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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
The Current Climate
Christopher Hart | 10 October 20122 Research & Development | Biometrics & Information Science
Iconograph by Reid Parham
Making a Meaningful Difference to Patients
Supporting experts in making decisions
•Focusing the efforts of our experts
•Effective use of the most relevant information
3 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science
Clinical development as an iterative cycle
Design
Execute
Interpret
Decide
Design decisions
4 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science
Constraints
Scrutiny of R&D can increase quality
5 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science
- 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
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
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
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
3
4
Christopher Hart | 10 October
2012
9Research & Development | Biometrics & Information Science
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
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
11Research & Development | Biometrics & Information Science
Preliminary Design
Clinical support for early projects
12 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science
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
Information Support
Experts supporting experts
13
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
Creating Program Options
Competitive review
14 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science
Creating Program Options
Competitive review
15 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science
Creating Program Options
Development strategies
16 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science
Creating Program Options
Development strategies
17 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science
Creating Program Options
Defining reasonable duration
18 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science
Creating Program Options
Defining reasonable duration
19 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science
Creating Program Options
Comparative safety review
20 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science
Creating Program Options
Comparative safety review
21 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science
Clinical development as an iterative cycle
Design
Execute
Interpret
Decide
Decision making during the study
22 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science
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
23 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science
An Efficient Clinical Trial
24 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science
Design
Execute
Interpret
Safety oversight
A More Efficient Clinical Trial?
Ongoing review
25 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science
Design
Execute
Interpret
Review Prepare
Ongoing Review
Operational
• Data entry
lag
• Set up
• Cost
• Resource
Systemic
• Standards
• Technology
• Training
• Familiarity
Obstacles
26 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science
Ongoing Review
• “Statistically guided review of clinical data”
• Colloquially called ‘Data Review Tool’
- S-Plus based
Creating a consistent foundation
27 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science
Guided Data Review
Example lab data
Christopher Hart | 10 October 201228 Research & Development | Biometrics & Information Science
Guided Data Review
Shift plots
Christopher Hart | 10 October 201229 Research & Development | Biometrics & Information Science
Guided Data Review
Adverse event incidence
Christopher Hart | 10 October 201230 Research & Development | Biometrics & Information Science
Guided Data Review
Group comparison plot
Christopher Hart | 10 October 201231 Research & Development | Biometrics & Information Science
Guided Data Review
Looking at a patient’s data
Christopher Hart | 10 October 201232 Research & Development | Biometrics & Information Science
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
33 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science
Ongoing Review
Example population lab data
34 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science
Ongoing Review
Example population lab data
35 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science
Ongoing Review
• data review tools
- real time
- statistically guided
- interactive
- intelligible
An essential activity in drug development
36 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science
Clinical development as an iterative cycle
Design
Execute
Interpret
Decide
37 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science
Set up
Execute
Analyze
Set up
Execute
Analyze
Accurate Forecasting Affects Analysis
Sometimes things take longer than planned
38 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science
Set up
Execute
Analyze
D
e
c
i
d
e
Less is More
Fewer static reports help interpretation
39 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science
Traditional Trial Reporting
A phase 2 study, 210 patients
Christopher Hart | 10 October 201240 Research & Development | Biometrics & Information Science
Presenting Our Results
Contemporary technology
41 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science
Setting the Rules for a Decision
Design
Execute
Interpret
Decide
Design with the end in mind
42 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science
Great Design Should Give Good Results
Easy, unambiguous interpretation of results
43 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science
Shades of Evidence
Easy, ambiguous interpretation of results
44 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science
Complex Measures
Expert interpretation is needed
45 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science
pre post
Openness and Simplicity Help
• Clear criteria
• Explicit assumptions
• Predefined analyses
• Immediate access to interpretable trial data
46 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science
Setting the Rules for a Decision
Design
Execute
Interpret
Decide
Anticipating changes
47 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science
To the Future
Experts with information at their fingertips
48 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science
Clinical applications project
Christopher Hart | 10 October 201249 Research & Development | Biometrics & Information Science
To the Future
50 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science
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
51 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science
Linked Data Are Changing What We Can Do
Linked open data in 2011
52 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science
Linking Open Data cloud diagram, by Richard Cyganiak and Anja Jentzsch.
