coming up: ICH M10 (concept adopted June ‘16)
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Acknowledgement
• Pfizer Colleagues• Many Scientists from organizations………
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• Back-Up slides
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Robustness/Reproducibility
PROBLEMS SOLUTIONS
• ‘Noisy’ background• Different laboratories often
perform with different reagents and equipment
• Assay format e.g. ELISA performance may depend on reagents
• Cross-comparison of different platforms within the same laboratory
• Run healthy volunteer controls • Evaluate extent of biological
variation• Batch-run longitudinal samples per
subject to Minimize effect of biological variation between individuals
• Run the same samples in parallel in different laboratories/different platforms to assess comparability
• Often, quantitative differences are found but longitudinal trends are comparable
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Specificity
PROBLEMS SOLUTIONS
• Surrogate peptides not uniquely specific
• Methods are not always selective due to matrix complexity
• Antibody used be specific
• Test antibodies from various vendors and various lots
• Consider replacing format
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• Intended application of biomarkers dictates the rigor of biomarker assay validation for clinical studies
• Limited validation in exploratory and proof-of-concept biomarkers• Extensive full validation for biomarkers which provide pivotal data for critical
decision making in the drug development process, as part of regulatory requirement
Validation of biomarkers for clinical studies - Fit for purpose approach
Rigor of Validation
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