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Overcoming Operational Barriers to Oncology Clinical Trials Execution

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Title: Overcoming Operational Barriers to Oncology Clinical Trials Execution


1
Overcoming Operational Barriers to Oncology
Clinical Trials Execution
  • September 2009
  • Eliav BarrVice President Oncology Clinical
    ResearchMerck Research Laboratories

2
Who am I (So That You Know My Biases)
  • Conflict of Interest
  • I am an employee of Merck Research Laboratories,
    a division of Merck Co., Inc.
  • I own stock in Merck Co., Inc.
  • Current Position
  • For the past 1.5 years, I have managed the
    interface between Mercks Oncology Clinical
    Research and Mercks Clinical Research Operations
    Groups
  • I am not an Oncologist
  • Prior Experience
  • 14 years in Industry, at U of Chicago prior to
    that
  • I have worked in clinical research in Acute
    Cardiovascular Medicine, Primary Care, Vaccines,
    and Oncology
  • I developed and ran the clinical program for
    GARDASIL (quadrivalent HPV vaccine)

3
Setting the Stage
Obligatory Famous Quote We have met the enemy
and he is us. Walt Kelly
  • Heard in the Halls of Merck (and Several Medical
    Centers)
  • But weve always done it that way
  • Well, I believe we do it this way because it is
    a insert one of the following Regulatory,
    HIPAA, Hospital, Technical requirement I
    think.
  • They insert one of the following hospital
    management, Pharma research management, Oncology
    staff will not go for this because they are set
    in their ways, and there is too much change

Speed and Accuracy are Critical I am going to
post the data I have at this point. He has been
on the MK-2206 (AKT pathway inhibitor) trial.
When he started the drug, he had a cough, had
terrible pain, was running temperature, and
sleeping all but 6 hours of the day. His tumors
on last scan were growing rapidly. He is now
cough free, OFF ALL PAIN MEDS and is no longer
running temperature. He is up and about and is
going hunting tomorrow! Patients wife, via Blog
4
Presentation Outline
  • Oncology Differs from Other Therapeutic Areas
    Unique Operational Issues
  • How one Pharma Company has Chosen to Address
    These Issues

5
Presentation Outline
  • Oncology Differs from Other Therapeutic Areas
    Unique Operational Issues
  • Broad Parameters (Timelines/Success Rates)
  • Granular Issues (Operational Nuts and Bolts)
  • How one Pharma Company has Chosen to Address
    These Issues

6
Oncology Clinical Research Accounts for 20 of
all Pharma Clinical Research and This
Proportion is Increasing
Source BioNest Partners Analyses www.bionest.com
7
More Trials Does Not Equal More Success
Productivity in Phase 2 is Declining
Source BioNest Partners Analyses www.bionest.com
8
Oncology Development Timelines are Slower than
for Other Areas
Years from First-in Human to First Filing
Source CMR International
9
Leading Causes of Study Delay in US Clinical
Trials Centers
10
Key Causes of Enrollment Delays US Sites
11
Success Rates Oncology vs. Other Therapeutic
Areas
Source CMR International
12
Presentation Outline
  • Oncology Differs from Other Therapeutic Areas
    Unique Operational Issues
  • Broad Parameters (Timelines/Success Rates)
  • Granular Issues (Operational Nuts and Bolts)
  • How one Pharma Company has Chosen to Address
    These Issues

13
Congestion
Other TAs
Oncology
  • Centralization of care fewer sites to conduct
    studies
  • Sites often in Universities less use of central
    IRBs, more bureaucracy
  • Over 1000 compounds in development
  • Primary care approaches
  • Larger patient population
  • Often arranged for rapid clinical trial execution
  • Need to be able to cut through barriers
  • Need to be flexible, nimble like in no other
    field
  • Need to establish longer-term relationships

14
Complex Clinical Studies Programs
  • Highly fragmented indication spectrum
  • Signal clinical activity, not surrogate
  • Adaptive trials are the rule
  • Rapidly changing field ? nimble clinical plans
  • Narrower indication spectrum
  • Can get signal in Phase 1 using validated
    surrogates (ie, cholesterol, BP, PFTs, etc.)
  • Large Longitudinal Phase 3 studies are the rule
  • Oncology Lung cancer 15 settings
  • Within Lung Cancer SCLC vs. NSCLC
  • If choose NSCLC neoadjuvant, adjuvant, primary
    therapy (depends on stage)
  • If choose Stage 3b/4 NSCLC 1L, 2L, 3L
  • If choose 1L Stage 3b/4 NSCLC separate trials
    for one of 3 different SoC meds
  • Metabolism Type 2 diabetes
  • Variability by background meds, age, severity only
  • High variability/complexity in study designs,
    frequent amendments ? Changes to EDC tools,
    changes to procedure/data manuals, must retrain
    site and Pharma staff
  • Need highly educated Site Merck staff familiar
    with our tools and with each other
  • Need speedy, flexible, intuitive, reliable EDC
    and specimen management tools

