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COMPANY CONFIDENTIAL

Biomarker-Driven Trials: How Laboratory Insight Can Enhance

Clinical Trial Design and Optimize Drug Development

Kathleen Gray, PhD

Scientific Advisor

Outsourcing in Clinical Trials New England | September 16, 2015

2 COMPANY CONFIDENTIAL

• Review current trends and challenges in biomarker-driven

drug development

• Discuss how your laboratory partner can provide support for

successful trial execution from early to late-phase

• Review key case studies demonstrating the benefits

provided through pharma/laboratory collaboration

Objectives

Company Confidential


• Biomarkers are already embedded

in our language and medical care

today

• Now taking center-stage due to the

convergence of several factors:

– Proliferation of basic research

– Increasing interest in translational

research, i.e. clinical relevance

– Innovations in science and technology

• The Result: Incorporation of

biomarkers as critical components of

clinical trials

– Endpoints

– Inclusion/Exclusion

– Exploratory/Research

Biomarkers: The ‘New’ Frontier of Drug Development Established medical tools with expanding and evolving clinical significance

500+

>85 CDx on market

Clinically-relevant biomarkers

Source: Personalized Medicine- The Path Forward,

McKinsey & Company 2013


Use of Biomarkers in Clinical Trials Applying evaluable and measurable biological characteristics to guide drug development

Markers of Efficacy, Toxicity or Resistance

Diagnostic*

Indicates the presence or absence of pathogenic process

Prognostic*

Indicates future clinical course in the absence of a therapeutic intervention

Predictive*

Identifies patients who are susceptible to a particular drug effect (benefit, harm)

Pharmacodynamic*

Reveals existence or magnitude of biological response post therapeutic intervention

Surrogate An accepted

indicator of future

clinical outcome

Non-surrogate

Not a currently accepted indicator of future clinical outcome

Unrelated to Therapeutic Response Related to Therapeutic Response

*Classification may depend upon context of use


Patients with the same diagnosis Patients likely to have adverse event or poor clinical response

Patients likely to have a favorable clinical response

Right patient, Right drug, Right dose

The Promise of Personalized/Precision Medicine


Biomarker enrichment

– Enrollment is restricted to marker-positive patients; marker-

negative is not studied

Biomarker stratification

– All patients are enrolled and treatment effect is

examined in overall population versus marker-positive

Umbrella

– Multiple drugs, single tumor type or histology, multiple biomarkers

Basket or Bucket

– Single drug, multiple tumor types but with shared biomarker

Adaptive

– 2+ stages with interim data analyses

• Marker-positive and marker-negative included before interim analysis

• Enrichment or stratification criteria may be modified following interim analysis to

increase probability of success

Biomarker-Driven Trials Innovative clinical trial designs prioritize biomarkers as tools for target patient ID


Source: Measuring Complexity: The Intelligent Clinical Trial, Forbes, 11/20/2014

http://www.forbes.com/sites/medidata/2014/11/20/measuring-complexity-the-intelligent-clinical-trial/

Implications of Biomarker-Driven Trials Integrating biomarkers increases overall study ‘burden’ from site perspective


Innovative trial designs often result in additional operational complexity

• Phase-2 randomized studies

• Adaptive study designs

involving surrogate end points

• Prospective biomarker based

patient selection strategies

Source: Getz KA. Improving protocol design feasibility to drive drug development economics and performance.

International Journal of Environmental Research and Public Health. 2014;11(5):5069-5080.

Design Characteristics

(All values are Means)

2002 2012

Total number of endpoints 7 13

Total number of procedures 106 167

Total number of eligibility criteria 31 50

Total number of countries 11 34

Total number of investigator sites 124 196

Total number of patient randomized 729 597

More endpoints

More procedures

More patients

Increased

Complexity

Biomarkers Also Influence Clinical Protocol Execution


Collaboration is Key to Reducing Complexity Companion diagnostics approvals demonstrate value of alliances for biomarker execution

US FDA-approved companion

diagnostic drugs (2012) $26

$38 $40

Xalkori Iressa TarcevaDeve

lop

me

nt

Co

st

($M

)

