Presentation supporting a talk at the 2nd Annual Oncology Biomarkers Congress in Manchester, UK. Details several of my projects providing information to support effective clinical program design, data interpretation, and biomarker development.
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Information support for decision making. Christopher Hart 2012
1. Decisions, Decisions,
Decisions
Oncology Clinical Development Congress 10 October 2012
Christopher Hart
Clinical Information Management Director, Oncology Clinical
Discovery Team
Information support for
decision making
2. The Current Climate
Christopher Hart | 10 October 20122 Research & Development | Biometrics & Information Science
Iconograph by Reid Parham
3. Making a Meaningful Difference to Patients
Supporting experts in making decisions
•Focusing the efforts of our experts
•Effective use of the most relevant information
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4. Clinical development as an iterative cycle
Design
Execute
Interpret
Decide
Design decisions
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5. Constraints
Scrutiny of R&D can increase quality
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6. - Create program options
from study prototypes
- Assess program options
from an operational and
a likelihood of success
point of view
Creative Process for Program Design
1
23
4
DELIVER
PROGRAM
OPTIONS FOR
OPTIMAL COST,
SPEED &
CERTAINTY
Identify
questions
Identify
potential
measures
Create
study
prototypes
Create
program
options
- Identify what key
questions
need to be answered for
the
next Investment
Decision
- Identify the potential
measures
that could be used to
answer
each clinical question
- Use integrative thinking to
come up with different
study
options that could deliver
each measure (i.e.,
consider study population,
treatment, locations, etc)6 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science
7. Workbench - Key Benefits
CREATIVITY TRANSPARENCY CUSTOMER
INTIMACY
STANDARDISATION
Collaboration
Experts assigned to
address key
uncertainties
Knowledge re-use
Leveraging
knowledge from past
and parallel projects
Integrative thinking
Superior options
synthesized through
multi level design
process
Transparent Decisions
Decisions based on
robust, documented
evaluation of options,
are tied directly to
desired business
outcomes
Track changes and
understand impact
Changes are
visualized and traced,
with impact on related
decisions marked to
ensure consistency
Project Teams
A well defined design
process, along with
best practice, allows
designers to focus on
making expert
decisions
Governance
Access to full thinking
and rationalization
behind proposals
Early input of experts
Ability to capture input
of experts flexibly, at
an early stage
Recyclable process
Ensure that best practice
continues to be evolved,
and uniformly used
Recyclable knowledge
Design thinking becomes
accessible design
knowledge
Standards from the Start
Standardized design will
lead to standard data
capture, reporting, and
data utilization
Christopher Hart | 10 October
2012
7Research & Development | Biometrics & Information Science
8. Building a “Workbench” for Clinical Trial Design
Clinical Claims: How likely are
we to succeed? Where do we
need to be at next investment
decision?
Efficacy Claim Safety Claim
Benefit Questions Risk Questions
Major measure options Minor measure options
Options for Design elements
Assessment Comparator Design Location PopulationTreatment
Benefit/Risk/Value Clinical
questions are created, stated in
a measurable way, aimed for
next investment decision.
…
Study prototype options
Program options
Optimal CostOptimal RobustnessOptimal Speed
Clinical studies
Each Clinical question is broken
down into potential Major and
Minor measures, which are
assessed.
Measures are further worked up
through assessing options for
Design elements.
Prototype studies are pulled
together from Design elements.
Statistical and operational
information is worked up, e.g.
Sample size, Duration, Power,
Cost, Time
Prototype studies are pulled
together to form a program
option optimized for Cost, Speed
and Robustness. Statistical and
operational information is
finalized.
Value Claim
Value Questions
1
2
3
4
5
6
DesignremitDesignProgramoptions
Christopher Hart | 10 October
2012
8Research & Development | Biometrics & Information Science
9. Measures and Design elements
Identify Potential measures
Each Clinical question is broken
down into potential Major and
Minor measures, which are
assessed.
Create options for Design elements
A Major measure is further worked
up through assessing options for
Design elements. Possible Minor
measures are pulled in from the
same or other Clinical questions
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4
Christopher Hart | 10 October
2012
9Research & Development | Biometrics & Information Science
10. Study prototypes and Program options
Create Study prototypes
Prototype studies are pulled
together through combining
Design element options.
Statistical and operational
information is worked up, e.g.
Sample size, Duration, Power,
Cost, Time.
Create Program options
Prototype studies are pulled
together to form a program
option optimized for Cost,
Speed and Robustness.
5
6
Christopher Hart | 10 October
2012
10Research & Development | Biometrics & Information Science
11. Refining and Evaluating Options
Refine
At the very end of the process, the
design team pulls together the
appropriate options to compose Program
options for Cost, Speed and Robustness.
Evaluate
After combining options, Workbench
helps the team evaluate the options. The
team defines important “Success
factors”, e.g. for Location “Regions are
preferred from a Patient prevalence
perspective”.
This captures the strategic thinking of
the team and helps them use creativity to
identify superior options
Christopher Hart | 10 October
2012
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12. Preliminary Design
Clinical support for early projects
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Clinical MeMo
studies
Human tissue
target linkage
Conduct Method &
Model studies
needed to qualify
Proof of Mechanism
and Proof of
Principle
biomarkers for use
in early clinical
studies
Provision of human
tissue for target
linkage throughout
the discovery /
development cycle
Discovery
access to a
clinical voice
An early accessible
& consolidated
clinical voice into
the developability
of target and drug
13. Information Support
Experts supporting experts
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Christopher Hart | 10 October
2012
Research & Development | Biometrics &
Information Science
Chemistry and Patents Current Awareness
News Company Profile
and Pipeline
Information
Competitive Intelligence Literature and Clinical Trials
Literature
and
Chemistry/
Patent Alerts
Key Opinion
Leaders and
Associations
Literature
Linked to
Full-text
articles
Alert System
Aligned to Target
Portfolio
Expertise in Tools
and ResourcesPatent Analysis
Patent Analysis
with STN
Anavist
Chemistry Structure
and Reaction
Searches
IP Research
Landscape
Prior Art Searches
- Before patent filings
- New target evaluation
- For alternative
indications,
collaborations, etc.