15
Types of Schedules of Administration of Medicines
Other Therapeutic Areas
Oncology
  • Medicines often have narrow therapeutic window,
    with frequent toxicities
  • In general, medications are given in cycles to
    allow recovery from toxicities
  • E.g. meds at Day 1 and 15 X 28 day cycle
  • Delay in cycle starts if recovery from toxicity
    is incomplete
  • Often, medications are dosed on a mg/m2 basis and
    may be adjusted each cycle
  • High variability in actual dose given
  • Dosing may vary with prior toxicities
  • In general, meds have large therapeutic index and
    are given chronically
  • Meds administered qD until study end
  • May have discontinuation, but rarely dose changes
  • In general, one dose is used throughout the study
  • Most common alternative protocol-required ramp
    up to a target dose
  • Decrease in dose is less common

? complexity in protocol design, drug supplies,
data collector development, data entry, patient
tracking, summarization
16
Data Management
Other Therapeutic Areas
Oncology
  • High data density and different kinds of data
  • A lot of local laboratory values requires
    significant data entry
  • A long medical chart lots of complications
  • Variability in drug administration
  • Use of unique grading systems and data rules
  • Central labs allows streamlining of data entry
  • Complicated patients typically excluded
  • Once-per-day medication. Titration rare (and if
    present, allowed only at study start)
  • Commonalities in data rules across TAs
  • Need expert data coordinators expert at
    understanding the clinical picture
  • Need to leverage tools used by oncology field to
    improve site compliance
  • Need Familiarity Sites ? Merck, Merck ? Onc
    Standard
  • Need flexible, intuitive tools

17
Adverse Events Reporting
Oncology
Other Therapeutic Areas
  • Oncology patients have frequent serious adverse
    events (due to cancer, due to non-study meds, due
    to study meds)
  • Complex adverse event scenarios
  • CTCAE grading is standard
  • Patient-level review is often needed
  • Serious adverse events are rare
  • Occurrence of cancer is a serious adverse event
  • Assessment of adverse events relatively
    straightforward
  • Patient level review non-standard

AE management systems may need to be tailored for
Oncology Must use experienced investigators and
sites Use CTCAE system as primary tool for AE
collection
age of Pts with 1 SAE
18
Laboratory Management
Other Therapeutic Areas
Oncology
  • High use of local laboratories
  • Need same day results - prior to each round of
    therapy
  • Large number of tests/patient
  • Unique tests
  • Complex readout
  • Research Use Only tests
  • Unique Specimens
  • High use of central laboratories
  • Data entry at sites, rather than a central lab
    feed into database ? more errors, high burden on
    sites (esp. Lab Normal Ranges), high burden to
    Merck (reconciliation)
  • Non-standard forms, high amount of data for each
    test
  • Multiple sources of data multiple vendors with
    complex requirements
  • Lose ability to use central lab data to monitor
    study progress, safety

19
Biomarkers are Critical to the Success of Oncology
Other Therapeutic Areas
Oncology
  • Efficiently define most promising new
    medicines/combinations in Ph 1/2a
  • Improve POS of agents/combinations
  • Rapid read-out instead of expensive, long studies
    measuring clinical response
  • Define responders/non-responders
  • Field demands personalized medicine
  • Improve benefit/risk ratio and value
  • Requires new tumor markers co-developed with new
    targeted medicines
  • Can define activity in Phase 1 based on surrogate
    or registration markers
  • Blood chemistries (e.g. cholesterol)
  • Assays are available and validated
  • Specimens easy to access, easy to measure
  • Relationship to hard endpoints generally defined
  • Personalized medicine not yet on the horizon
  • Seamless research effort of a dedicated team of
    molecular epidemiology, pre-clinical,
    experimental medicine, and clinical research
    personnel
  • Operations group arranged to work together with
    sites and the labs to ensure high quality
    specimen acquisition, handling, and testing

20
How Oncology Compares Against the Ideal Clinical
Trial Setting
21
Presentation Outline
  • Oncology Differs from Other Therapeutic Areas
    Unique Operational Issues
  • How one Pharma Company has Chosen to Address
    These Issues