Clinical Trial Development Costs

960 2850 3110

Xalkori Iressa Tarceva

En

roll

ed

P

ati

en

ts Total Clinical Trial Enrollment

1.8 7.0 5.3

Xalkori Iressa TarcevaDe

ve

lop

me

nt

Tim

eli

ne (

Y) Phase I Initiation to NDA

Source: Adis, ClinicalTrials.gov, RedBook, Quintiles Analysis; * Xalkori 2011/2012, Iressa 2003/2005, Tarceva 2004/2012

Source: Pharmgenomics Pers Med. 2015; 8: 99–110

Pharma IVD Companion

Diagnostic


• Once a biomarker of interest is identified, the strategy for translation to clinical

sample testing is critical

From Biomarker ID to implementation Key factors to consider when incorporating a biomarker strategy into a clinical trial

Sample Readout

Feasibility

Assay and Method Development

Operational Execution

Early engagement or

collaboration with laboratory can

help align and smooth transition

between study phases


• CROs/laboratories provide access

to a diverse network of clinicians

and scientists

– MDs, PhDs, MTs, HTs

– Bioinformaticists, geneticists, flow

cytometrists, mass spectrometrists,

microbiologists, virologists,

immunologists, anatomic

pathologists, cytopathologists,

hematopathologists

– Regulatory experts,

bioanalytical/medical writers,

physicians

• Clinical trial perspective for

biomarker delivery

The Advantages of Laboratory Collaboration Engaging laboratory resources and expertise to complement Rx efforts

Diagnostics

Biomarkers

Clinical/Med

Lab

Operations

Insights to optimize

protocol design and

execution

Biomarker/

Drug R&D

Protocol

Development

Laboratory

Expertise

Pharma

Expertise


Bringing Biomarkers From Concept to Execution Develop a fit-for-purpose testing strategy based on knowledge and experience

Feasibility

Test

Methodology

and Platform

Operational

Aspects

• Analyte stability

• Sample matrix

• Data analysis and interpretation

• Sample volume/input requirements

• Analytical parameters

• Throughput and scalability

• Potential CDx path?

• Required level of analytical

validation

• Reagent availability and

usage

• Regulatory

• Cost

• Pre-Analytics

• Kit supply

• Development timelines

• Turnaround times

• Testing location

• Management of reporting

and query resolution

• Sample logistics and

storage

• Data entry and transfer


Clinical Protocol Versus Real-World Laboratories can help mitigate risk and implement proactive, experience-based solutions

Mutation

Assay FFPE Tissue Result

What can be addressed upfront to confirm end goal will be met?

What be done to help sites?

Which lessons/best practices can be applied?

Protocol:

Live Study:

US RUO

EU CE-IVD

Assay 1

Patient Eligible/

Non-Eligible

Assay 2

China?

Mutation X

Mutation Z

Mutation Y

Wild-type=?

Mutation X

Turnaround time

Report

mutations?

Detected/ND?

Block return?

Re-Test?


The nature of the biomarker and its purpose for the individual study shapes the

laboratory analytical support plan

Aligning the Laboratory Strategy With the Study Needs

Biomarker Class Implications Considerations

Safety Rapid TAT,

reference ranges,

flags/alerts

Regional testing

(harmonization),

reflexes, standards

Prognostic Consistency with

Dx lab, on-study

monitoring

Centralization,

clinical standards

Predictive Rapid TAT, choice

of Dx assay,

consistency

Regional testing,

technical assay

transfer,

Pharmacodynamic Sample collection

and processing,

data records, assay

Analyte stability,

reference ranges,

technical transfer

Exploratory Method/matrix

selection,

screens/panels,

sample availability

Assay development,

centralization of

testing, sample

stability and storage

?


• Upfront review of protocol considering indication, regional practices, available

methodologies, and regulatory requirements (e.g. IVD, CLIA validation, etc.)

