Training Session M1 - Monday April 1, 2019, 7am to 5:30pm

"New Insights in Biomarkers Assays Validation (BAV): From US FDA BMV (2018) Guidance, Revised C-Path (2018) White Paper and CLSI Draft Document H62 to Fit-for Purpose Validation - Case Studies from LBA and Flow Cytometry"

Evolution of BAV strategy based on New US FDA BMV Guidance, Revised C-Path White Paper and CLSI Draft Document H62 versus traditional Lee (2006) Fit-for-Purpose White Paper
New: Providing feedback on December 2018 US FDA draft "Biomarker Qualification: Evidentiary Framework Guidance for Industry and FDA Staff"

(You can click on each blue title below to see details, or simply scroll down to see details)


Part 1: Novel Guidelines & White Papers for BAV
Part 2: Evolving Scientific & Regulatory Challenges and Novel Solutions in BAV
Part 3: Complex Case Studies of BAV
Part 4: Regulatory Perspectives
  • Panel Discussion with the Regulators:

    Address your questions on BAV and interact directly with US FDA, EU EMA, and Japan MHLW


DETAILS of Training Course M-1

Part 1: Novel Guidelines & White Papers for BAV
  • Lesson 1
    Evolution of WRIB Recommendations on LBA BAV based on CoU from 2015 to 2018: Where are we now and what next?
    • How the 2015-2018 White Paper in Bioanalysis Recommendations on Biomarkers have impacted the current industry practice and regulations
      • Fit for purpose BAV parameters
      • Exploratory/Confirmatory Biomarkers
      • BAV upon changing of context of use (CoU) throughout drug development
      • Commercial kits recommendations and home brewed assays
    • Understanding where we started in 2015 and where we are now
      • Progresses based on Industry/Regulators’ experience at WRIB
    • Evolving thinking in BAV from the Global Biomarkers Community with specific focus on the Drug Development Process
    • Key BAV parameters discussed in the 2015-2018 White Papers in Bioanalysis basic performance characteristics of the assay
    • How to address the lack of one single Guideline to cover all types of biomarker assays and their intended uses
      • How BAV strategy can be defined based on published White Paper and recent 2018 FDA BMV Guidance
      • What should be taken into consideration during BAV?
      • Biomarker data used in support of the regulatory submissions
      • Industry best practice expectations on the rigor of assay qualification/validation

  • Lesson 2
    Flow Cytometry Biomarker Assay Validation (BAV) in Drug Development: Can the brand-new CLSI H62 document applied to pharmaceutical BAV?
    • BAV parameters definition based on Flow Cytometry Exceptional degree of functionality
      • Typical validation procedure established
    • Application of Flow Cytometry in a Regulatory Environment
    • The New CLSI H62 Document for the Validation of Methods Preformed by Flow Cytometry
      • Clinical laboratories Standards Institute consensus guideline for flow cytometry assay validation: Can it be applied to Drug Development?
      • Flow Cytometry current standards in the Bioanalytical Lab
    • Collaborative experts’ effort to define BAV for Flow Cytometry application in clinical trials

  • Lesson 3
    Understanding of the Biology of Biomarker for successfully BAV: How is the importance Biology of Biomarkers taken into consideration in the New US FDA BMV Guidance & Revised C-Path White Paper (2018) versus traditional Lee (2006) Fit-for-Purpose White Paper?
    • Challenges in the identification of the correct biomarkers based on biology
      • In depth investigation of the biological variability and impact on the assay
      • Are the 2018 FDA BMV Guidance & C-Path Revised White Paper taking into consideration the issues in biomarkers biological variability?
    • How the Biology of the Biomarkers can impact the BAV by determining
      • Analytical ranges and selection of the acceptance criteria
      • Specificity & selectivity
      • Stability & reproducibility using endogenous QCs
    • Definition of intended use for the data and BAV parameters to be assessed