22
Challenge and Potential Solutions
New Drug AND New BiomarkerThe Right Medicine
for the Right Patient
Biomarker/Biopsy-Rich Phase 0 to 2a Studies
Stronger Collaboration with Sites
Fragmented FieldHow to Optimally Develop our
Drugs?
Collaborative Studies Program
Cycle Times are Long
Streamline Late Phase Trials
Studies are Costly
Solve Data Mgmt Pain Points
Competition Patients, Sites, Staff, Equipment
Oncology Standards
Clinical Trials are ComplexDrug Admin,
Procedures, Specimen Mgmt
Global Footprint
Data Management Tools are ComplexEach Company
is Different
Using Todays ToolsOncology e-Communications
Portal
23
Issue Complexity of Early Clinical Trials
  • Length driven by environmental, competitive,
    process causes
  • Resulting in increased overall Phase 1 to 2a
    timelines

FIH to Ph 2a LPE in Oncology MRL Programs vs.
Pharma Top 25ile
9.5 months
Days
Top 25ile
Merck
24
Solution Deeper Collaboration With Key Sites
  • Choose sites w/strong interest in Mercks Ph 1/2a
    oncology trial designs
  • New designs, complex biomarkers, require
    adaptability
  • Maximize efficiencies through long-term
    relationships
  • Mutual prioritization and commitment (pipeline
    view, not protocol view)
  • Less administrative time, more science time
    (modify internal processes to reduce cycle times)
  • Standardization of protocols, start-up
    procedures, data capture, guidelines
  • Dedicated site resource talking to dedicated MRL
    field staff
  • Sites meeting metrics have access to funds for
    investigator-initiated studies
  • Acknowledge Globalization
  • Asia Pacific growing cancer burden, different
    cancer types
  • Europe high experience, high quality sites,
    annotated tumor banks
  • North America high experience, high quality sites

25
Issue Where to Test our Drugs for
Proof-of-Concept
  • It is important to define the activity (or
    lack-of-activity) of drugs early
  • However, cancer includes multiple settings
  • Different organs
  • Different etiologies
  • Localized vs. Metastatic
  • surgery,
  • radiation
  • Background therapy
  • There are only so many scientists at Merck
  • Can we get help in prioritization?
  • Can we get ideas for study designs, biomarkers,
    settings from the outside?
  • How do we ensure that the advice is right?

26
How to Choose Among Multiple Studies/Indications?
Oncology requires multiple Phase 2a Studies to
Evaluate Different Settings unique among
Therapeutic Areas
CTEP
External Partnerships
  • Core MRL Studies
  • Merck-Sponsored and -run studies
  • Merck-Sponsored and CRO-run studies

Trial Groups
OCSP
Merck-Funded, Site Conducted Early Phase
27
How to Choose Among Multiple Studies/Indications?
Oncology requires multiple Phase 2a Studies to
Evaluate Different Settings unique among
Therapeutic Areas
CTEP
External Partnerships
  • Core MRL Studies
  • Merck-Sponsored and -run studies
  • Merck-Sponsored and CRO-run studies

Trial Groups
OCSP
Merck-Funded, Site Conducted Early Phase
28
Oncology Collaborative Studies Program - OCSP
(Merck) - 1
  • Definition of Oncology Collaborative Studies
    (Merck)
  • Phase 0, 1, 2a studies of Mercks investigational
    compounds sponsored and conducted by a cancer
    center or a consortium of cancer centers
  • For each compound, trials start once Phase 1a
    study achieves PK/PD targets
  • Why Invest in OCSP?
  • Recognition that Merck does not have a monopoly
    on brains and brawn
  • Allows for more creativity in developing our
    novel compounds
  • Allows broader access to novel biomarkers or
    trial approaches
  • Resource sparing (less bureaucracy and personnel
    involvement at Merck)
  • Recognition that site performance varies with
    motivation
  • Better performance if it is the sites idea
  • Better performance if the site is in charge
  • Key Guiding Principles
  • Critical part of Mercks developmental activities
    equal weight to core studies
  • Must be sufficiently robust so that program
    decisions can be made
  • Top notch science
  • Top notch execution (data quality, timelines)

29
Oncology Collaborative Studies Program - OCSP
(Merck) 2Key Operational Principles
  • Only selected sites are eligible
  • Sites that have capacity/track-record for novel
    early phase trials
  • Sites that have entered into a pipeline-based
    longitudinal relationship with Merck and have a
    proven track record of success
  • Sites that have streamlined administrative
    processes and reduce delays
  • Study designed by site, but in collaboration with
    Merck scientists
  • Merck and advisory team (from sites) propose
    areas of interest
  • Sites design study proposals (study capsules with
    justification)
  • Selection of trials based on robustness of
    science, track record, and strategic fit
  • Merck provides study grant, but site/consortium
    is responsible for the study
  • Merck willing to invest in site personnel as part
    of larger collaborative arrangement
  • Site responsible for conduct (IND, protocol
    adherence, data, regulatory matters)
  • Mutual agreement on timelines and format for
    read-out (analysis plan)
  • Merck is updated regularly
  • Site holds database, publishes results, can use
    the data for internal research purposes (per
    agreement)