Mapping
potential
opportunities
Clinical
Trials
18. Creating Program Options
Defining reasonable duration
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19. Creating Program Options
Defining reasonable duration
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20. Creating Program Options
Comparative safety review
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21. Creating Program Options
Comparative safety review
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22. Clinical development as an iterative cycle
Design
Execute
Interpret
Decide
Decision making during the study
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23. Prompt Data Review
• 21CFR312.32 IND safety reporting
- “(b)Review of safety information . The sponsor must
promptly review all information relevant to the safety of the
drug … including information derived from any clinical …
investigations…
• ICH E6R1
- 4.11.2 Adverse events and/or laboratory abnormalities
identified in the protocol as critical to safety evaluations
should be reported to the sponsor according to the reporting
requirements and within the time periods specified by the
sponsor in the protocol.
A requirement
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24. An Efficient Clinical Trial
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Design
Execute
Interpret
Safety oversight
25. A More Efficient Clinical Trial?
Ongoing review
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Design
Execute
Interpret
Review Prepare
26. Ongoing Review
Operational
• Data entry
lag
• Set up
• Cost
• Resource
Systemic
• Standards
• Technology
• Training
• Familiarity
Obstacles
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27. Ongoing Review
• “Statistically guided review of clinical data”
• Colloquially called ‘Data Review Tool’
- S-Plus based
Creating a consistent foundation
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28. Guided Data Review
Example lab data
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29. Guided Data Review
Shift plots
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30. Guided Data Review
Adverse event incidence
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31. Guided Data Review
Group comparison plot
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32. Guided Data Review
Looking at a patient’s data
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33. Ongoing Review
• REACT: REal-time Analytics for Clinical Trials
• We use it for the early assessment and
ongoing monitoring of adverse events during a
clinical trial.
Putting more in the hands of the expert
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34. Ongoing Review
Example population lab data
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35. Ongoing Review
Example population lab data
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36. Ongoing Review
• data review tools
- real time
- statistically guided
- interactive
- intelligible
An essential activity in drug development
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37. Clinical development as an iterative cycle
Design
Execute
Interpret
Decide
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38. Set up
Execute
Analyze
Set up
Execute
Analyze
Accurate Forecasting Affects Analysis
Sometimes things take longer than planned
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Set up
Execute
Analyze
D
e
c
i
d
e
39. Less is More
Fewer static reports help interpretation
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40. Traditional Trial Reporting
A phase 2 study, 210 patients
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41. Presenting Our Results
Contemporary technology
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42. Setting the Rules for a Decision
Design
Execute
Interpret
Decide
Design with the end in mind
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43. Great Design Should Give Good Results
Easy, unambiguous interpretation of results
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44. Shades of Evidence
Easy, ambiguous interpretation of results
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45. Complex Measures
Expert interpretation is needed
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pre post
46. Openness and Simplicity Help
• Clear criteria
• Explicit assumptions
• Predefined analyses
• Immediate access to interpretable trial data
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47. Setting the Rules for a Decision
Design
Execute
Interpret
Decide
Anticipating changes
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48. To the Future
Experts with information at their fingertips
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50. To the Future
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51. Increasing Transparency
• NEJM editorial on the USA Trial and Experimental Studies
Transparency Act
• “…clinical trials should be conducted in the open, with full
public knowledge of the question asked, the intervention
tested, and the results obtained. The TEST Act is another
step toward this end, and we strongly support it.”
• European Medicines Agency statement
- “…it will proactively publish clinical trial data and enable
access to full data sets by interested parties.”
• EFPIA statement
- “EFPIA, the voice of the research-based pharmaceutical
industry, welcomes all moves to remove perceived secrecy,
as long as legitimate trade secrets are protected”
The call and the response
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52. Linked Data Are Changing What We Can Do
Linked open data in 2011
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Linking Open Data cloud diagram, by Richard Cyganiak and Anja Jentzsch.
http://lod-cloud.net/
53. Increasing Interest in Linked Data
An evolving set of tools
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54. Open Data Let People Do More
You can apply your own perspective
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55. Health Data
Accessible? Open?
• Because of PatientsLikeMe, we are better
able to recognize warning signs... [and] keep
things in perspective. In short,
PatientsLikeMe empowers us.
• PatientsLikeMe has provided me with new
friends- people who are experiencing the
same problems as I am.
• I joined because I didn't want to feel alone
anymore. Simply put. And I knew that I could
be helpful [by sharing] my experience.
• www.patientslikeme.com
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[myhealthevet] provides you
opportunities and tools to make
informed decisions
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57. In summary
• Make better use of experts’ time by focusing effort
- Make best use of available information in ways experts can
use
- Keep things simple
- Embrace the available technologies and cultural changes to
make the most meaningful difference for patients
Make the biggest difference possible
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58. Acknowledgements
• AstraZeneca
- Andrew Hughes, Anita Lindsay, Louise Grochow, Laszlo
Vasko, Nina Mian, Amrik Mahal,Jjames Weatherall, Harry
Southworth & Dónal Landers
• Thomson Reuters
- Tim Miller, John Cole & Richard Chamier
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