Considerations for Successful Biomarker Bioanalysis in Regulated Environment

Transcription

1 Considerations for Successful Biomarker Bioanalysis in Regulated Environment Darshana Jani, M.Sc. 10 th European Bioanalysis Forum November 15,

2 Disclaimer The contents of this presentation reflect the personal opinion of the author and may not represent the official perspectives of the affiliated organization 2

3 Scope Biomarker Basics Core Validation Challenges and Solutions Case Studies Sample Analysis Pre-analytical Factors Data Handling Summary 3

4 What is a Biomarker? "Almost anything you can measure" A characteristic that is objectively measured and evaluated as an indicator of normal biological processes, pathogenic processes, or pharmacological responses to a therapeutic intervention. DIFFERENT TYPES 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). Biomarkers Definitions Working Group (2001) Clin Pharm Ther 69(3):89 R Frank and R Hargreaves (2003) Nature Rev Drug Disc 2:566. 4

5 Biomarker Assay Flow from Research to Clinical Study Research/ Discovery Translational Lab Development Lab Clinical Study Clinical Utility Key activities and deliverables Identification of Biomarkers Generate a reasonable proposal Evaluate 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 feasibilitysample 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 5

6 Concept appears simple! What are the biggest challenges? Scientific Technical Regulatory What are the common accepted approaches?? 6

7 Key Questions for Successful Biomarker Assay Development 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? Crystal City Report Bioanalysis 2016(8) 7

8 Core Challenges in Biomarker Measurement 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 8

9 Matrix PROBLEMS 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 POSSIBLE SOLUTIONS 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 9

10 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 10

11 Serum vs Tissue PASI Serum (pg/ml) Skin biopsy (pg/ml) Donor Score IL17A IL17A normal IL17A lesion nd nd nd nd nd 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 PASI=Psoriasis activity and severity index Consider Assay Format Based on the Matrix! 11

12 Reference Standards PROBLEMS 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 SOLUTIONS Use the same sourced standards Perform batch-to-batch comparisons to ensure consistency between own results 12

13 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 13

14 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 14

15 TGF- β1 Stability Use Individual or Pooled Clinical Samples for Stability Testing Stability samples Sample concentration values Sample 1 Sample 2 Sample 3 Replicate 1 Replicate 2 Replicate 1 Replicate 2 Replicate 1 Replicate 2 Purified TGF-β1 spikes in buffer Prefreeze thaw Postfreeze thaw % recovery Purified TGF-β1 spikes in urine Prefreeze thaw Postfreeze thaw % recovery Diabetic urine samples Prefreeze thaw Postfreeze thaw % recovery

16 IL-13 Stability (1/2) IL-13 stability was established using serum spiked reference material IL-13 spiked sample stability. QC concentration (pg/ml) % recovery month 4 % recovery month Unanticipated loss of stability at 5 months % recovery: (concentration at time/initial concentration)

17 IL-13 Stability (2/2) Samples were stored beyond established stability Incurred samples were tested to confirm validated QC sample stability Sample Initial concentration (pg/ml) Reassay concentration (pg/ml) % difference from original conc. Months in storage of 8 met ± 30% criteria Stability extended to 15 months 17

18 Multiplex Method Validation METHOD Cross-reactivity Test with missing man technique VALIDATION Cross-talk Test with single analyte if possible MRD, Selectivity Use highest MRD based on parallelism, reproducibility results Confirm final conditions for all analytes Test early on, prior to pre-validation/validation experiments Failed analyte(s) Consider alternatives pre-validation Rerun and evaluate failed analyte(s) data only 18

19 Attention to Pre-analytical Factors Samples that are most relevant to the intended clinical application based on biology Range of samples/time points Adequate attention in specimen handling Shared samples for various analyte Shipping challenges Sample collection and processing Storage conditions Adequate attention for specimen integrity 19

20 Data Analysis in Regulated Environment - Multiplex METHOD 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 Recommendations for Use and Fit-for-Purpose Validation of Biomarker Multiplex Ligand Binding Assays in Drug Development. The AAPS Journal (# 2015) DOI: /s y 20

21 Assay Maintenance 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 program Availability 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 Recommendations for Use and Fit-for-Purpose Validation of Biomarker Multiplex Ligand Binding Assays in Drug Development. The AAPS Journal (# 2015) DOI: /s y 21

22 Summary 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 22

23 References Critical 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 nd Upcoming publication WRIB 2014, 2015, 2016 Biomarker assay discussions Lee et al. 2005, 2006, 2009 Biomarker assay validation O Hara et al Critical Reagents characterization King et al GBC Harmonization white paper on critical reagents for LBAs Bower et al Commentary paper on reference standards and reagents in BMV 23

24 Regulations Examples Ø FDA BMV Guidance, 2001 (US) Ø EMA BMV Guideline, 2011 (EMA) Ø ANVISA BMV Guideline 2012 (Brazil) Ø MHLW BMV Guidelines (Japan) Ø cfda BMV Guidelines 2015 (China) Ø Coming up: ICH M10 (concept adopted June 16) 24

25 Acknowledgement Pfizer Colleagues Many Scientists from organizations 25

26 Back-Up slides 26

27 Robustness/Reproducibility PROBLEMS 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 SOLUTIONS 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 27

28 Specificity PROBLEMS SOLUTIONS Surrogate peptides not uniquely specific Methods are not always selective due to matrix complexity Test antibodies from various vendors and various lots Consider replacing format Antibody used be specific 28

29 Rigor of Validation Validation of biomarkers for clinical studies - Fit for purpose approach 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 29