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No Context, No AssayDemanding Context of Use in a demanding world

EBF Autumn Focus Workshop Biomarker Assay Validation – Bringing Context of Use into practice18-19 September 2019

Lauren Stevenson

Overview

• Introduction: Biomarkers – a Perspective• Context of use simplified• Demanding COU

• Common challenges• Myths & cautionary tales• Taking control

• Some thoughts on being a biomarker scientist

Biomarkers – A Perspective• Biomarker “assays” predate PK assays by thousands of years

• Written record of urine pregnancy test by ancient Egyptians – 1350 BCE• Yet, in 2019, PK assay-centric approaches for biomarker assays persist

• Biomarker assays are not PK assays• PK (drug concentration) assays serve one context of use • Drug concentration in a biological sample is a biomarker of dose administration• PK assays can be viewed as biomarker assays with a specific context of use

• Guidance• Many are looking for single guidance that addresses all biomarker assays• Why? Is this a consequence of PK assay-centric thinking? • What if biomarker guidance preceded PK assay guidance?

Biomarker Guidance

1350 BCE

BIOMARKER ASSAY GUIDANCE

1. BE A SCIENTIST2. EMBRACE FIT-FOR-PURPOSE3. DEMAND CONTEXT OF USE4. NO SPECIFIC RULES5. JUST DO GOOD SCIENCE

BIOMARKERS IN DRUG DEVELOPMENT

DON’T ASK FOR GUIDANCE…

…DO GOOD SCIENCE!

2019

• BEST resource 2016: • The Context of Use (COU) is “A statement that fully and

clearly describes the way the medical product development tool is to be used and the medical product development related purpose of the use”

• Or, more succinctly…• Context of Use = The ‘Purpose’ in Fit-For-Purpose

What exactly, is Context of Use?

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Fit-for-Purpose…

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COU is specific…

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Demand Context of Use

• Blanket mandates from stakeholders unable or unwilling to provide COU• “I want a fully validated assay”

• “Just make the best assay you can”

• Misapplication & Misinterpretation – when COU is ignored• Misapplication of existing assays

• “I have no control over the data after it leaves my lab…” leads to misinterpretation of data

• Organizational barriers• Lack of communication - interdependent line functions are siloed

• ‘Assay’ people seen as technical resource only

• Management is misaligned or unqualified

Easier said than done…Common issues encountered by the Biomarker Scientist

Mythbusting

Combatting blanket mandates from stakeholders:“I want a fully validated assay”

“Just make the best assay”

Without context of use…

Fully validated assay

The best assay

Mythical Creatures

1. Fully validated to detect presence of Biomarker X

1 2 3 4

With Context of Use: Fully validated to….

Actual Palomino horses

2. Fully validated to detect qualitative changes in level of Biomarker X (identify trends)

3. Fully validated to analytically detect ≥2-fold changes in levels of Biomarker X (relative quantification)

4. Fully validated to detect clinically meaningful changes in levels of Biomarker X (clinically qualified)

Demand COU: To ‘fully validate’ your assay

• All biomarker assays should be (fully) validated for their COU, regardless of their application

• ‘Exploratory’ is not a context of use• COU: How will the data be used? Start with a question…

• A standalone ‘full validation’ without COU is simply an analytical characterization, against which proposed contexts would need to be applied

Question COU Assay development & validation

• Without COU, we’re flying blind

Demand COU: To develop the ‘best assay’

How to combat “just develop the best assay possible…”

• Try: No context, no assay!

• Or more diplomatically….“In order to develop the best assay, I need to understand….”

• If all else fails, show them the shoes

The Best Shoe?

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Misapplication of Existing AssayA cautionary tale…

Existing qPCR assay deployed out of context

• Intended COU • Categorical designations (detected vs not detected)

• Misapplied COU • PD marker of treatment effect in Ph1 • Arbitrary criteria set without consulting qualified biomarker scientist

• 0.5 Ct change = PD• No biological variability data collected prior to study

• Results • Population statistics showed decrease in treated vs untreated, BUT….