30
Oncology Collaborative Studies Program - OCSP
(Merck) - 3
  • Examples of OCSPs
  • Ph 2a Study of IGF1R mAb in 1L treatment of
    Pancreatic Cancer (N 100)
  • Phase 2a Study of an investigational compound to
    define responders and provide proof of concept
    (Ovarian Cancer) (N 190)
  • Phase 0 study to compare the activity of
    standard-of-care medications and Mercks
    compounds on markers of cell proliferation and
    survival in a neoadjuvant breast cancer setting
    (N 150)
  • Phase 0 study to validate a new imaging technique
    against response rate and PFS in lung and
    pancreatic cancer (N 100)
  • Size of Program
  • Year over year, investment has increased from 5
    (2006) to 35 (2010) of our Phase 1 to 2a Budget
  • To date, site performance has been excellent,
    consistent with predictions

31
Data Management is Difficult Need Improvements
  • High complexity
  • A lot of data are collected, but how much of the
    data is actually important?
  • Multiple sources of data (local lab, central lab,
    radiology, patient care visits, etc)
  • Lack of standardization
  • Each company has unique EDC system each with
    its strengths and weaknesses
  • Even within a company, studies may vary with
    regard to standard eCRFs
  • Pharma staff may give different answers to the
    same question (!)
  • Manual Entry/Transcription Errors
  • At many sites, staff at site transcribe data from
    one database (EMR) to another database (company
    EDC)
  • High error rates in most common data points
  • Free form text
  • Complex medical history

32
Example Problem eCRFs
Supportive Data
33
How to Solve Data Problems?
  • Top to Bottom Review of eCRFs
  • Are data needed?
  • Are questions clear?
  • Beta-test with study data entry personnel
  • Reliance on Standards for AE Collection
  • Can CTCAE classification system be used to allow
    for pull down menus minimizing free form text?
  • Data Entry and Handling Guidelines are not
    helpful
  • Currently too long, too vague, inconsistent
  • Create FAQ and example modules in a web-based
    tool
  • EMR to EDC
  • Some sites have a robust EMR system
  • Can data be extracted directly to EDC?
  • Complexity validation of transfer (many sites,
    many EMR systems)

34
Global Footprint
  • The US has been a mainstay of innovation/research
    in Oncology however
  • American cancer centers are congested too many
    trials
  • There has been a steady increase in costs and in
    barriers to interaction
  • In most centers, lt20 of patients participate in
    trials
  • Cancer Centers in the European Union/Australia
    are Equally Outstanding
  • Lower costs generally
  • Standardization of care AND standardization of
    medical records facilitate trials
  • BUT are heavily congested, and staffing can be
    difficult
  • Developed East Asian Countries are Highly
    Competitive
  • Korea, Japan, Taiwan, Hong Kong, Singapore have
    great scientists and facilities
  • Korea, Japan, Taiwan require ethnic/national
    inclusion prior to licensure
  • Cost structure is equal to US (Korea, Japan) or
    much lower (others)
  • Emerging Markets are Tomorrows Giants
  • Brazil, Russia, India, China, Turkey all expected
    to grow dramatically
  • Each already has solid research capabilities and
    much lower cost structure
  • Each has unique administrative limitations that
    lengthen cycle times but they are changing to
    accommodate research

35
Emerging Markets Strength and Weakness
36
Communications
  • Old style is inefficient
  • Paper
  • Phone
  • Visits/meetings
  • Sites and Pharma have recognized this, and are
    shifting to web-based approaches
  • Remote monitoring
  • Ability to obtain up-to-date information on
    patients (without calling the site)
  • Sophisticated e-portals
  • Provide protocol information, key documents,
    status reports
  • Request supplies
  • Answer questions at all hours
  • Videos on specimen handling

37
Challenge and Potential Solutions Huge Room for
Improvement in the Years to Come
New Drug AND New BiomarkerThe Right Medicine
for the Right Patient
Biomarker/Biopsy-Rich Phase 0 to 2a Studies
Stronger Collaboration with Sites
Fragmented FieldHow to Optimally Develop our
Drugs?
Collaborative Studies Program
Cycle Times are Long
Streamline Late Phase Trials
Studies are Costly
Solve Data Mgmt Pain Points
Competition Patients, Sites, Staff, Equipment
Oncology Standards
Clinical Trials are ComplexDrug Admin,
Procedures, Specimen Mgmt
Global Footprint
Data Management Tools are ComplexEach Company
is Different
Using Todays ToolsOncology e-Communications
Portal
38
THANK YOU! Eliav_Barr_at_Merck.com 1-267-305-7282
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