workshop 3 exploratory biomarkers...workshop 3 exploratory biomarkers marianne scheel fjording, on...

Workshop 3 Exploratory Biomarkers

Marianne Scheel Fjording, on behalf of the EBF

11th EBF Open SymposiumRaise the Anchor – Set sail for Science

21-23 November 2018

Exploratory Biomarkers

Workshop arranged by– Uli Kunz, Boehringer-Ingelheim– Joe Stanta, Covance– Anthony Upton, Intertek– Karen Elsby, Alderley Analytical – Richard Hughes, LGC

EBF acknowledges Darshana Jani, Pfizer for the stimulating discussions

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Ø Aim of this workshop

Ø Prepare an assay validation plan (analytical plan) for a biomarker in a clinical programme

Ø Take into action/consideration – Exploratory clinical “research” status of the biomarker– The drug development phase – Intended use / Context of use of data for the biomarker– Risk (patient, regulatory, business)

Background

ØWhat is an exploratory biomarker?

ØBiomarker assay validation categories

ØRegulatory expectations

ØAssay validation parameters

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What is an exploratory Biomarker?

Ø Bridge the results of animal models to clinical expectationØ Are used to understand the Pharmacodynamic or Mechanism of Action of the

drugØ Hypothesis generation Ø Can be used to fill the gaps of uncertainty about disease targets or variability in

drug responseØ Data are not suited to judge on safety and efficacy of the drug

Ø Data are for internal decisions

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No patient risk

Low Regulatory

review

Low to medium Business

risk

Clinical trial –

research status

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ØDo we need to validate the assay at all?– How to ensure reliable results– The sample analysis of the clinical study samples is still according to GCP

o assay validation as a central part of a quality management system (EMA reflection paper)

ØHow to validate– What are the minimum required validation parameters

o Reliable results with regard to the pre-defined context of useo Scientific validation based on the risk taken by the stakeholder

(accept a potential risk not to get the results that you expected!)

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Biomarker Assay validation categories

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Quantitative

Qualitative

Definitive

Relative

Quasi

e.g. LC-MS assays

e.g. LBA for biomarkers

e.g. non-parallel LBA, non-calibrated FACS, enzyme activity

e.g. IHC, immunogenicity; pos/neg

Lee et al. Pharm Res. (2006); 23(2):312-28 Fit for purpose paper

10Cummings J et al, Br J Pharmacology, 153, 646-656. 2008

Regulatory Expectations

Take home messages from Crystal City VIConsensus

ØCategory 1 = Exploratory Biomarkers– Internal decision making– Understanding of PD or MoA of the drug compound

ØCategory 2 = Confirmatory Biomarkers– Biomarker to support pivotal decisions & label claim– It is critical to ensure the integrity of the data by high level in assay

validation

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Common elements of Validation parametersØReagentsØReference MaterialØRobustness – change of

reagentsØSpecificity – use data from

kit?

ØSample handling– Collection Matrix– Processing– Storage

ØDocumentation

ØCalibration curve MatrixØPrecision ØAccuracy (relatively)ØTarget rangeØAssay range

(dynamic range LLOQ-ULOQ)ØSensitivity ØSelectivity / Matrix effectØParallelismØDilution LinearityØStability

– Samples; Freeze-thaw, Long-term & Short-term

– Reagent + Ref Mat12

Common elements of Validation parametersØReagentsØReference MaterialØRobustness – change of

reagentsØSpecificity – use data from

kit?

ØSample handling– Collection Matrix– Processing– Storage

ØDocumentation

ØCalibration curve MatrixØPrecision ØAccuracy (relatively)ØTarget rangeØAssay range

(dynamic range LLOQ-ULOQ)ØSensitivity ØSelectivity / Matrix effectØParallelismØDilution LinearityØStability

– Samples; Freeze-thaw, Long-term & Short-term

– Reagent + Ref Mat13

Validation parameters – also to be considered

Ø QC preparation 1. Assign a nominal value using the endogenous level; what if

the endogenous level is high2. Spiked samples; how to prepare low QC when endogenous

levels are high?3. Matrix

Ø Number of validation runs

Ø Acceptance criteria

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As a starting point……

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But also be aware that Biomarker validation is not a tick-box exercise

This Workshop – 3 Case Studies

1. TNF-alpha– ELISA

2. 7-keto-Cholesterol – LC/MS

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This Workshop – 3 Case Studies

3. Caspase 7/9 activity– Enzyme activity assay

Ø Challenges– STD and QCs preparation – Normalisation ?