• Timing of “PD” was biologically implausible • Pbo population showed longitudinal biological variability of 3.0 Ct

Misapplication: Resolution

• Qualified biomarker scientist raised concerns at study report review

• Averted misinformed decision to go to next phase

• Had Go decision been made based on misapplication:

• ~$15M in clinical trial costs + associated time/FTE investment

• Patients subjected to a trial without benefit

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Misinterpretation/Overinterpretation When data go rogue…

“Original” data representation – Biomarker scientist

Discovery phase exploratory researchQuestion: Are levels of targeted biomarker different in HV vs pre-disease and disease state?

COU: Explore levels in cross sectional set of samples and determine if biomarker warrants further exploration

Assay: LBA with EQC inter-assay precision ≤ 25%

Samples: Procured samples from multiple vendors/sites:• HV from single vendor • Disease and pre-symptomatic from multiple

repositories

Healthy

Pre-symptomatic

Disease

0

50

100

150

200

250

pg/mL

N = 42 N = 19 N = 14

Biomarker Scientist: Conclusions

• Additional exploration of biomarker is warranted

• Need to collect information on biological variability

Healthy

Pre-symptomatic

Disease

0

50

100

150

pg/mL

Data representation v2 – Research colleague

P = 0.028

Research scientist conclusion:We have identified a biomarker of Disease X!

Data representation v3 – Project team leader

P = 0.028Project team conclusions:We have identified a biomarker of Disease!We can enroll patients based on levels of Biomarker X

Healthy

Pre-symptomatic

Disease

0

20

40

60

80

100

pg/mL

We have identified levels of Biomarker X that identify pre-symptomatic diseaseWe can accelerate development by enrolling pre-symptomatic patients based on Biomarker X

Biomarker Scientist Response• Additional exploration of biomarker is warranted• Need to collect information on biological variability

• Using the proposed “cut off”…

• 13/42 (31%) HV samples would be incorrectly identified as disease

• Only 7/14 (50%) disease samples would be identified as disease

Healthy

Pre-symptomatic

Disease

0

50

100

150

200

250

pg/mL

N = 42 N = 19 N = 14

Biomarker Scientist Response

• The team is proposing new contexts of use…• To support the proposed new contexts of use: the biomarker would

need to be qualified and an assay validated• Requires regulatory engagement• And a much larger data set• And a better/different assay• And a LOT more time

Impact• Weeks, if not months, of Biomarker Swirl

• Countless meetings, slide decks• Diplomatic education of executive leadership

• Biomarker scientist bashing• “not committed” to the success of the program

• Wasted time & resources

• And, if biomarker scientist is ultimately ignored – more wasted time & resources and patients best interests are not served

Taking Control…via Ownership• We own our personal actions• We develop, validate and own the assays• We generate, and own, the data• We own the resources that develop and validate the assays and

generate the data

Leveraging ownership• Owning personal actions - communication

• Communicate proactively with stakeholders, project teams, cross-functional partners• Offer education via seminars, departmental meetings, etc. • Make cross-functional allies & together build organizational understanding of COU

• Owning the assay• Include COU statements in assay validation and bioanalytical reports• Share summary of the validation and COU with teams

• Owning the data• Align on data analysis plans with biostats• Provide a data summary with conclusions in context• Only share data files through proper channels• No P values!

Leveraging ownership• Owning the resources

• We are the gatekeepers of our resources• If resources are in demand, then work must be prioritized• Demand COU: No context, no resources, no assay • Create a scientific forum to review biomarker plans and allocate resources

• Provides stakeholders insight into resource constraints & potential trade-offs• Ensures requests have been thought through…• Demanding COU helps teams build decision trees, go/no-go criteria• Results in more meaningful biomarker efforts

Final thoughts: on being a biomarker scientist

• Being a successful biomarker assay scientist, means being a Biomarker Scientist

• Biology + COU + analytics• The analytics cannot be done in isolation

• Biomarker Scientist job requirements• Impeccable science• Comfortable being uncomfortable• Deep personal resolve in face of adversity • Dogged over-communication • Build relationships and influence others• Take control through ownership

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If there’s no scientific rationale, it’s not science

Demand Context of Use

Critical thought partners: John Allinson (ILX) Devangi Mehta (ILX) Linda Terry (GSK)