http://lod-cloud.net/
Increasing Interest in Linked Data
An evolving set of tools
53 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science
Open Data Let People Do More
You can apply your own perspective
54 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science
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
55 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science
[myhealthevet] provides you
opportunities and tools to make
informed decisions
56 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science
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
57 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science
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
58 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science
59 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science
Confidentiality Notice
This file is private and may contain confidential and proprietary information. If you have received this file in error, please notify us and
remove it from your system and note that you must not copy, distribute or take any action in reliance on it. Any unauthorized use or
disclosure of the contents of this file is not permitted and may be unlawful. AstraZeneca PLC, 2 Kingdom Street, London, W2 6BD, UK,
T: +44(0)20 7604 8000, F: +44 (0)20 7604 8151, www.astrazeneca.com

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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 3 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science
  • 4. Clinical development as an iterative cycle Design Execute Interpret Decide Design decisions 4 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science
  • 5. Constraints Scrutiny of R&D can increase quality 5 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science
  • 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 3 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 11Research & Development | Biometrics & Information Science
  • 12. Preliminary Design Clinical support for early projects 12 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science 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 13 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
  • 14. Creating Program Options Competitive review 14 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science
  • 15. Creating Program Options Competitive review 15 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science
  • 16. Creating Program Options Development strategies 16 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science
  • 17. Creating Program Options Development strategies 17 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science
  • 18. Creating Program Options Defining reasonable duration 18 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science
  • 19. Creating Program Options Defining reasonable duration 19 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science
  • 20. Creating Program Options Comparative safety review 20 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science
  • 21. Creating Program Options Comparative safety review 21 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science
  • 22. Clinical development as an iterative cycle Design Execute Interpret Decide Decision making during the study 22 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science
  • 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 23 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science
  • 24. An Efficient Clinical Trial 24 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science Design Execute Interpret Safety oversight
  • 25. A More Efficient Clinical Trial? Ongoing review 25 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science Design Execute Interpret Review Prepare
  • 26. Ongoing Review Operational • Data entry lag • Set up • Cost • Resource Systemic • Standards • Technology • Training • Familiarity Obstacles 26 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science
  • 27. Ongoing Review • “Statistically guided review of clinical data” • Colloquially called ‘Data Review Tool’ - S-Plus based Creating a consistent foundation 27 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science
  • 28. Guided Data Review Example lab data Christopher Hart | 10 October 201228 Research & Development | Biometrics & Information Science
  • 29. Guided Data Review Shift plots Christopher Hart | 10 October 201229 Research & Development | Biometrics & Information Science
  • 30. Guided Data Review Adverse event incidence Christopher Hart | 10 October 201230 Research & Development | Biometrics & Information Science
  • 31. Guided Data Review Group comparison plot Christopher Hart | 10 October 201231 Research & Development | Biometrics & Information Science
  • 32. Guided Data Review Looking at a patient’s data Christopher Hart | 10 October 201232 Research & Development | Biometrics & Information Science
  • 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 33 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science
  • 34. Ongoing Review Example population lab data 34 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science
  • 35. Ongoing Review Example population lab data 35 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science
  • 36. Ongoing Review • data review tools - real time - statistically guided - interactive - intelligible An essential activity in drug development 36 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science
  • 37. Clinical development as an iterative cycle Design Execute Interpret Decide 37 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science
  • 38. Set up Execute Analyze Set up Execute Analyze Accurate Forecasting Affects Analysis Sometimes things take longer than planned 38 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science Set up Execute Analyze D e c i d e
  • 39. Less is More Fewer static reports help interpretation 39 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science
  • 40. Traditional Trial Reporting A phase 2 study, 210 patients Christopher Hart | 10 October 201240 Research & Development | Biometrics & Information Science
  • 41. Presenting Our Results Contemporary technology 41 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science
  • 42. Setting the Rules for a Decision Design Execute Interpret Decide Design with the end in mind 42 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science
  • 43. Great Design Should Give Good Results Easy, unambiguous interpretation of results 43 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science
  • 44. Shades of Evidence Easy, ambiguous interpretation of results 44 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science
  • 45. Complex Measures Expert interpretation is needed 45 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science pre post
  • 46. Openness and Simplicity Help • Clear criteria • Explicit assumptions • Predefined analyses • Immediate access to interpretable trial data 46 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science
  • 47. Setting the Rules for a Decision Design Execute Interpret Decide Anticipating changes 47 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science
  • 48. To the Future Experts with information at their fingertips 48 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science
  • 49. Clinical applications project Christopher Hart | 10 October 201249 Research & Development | Biometrics & Information Science
  • 50. To the Future 50 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science
  • 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 51 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science
  • 52. Linked Data Are Changing What We Can Do Linked open data in 2011 52 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science 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 53 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science
  • 54. Open Data Let People Do More You can apply your own perspective 54 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science
  • 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 55 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science [myhealthevet] provides you opportunities and tools to make informed decisions
  • 56. 56 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science
  • 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 57 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science
  • 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 58 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science
  • 59. 59 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science Confidentiality Notice This file is private and may contain confidential and proprietary information. If you have received this file in error, please notify us and remove it from your system and note that you must not copy, distribute or take any action in reliance on it. Any unauthorized use or disclosure of the contents of this file is not permitted and may be unlawful. AstraZeneca PLC, 2 Kingdom Street, London, W2 6BD, UK, T: +44(0)20 7604 8000, F: +44 (0)20 7604 8151, www.astrazeneca.com