Ø Robustness of the method

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What now?

Ø Three rooms outside the auditorium – LBA– LC/MS– Enzyme activity

Ø Discuss for 30 min– What would you suggest as minimum validation parameter for this

exploratory biomarker? – What will you add-on if the biomarker move to confirmatory biomarker?

Ø Feedback in plenum (45 min)

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Case Study – Questions to be discussed

1. What would you suggest as minimum assay validation parameters to include in the experiments for this exploratory biomarker?

2. Is it necessary to repeat experiments that have already been performed during method development?

3. Would you test specificity or just refer to kit manual?4. Which is the minimum stability information necessary in order to enter the first

study?5. Is long term stability necessary for explorative BM with acceptable proven stress

condition stability at RT or 37�C?6. What are the basic method acceptance criteria for the various validation

parameter? Are they necessary at all?

7. How would you set the in-study run acceptance criteria?19

Ø Get started J

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Feedback session

ØHow did you approach the case study

ØValidation samples

ØAssay Validation Parameters

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Case Study 1 - ELISA

1. Definition of Critical reagents2. What would you suggest as basic assay validation parameters to include in the

experiments for this exploratory biomarker?3. Is it necessary to repeat experiments that have already been performed during

method development?4. Would you test specificity or just refer to kit manual?5. Which is the minimum stability information necessary in order to enter the first

study?6. Is long term stability necessary for explorative BM with acceptable proven

stress condition stability at RT or 37�C?7. What are the basic method acceptance criteria for the various validation



Case study 2 - LC/MS

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1. Definition of Critical reagents - IS?2. What would you suggest as basic assay validation

parameters to include in the experiments for this exploratory biomarker?1. Is it necessary to repeat experiments that have already been performed during





6. How would you set the in-study run acceptance criteria?

Case study 3 - Enzyme activity1. Which reagents would you consider as critical reagents of the assay?2. Would you prepare surrogate calibration samples from the recombinant Caspase-3 as additional

validation samples just to control the dynamic range of the assay/luminometer during the validation runs?

3. How would you use the reference sample for normalization of the response values? Would you use it as a QC sample or more like a calibration sample? would you use an absolute value or a ratio?

4. Definition of LOD as a ‘cut-off value’ 5. What kind of validation samples would you prepare? (check more than one if applicable)

a. human serum from healthy volunteersb. spiked with recombinant enzymec. disease matrixd. dilution of the pooled matrix (with an established value)

a. healthy b. disease

e. samples containing Caspase (enzyme) inhibitor6. How do you define the LOD of the assay (lowest normalised response value that can be distinguished

from blank), and ULOD (highest normalised response value that is not “above dynamic range” ) of the assay?

7. Are the LOD and ULOD samples necessary or would you prefer fixed response values for LOD and ULOD?

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Case study 3 - Enzyme activity

1. Definition of Critical reagents2. What would you suggest as basic assay validation parameters to include in the

experiments for this exploratory biomarker?3. Is it necessary to repeat experiments that have already been performed during






Thank you and questions

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EBF symposium – Biomarker Workshop - Case study 1

Using a commercial Ligand Binding assay to determine the relative concentration of exploratory Biomarker TNF-a

Clinical Protocol Synopsis

Title of Study: A Randomized, Double-Blind, Phase 2 Study toDemonstrate Efficacy and Safety of Drug X Compared to Drug Y

in Patients with Active Rheumatoid ArthritisStudy Period: 1 year Clinical Phase: Phase 2

Study design: Randomized, double-blind, multicenter, multiple dose, intravenous (IV) infusion, parallel-group, efficacy, pharmacokinetic, pharmacodynamic, and safety study.Primary Objective:The primary objective of this study is to demonstrate that Drug X is equivalent to Drug Y in terms of safety and efficacy as determined by clinical response.Secondary Objectives:The secondary objectives of this study are to evaluate long-term efficacy, pharmacokinetics, and pharmacodynamics of Drug X in comparison with Drug Y reference product.Pharmacodynamic analysis on the serum concentration of rheumatoid factor (RF) throughout the study duration.Exploratory Objectives:Exploratory analysis will be performed on the serum concentration of tumor necrosis factor alpha (TNF-a) throughout the study duration.