  • Lesson 4
    How to deal with the Differences between a Bioanalytical Lab (GLP/GCP) for Clinical Trials and a Diagnostic Lab (CLIA): Focus on Conversion of a Clinical Trial Biomarker Assay to a Clinical Diagnostic test in CLIA
    • Clear understanding of Clinical Laboratory Improvement Amendments (CLIA) vs Bioanalysis for Biomarkers
      • When biomarker testing needs to be performed in a Diagnostic Lab (CLIA) vs Bioanalytical Lab?
      • Do CLIA regulations for the biomarker assay apply for patient selection in Drug Development Clinical Trials?
      • Why the Global Bioanalytical Community should be careful in adopting CLIA biomarkers validation regulations rather than developing specific drug development guidelines
    • How to proceed in the conversion of a biomarker assay developed for Drug Development Clinical Trials to a Clinical Diagnostic test in CLIA
      • What are the regulatory requirements?
      • What is the additional work needed for this conversion?
    • Biomarkers Assay Evolution
      • From RUO to GLP to CLIA/LDT to CD
      • Understanding the whole translational medicine process from discovery to end
    • Biomarkers have been measured for in CLIA Lab for decades
      • Is the presence of scientists with strong experience in clinical biomarkers (CLIA) needed in bioanalytical labs?
    • Case studies will be discussed on BAV in different types of Lab


Part 2: Evolving Scientific & Regulatory Challenges and Novel Solutions in BAV
  • Lesson 5
    Progresses in Parallelisms, MRD, and Sensitivity Understandings in LBA BAV: New US FDA BMV Guidance & Revised C-Path White Paper (2018) versus traditional Lee (2006) Fit-for-Purpose White Paper
    • Updates on parallelism for Biomarker assays from recent Guidance and Recommendations
      • Well-established parallelism evaluation in C-Path White Paper
      • Parallelism as a key parameter in BAV
      • Evolution of parallelism understanding vs. the Lee (2006) paper
      • Case studies on how recent Guidance and White Paper recommendations impact on biomarker assay and parallelism assessment
    • Parallelism evaluation and its impact on the determination of BAV parameters such as MRD, and sensitivity
      • How parallelisms can help meet the constant requests for higher sensitivity for biomarker assays allowing the detection of previously undetectable biomarkers
      • Issues around sensitivity when developing and validating biomarker assays
      • Correlation between sensitivity achievable vs FFP BAV achievable
      • Understand the expectations in defining the biomarker assay MRD
      • Case studies on how the MRD is calculated based on Parallelism and sensitivity of the assay
    • What to do if parallelism fails or cannot be assessed?
      • How to create confidence in you assay
      • Method development strategies to improve assay performance

  • Lesson 6
    Choosing the Most Appropriate Quality Control (QC) for LBA BAV: Case studies on the importance of QC to understand the difference between endogenous biomarker and calibrator material stability
    • Endogenous QC determination & application for precision and stability evaluations
      • Evaluation of the differences between spiked QC with recombinant reference standard and endogenous QC
      • Strategies to prepare QC material in bulk to ensure Biomarker assays life cycle management
    • Use of Endogenous QC and ISR evaluation for Biomarker Assays
      • Interpretation of 2018 FDA BMV Guidance vs Industry standards
    • Case studies on the characterization of biomarker assay performance by using Endogenous QC samples

  • Lesson 7
    Flow Cytometry Reproducibility & Stability Evaluations in Biomarker Assay Validation: Minimizing variability by considering best selection of Calibration & Endogenous QC material and defining a core set of commonly used validation experiments to ensure reproducibility
    • Reproducibility evaluation for Flow Cytometry BAV
      • Best practice to demonstrate that the Flow Cytometry assay is reproducible
      • Key experiments from method development to BAV in Drug Development: bioanalytical Labs and clinical/diagnostic Labs
    • Stability evaluation for Flow Cytometry BAV
      • Pros and cons of different approached to demonstrate stability
      • Assessment of specimen stability based on the CoU
      • Stability parameter evaluation during method development and BAV
      • Evaluation of downstream assay requirements, specimen type, collection, and storage
        • Peripheral whole blood, peripheral blood mononuclear cells (PBMC) and tissue specimens
      • Factors to consider establishing stability acceptance criteria
        • Precision and Relative percent change between the fresh specimen and the stored specimen