• Sample requirements per test and per patient

• Provision of standardized collection kits and supplies (e.g. slides, formalin,

cassettes)

• Open communication and collaboration to link assay output with data and

reporting requirements

• Site lab manuals and training

Protocol Review, Proactive Trouble-Shooting, and Site Training to Promote Successful Outcome

Cancellation rates 20-30%

(FISH) and 5-10% (IHC)

due to technical reasons

• Delayed enrollment

• Screen fails

Established AP Quality

Management Plan

• Capture metrics

• >5% triggers

investigation, sponsor

notification, and site

re-training

Improvement in cancellation

rates:

• Sponsor 1: 33% to <5%

• Sponsor 2: 19/23% to <5%

Case Study: HER2 FISH and IHC for enrollment

Challenge Solution Outcome


Situation: Pharma requires pathologist expertise and central testing for

large CDx program

Solution:

– Pathologist familiar with drug MOA engaged to score and refine protocols for

6 +indications in collaboration with Rx pathologist and support from Dx

– Global laboratories trained with expanded pathologist team led by lead pathologist

Result: Global assay deployment, cost and time-savings for pharma, central lab

pathologist support for regulatory discussions

Case Study: Pathologist Expertise for IHC CDx Development of scoring methodology for Rx-sponsored study using Dx-provided assay

Protein

Biomarker

Scoring

Development

Lab

Pharma

Global

Deployment

Dx

Pharma

Dx

Ongoing CDx

Support

Lab

Pharma

Dx

*Q2 Solutions refers to either legacy Quintiles or legacy Quest central laboratories


Case Study: Test Selection for Mitigation of SAE Clinician-guided selection and incorporation of assays for safety-related testing

Situation: Pharma instructed by regulatory agencies to include strategy to monitor

patients in single-indication study for MDS/AML as potential SAE

Solution:

› Laboratory clinician and diagnostics expert engaged to recommend testing solutions

based on medical and scientific knowledge of indication and drug

› Morphology and MDS FISH at screen for all patients; blood sample collected for testing

with NGS-based laboratory-developed diagnostic for patients developing MDS/AML

Result: Protocol modification and subsequent approval; biomarker strategy

implemented for all indications across drug program

Test 1 to

Exclude

Patients w/

Existing

Disease

Test 2 to

Determine

Pre-Existing

Risk of

Disease Tx

FDA

mandate to

address

potential

SAE

Incorporation

of Testing and

Protocol

Approval


• Interest in biomarkers continues to grow

• Novel biomarkers, increased sampling demands, and big data bring new

challenges and opportunities for collaboration

Biomarkers in Clinical Trials: The Road Ahead

Challenge Example Potential Solutions

Sample availability/usage NSCLC rearrangements NGS-based approaches,

multiplexing

Repeat, invasive

procedures

Tissue biopsy, lumbar

puncture

Increased sensitivity

platforms for blood, saliva,

or urine-based detection

Standardization Immunophenotyping,

minimal residual disease

Collaboration with KTLs,

proficiency surveys

Implementation of new

technologies into the

clinical realm

NGS clinical data

interpretation, CLIA assay

validation

Participation in regulatory

discussions, alignment with

Dx companies, exploration

of new technologies in

research setting


Patient Pre-Profiling

Patient Presents- ICF, Patient Enrollment Sample Collection

Genomic Testing

Bioinformatic Analysis

Clinical Annotation and Reporting

Physician-Patient discuss options

Site request just-in-time start-up, ICF signed,

patient enrolled in treatment study

Matching patients to studies based on prospective genomic testing

Genomic testing registry

Genomic testing at

Q2 Solutions Labs

Clinical Report

Site staff activities of treatment

decisions and study initiation

*Q2 Solutions refers to either legacy Quintiles or legacy Quest central laboratories


• Collaboration to implement judicious use of biomarkers for

improved clinical outcomes

• Value of collaborations can grow over time

Conclusion The benefits of pharma and laboratory partnerships

› Standards and best

practices

› Combined expertise and thought leadership

› Expert review of

feasibility and

methods

› Early engagement for

implementation of

new technology

• Drug breakthroughs get to the right patients faster

http://blogs.cdc.gov/genomics/2015/03/02/precision-public/


Thank You and Questions

Company Confidential

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