Subject Population: The study population will consist of adult male and female subjects with active rheumatoid arthritis (RA) who meet all of the inclusion criteria and none of the exclusion criteria upon study entry.

Sample Size: Approximately 50 male and female patients with active rheumatoid arthritis (RA) will be enrolled in a 1:1 ratio (approximately 25 patients per treatment group).

Clinical Protocol SynopsisFlow chart

Stage Screening Treatment EOSWeek 0 2 6 14 22 38 54Day -14 to -7 0 14 42 98 154 266 378Informed consent,Medical History &Screening tests

X

Treatment Drug X and Drug Y

X X X

Pharmacokinetic X X X X X X XPharmacodynamic Biomarker(RF)

X X X X X X X

Immunogenicity X X X X XExploratoryBiomarker(TNF-a)1_

X X X X

Translation into bioanalytical strategy

Scenario 1The level of an exploratory circulating biomarkerTNF-a has been requested for analysis in support ofa Clinical Study. It is expected that the level of thecirculating biomarker will be reduced in the patientpopulation following drug treatment. The change inthe circulatory biomarker is expected to be smalland different baseline levels are expected for eachpatient.

The data will be used for internal informationonly.

What are the minimum validation assessments and associated validation criteria that you would apply to this exploratory biomarker?

Scenario 2The data will be used for modelling against PK and PD endpoints.

What additional validation assessments and associated validation criteria compared to scenario 1 would you apply to this exploratory biomarker?

Validation samples

1. What kind of validation samples would you prepare?– E.g. healthy volunteer or diseased state serum,– Serum spiked with recombinant TNF α (high response)– Buffer with recombinant TNF α– different dilution(s) of the pooled matrix (low response)– Something else?

2. How many levels of validation samples would you prepare?

3. What would you choose as technical run acceptance criteria (similar to calibration curve criteria in quantitative assays)?

Validation experiments

4. What would you suggest as the minimum assay validation parameters for this exploratory biomarker?

5. Would you test specificity or just refer to the kit manual?– How much of the manufacturer’s data would you rely on?

6. Which is the minimum sample stability information required to go into the study?7. What are the basic method acceptance criteria for the various validation parameter?

Are they necessary at all?8. How would you set the in-study run acceptance criteria?9. What are the basic method acceptance criteria for the various validation parameter?

Are they necessary at all?10. How would you set the in-study run acceptance criteria?

Validation Parameter 1st Case StudyCirculating TNF-Alpha (exploratory)

2nd Case Study(TNF-Alpha for PK/PD Modelling)

Intra-Assay Precision and Accuracy

Required?Number of replicates/levels?e.g. 6 reps , low mid and highSample type?e.g. Incurred, spiked QC, matrix, buffer

Acceptance criteria for precision?Acceptance criteria for accuracy?

Inter-Assay Accuracy and Precision

Required?Number of runs/replicates per run?e.g. 6 reps, 2 runs, low mid & high

Sample type?e.g. Incurred, spiked QC, matrix, bufferAcceptance criteria for precision?Acceptance criteria for accuracy?

Sensitivity (LLOQ/LOD)

Required?Use kit data/bottom std?Number of replicates/runs?e.g. 6 replicates, one runSample type?e.g buffer or matrixLLOQ or LOD?

Acceptance criteria for accuracy and precision?e.g. 25% precision/accuracy

Selectivity

Required?How performed?e.g. how many individuals, hemolysed/lipemic? Spike level?

Parallelism

Required?