  • Lesson 8
    LBA Biomarkers Case Studies of Stability & Variability within Sample Collection Times, Matrix and Patient Biology and Background: How are these important factors taken into consideration in the New US FDA BMV Guidance & Revised C-Path White Paper (2018) versus traditional Lee (2006) Fit-for-Purpose White Paper?
    • Impact of biomarker individual variability on assay performance and results inconsistency
      • Intra- & inter-individual variation
      • Healthy vs and Disease population
      • Case studies on factors to be taken into consideration
    • Impact of biomarker pre-analytical variability/stability on assay performance
      • Sample handling and processing
      • How to handle the effect of changes in
        • Pre-analytical factors
        • Sample collection time
        • Biological matrices

  • Lesson 9
    New/Current strategies to Optimize Kit-to-kit & Lot-to-lot variability in LBA & Flow Cytometry BAV: Evolution of strategy based on New US FDA BMV Guidance, Revised C-Path White Paper and CLSI Draft Document H62
    • LBA and Flow Cytometry
      • Kit-to-kit variability
      • Lot-to-lot variability of reagents for assays
      • Cross-reactivity between Calibrators and Antibody reagent
    • Current strategies to optimize Kits the meet BAV requirements according to CoU
      • Implementation of recent Guidance and White Papers
      • In-depth case studies on kits optimization in specific matrix/disease states for LBA and Flow Cytometry
    • What is needed to minimize lot-to-lot variability?
      • How is it determined?
      • Why are different methods giving different results?


Part 3: Complex Case Studies of BAV
  • Lesson 10
    Complex Biomarker Assay Validation in Flow Cytometry for Clinical Diagnostic Implementation
    • Discussion on case studies and lesson learnt for complex validations in Flow Cytometry
    • Challenges to validate a Biomarker Flow Cytometric assay to be used in multicenter clinical trials and meet clinical diagnostic requirements by demonstrating
      • Pre-determined acceptance criteria for healthy and disease population
      • Minimum sample receipt time
      • Maximum sample stability time point
      • Reproducibility
      • Required specificity, sensitivity and assay robustness

  • Lesson 11
    Importance of Flow Cytometry Cellular Biomarkers Assays Validation in Multi-Center Global Clinical Studies
    • Discussion on case studies and lesson learnt for complex validations of Flow Cytometry Biomarkers Assays to demonstrated clinical endpoints
      • Focus on the importance of standardization and harmonization of Flow Cytometry assays for multi-center global clinical studies
      • How to ensure quality of data by ensuring assay robustness and reproducibility
    • Challenge in Flow Cytometry BAV in a global contest
      • Application of a robust FFP Validation protocol for Flow Cytometry assay to support clinical efficacy
      • Strategies with method transfer to clinical site and importance of on-site trainings

  • Lesson 12
    LBA Complex Cases of Biomarker Assays Validation for Free Assays: Lesson Learned
    • Understanding the complexity and the challenges of Free assays for Biomarkers
      • Difficulties in generating robust and reliable data
      • Ex vivo quantification vs actual in vivo amount of free form
      • Multiple sources of perturbation of the equilibrium during bioanalysis
      • Practical considerations for free vs total assessment
        • Lesson learnt and possible solution from actual case studies
    • Advanced strategies to overcome main free assays issues
      • Total/Free Equilibrium shifts due to dilution
      • Recovery across concentration range
      • LBA reagents and assay formats designed to measure free form
      • Optimization of
        • Capturing step
        • Incubation times
        • Sample collection to avoid equilibrium shift
        • Sample process steps and assay conditions that dissociate the bound form







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