How many individual subjects/dilutions?e.g. 3 subjects, 4 dilutions

ProzoneInvestigation Required?

Sample stability

Required?

Number of replicates/how many levels?e.g. 3 levels, 3 replicates

Sample type?e.g. incurred or spiked QCs

Specificity Required?How perform or use kit supplied data?

Dilution linearity

Required?e.g. Only if parallelism not performedNumber of replicates/dilutions tested?e.g. 2 individuals, 3 dilutions

Assay range From LLOQ to ULOQ or extrapolation allowed?

ISR

Required?

What % of samples, acceptance criteria?e.g. 2/3 within 30%

Sample Analysis

QC Acceptance criteria?e.g. Constant or adaptable according to assay validation performance?4/6/20 (30)?

EBF symposium – Biomarker Workshop – Case study 2

Definitive quantitative biomarker assay: 7-Keto-Cholesterol

Assay RequestObjective Definitive quantitative biomarker assay for 7-Keto-Cholesterol

(7KC)

Indication Niemann-Pick type C (NP-C) disease which is a rare, progressively fatal neurodegenerative disease

Biomarker qualification Exploratory, use for internal hypothesis testing

Biomarker category Pharmacodynamic, indirect target engagementDrug mode of action Alcaclotide is a small molecule drug and is believed to function by

stimulating a normal cellular protein repair pathway through the activation of molecular chaperones. Since damaged proteins, called aggregates, are thought to play a role in many diseases, it could treat a broad range of diseases.Alcaclotide activates the heat shock response and is believed to act at Hsp70.

Assay Request

Objective Definitive quantitative biomarker assay for 7-Keto-Cholesterol (7KC)

Data evaluation Absolut concentration of 7KC as an indication of disease progression and treatment efficacy

Expected treatment effect Decrease of 7KC to normal population levels

Use for Study in Patients Diagnosed With NiemannPick Disease Type C (age 2 – 18)

Translation into bioanalytical strategy

Ø LC-MS/MS based assayØ Previously described in literature

Literature reviewLC-MS/MS based assay and reference intervals in children and adolescents for oxysterols elevated in Niemann–Pick diseasesJiang et al. 2011

Jiang et al. 2011Klinke et al. 2015

7KC plasma concentrations in human

Assay strategy

Ø Commercially available reference standards– 7-Keto-Cholesterol– 7-Keto-Cholesterol-D7

Assay approaches:– Biological matrix– Surrogate matrix – Surrogate analyte– Surrogate analyte with analogue IS

Q: Validation samples

Ø Healthy volunteer serum activities can neither cover the whole dynamic range of the assay nor the expected responses of study samples

Ø Validation samples will be aliquoted (maybe later used as QCs too) and stored frozen at about -70�C.

1. What kind of validation samples would you prepare?– E.g. healthy volunteer serum, patient samples (pre-dose?) – Matrix spiked with reference standard (high response)– Matrix spiked with Deuterated 7KC– Surrogate matrix with reference standards – Different dilution of the pooled matrix (low response)– Something else?

Q: Validation experiments

2. What would you suggest as minimum assay validation parameters for this biomarker?

Common elements of Validation parameters

Ø ReagentsØ Reference MaterialØ Robustness – change of

reagentsØ Specificity – use data from kit?

Ø Sample handling– Collection Matrix– Processing– Storage

Ø Documentation

Ø Calibration curve MatrixØ Precision

with-in, between run, between operatorsØ Accuracy (relatively)Ø Target rangeØ Assay range

(dynamic range LLOQ-ULOQ)

Ø Sensitivity Ø Selectivity / Matrix effect / Recovery

(extraction)Ø ParallelismØ Dilution LinearityØ Stability

– Samples; Freeze-thaw, Long-term & Short-term– Reagent + Ref Mat

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Validation parameters – also to be considered

Ø QC preparation 1. Assign a nominal value using the endogenous level; what if the

endogenous level is high2. Spiked samples; how to prepare low QC when endogenous

levels are high?3. Matrix

Ø Number of validation runs

Ø Acceptance criteria

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Q: Sample analysis

3. What would you choose as technical run acceptance criteria?– Relative deviation of back calculated values for calibration samples, spiked

QC, endogenous QC – CV of replicates – Curve fit – Else?

4. Which is the minimum stability information necessary to go into the first study?

5. Would you include Parallelism?

EBF symposium – Biomarker Workshop - Case study 3

Quasi-quantitative Caspase 7/9 enzyme activity assay

Assay RequestObjective Quasi-quantitative enzyme activity assay for measurement of

Caspase7/9 in human serum samplesIndication OncologyBiomarker qualification Exploratory, use for internal hypothesis testing

Biomarker category Pharmacodynamic, indirect target engagementDrug mode of action induce apoptosis leading to Caspase activation and subsequent cell

deathData evaluation % change from baseline of total serum enzyme activity post

treatmentAmount of Caspase protein keeps constant during treatment

Expected treatment effect Increase by 200 – 1000% compared to baseline

Use for Single and multiple rising dose phase I studies

Translation into bioanalytical strategyØ Measurement of total serum enzyme glow

response after fixed time of substrate reaction (not the slope of response increase)

Ø Commercial reagent kit available:Caspase-Glo® 3/7 Buffer Caspase-Glo® 3/7 Substrate

Ø Serum samples are diluted in Caspase-Glo3/7 assay buffer to 15% and mixed 1 : 1 with Caspase-Glo 3/7 assay substrate, for 90 min at 30�C. Luminescence was measured as response units.

Ø 96-well format

Ø optimal sample dilution is in the lower range of the steep response-dilution curve as an increase is expected during treatment

Quasi-quantitative data evaluation

Normalization ApproachTo control for inter-run variation, luminescence response from samples is normalised to the value obtained with a positive control (= reference, e.g. human serum with endogenous caspase 3/7).

% "# $"%&'"( = 100 ∗ -./012 3240.671.89 3240.:2;2328<2 3240.671.89 3240.

Reagents and „Calibration“ samples

Additional reagents available (preparation of validation samples):

Ø specific caspase 3/7 inhibitor Ac-DEVD-CHO

Ø recombinant human caspase 3 and 7

Ø Drug, receptor blocker that induces enzyme activity increase

No calibration curve but surrogate “calibration” samples may be helpful to

verify the dynamic range of the assay during validation.

Auxiliary samples for linear normalization of response:Ø Blank sample (negative control) for subtracting from all response values:

substrate buffer or pooled inhibited serum

Ø Reference sample (positive control): e.g. Pooled human healthy volunteer

serum, aliquoted, stored frozen at -70�C

Technical run acceptance criteria

1. What would you choose as technical run acceptance criteria (similar tocalibration curve criteria in quantitative assays)?– E.g. CV of response values from replicates

– Mean absolute response values of blank and/or reference sample

– Ratio of both

– Else?

2. How do you define the LOD and ULOD of the assay?E.g. lowest normalized response value that can be distinguished from blank), highest norm. response value that is not “above dynamic range”

3. Are LOD and ULOD samples necessary in each run (in addition to blank and reference samples)?or would you prefer fixed response values for LOD and ULOD (absolute or relative to blank or reference)?

Validation samples

Ø healthy volunteer serum activities can neither cover the whole dynamic range of the assay nor the expected responses of study samples

Ø Validation samples will be aliquoted (maybe later used as QCs too) and stored frozen at about -70�C.

4. What kind of validation samples would you prepare?– E.g. healthy volunteer serum,– Serum spiked with recombinant enzyme (high response)– Buffer with recombinant enzyme (low to high response = dynamic range)– different dilution of the pooled matrix (low response)– serum spiked with Caspase (enzyme) inhibitor (low response)– Something else?

Validation experiments

6. Would you test specificity or just refer to kit manual?7. Which is the minimum stability information necessary to go into the

first study?

5. What would you suggest as minimum assay validation parameters for this exploratory biomarker?

Parameter Experiment Acceptancecriteria?

Precision e.g.: 3 Validation samples with 3 different response levels, 3 determinations on 3 days

Necessary?CV < X% (N=9)?

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