Download Globalization of Clinical Drug Development – Importance of Standards

Moving from US FDA
focus to Global focus –
Importance of Standards
Margaret Minkwitz
Sept 16, 2010
Definitions of terms used
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Health authorities – agencies responsible for review and
approval of new medicines (US Food & Drug
Administration (FDA)
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Common Technical Document – Internationally agreed
structure and content details for a submission to the health
authorities
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Standards: agreed format and data structure details
• Includes meaning of the variables
• Details in agreed structure
• Globally agreed and maintained – updated and reviewed
• Version controlled
Do we have a common understanding of
the issues?
Are we talking
the same
language?
Health Authorities: reasons to
standardize data collection and reporting
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Ability to evaluate data across products / companies
• Evaluation of common effects across treatments (class effects)
Ability to use common tools to verify the reported results
• Primarily the FDA
• Other health authorities starting to follow suit
Ability to compare across data presented on public web
sites – common terms and reporting structure
Ability to standardize the product labels so that doctors can
compare the properties of treatments when deciding which
treatment to prescribe to a patient
Additional reasons for companies to
embrace standards
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Co-development – 2 companies sharing the development
costs and risks (example: AstraZeneca and BMS –
ONGLYZA® for diabetes, TV ad notes both companies)
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Outsource partnering with a Contract Research
Organization (CRO) for study conduct and reporting
• CRO partner doing studies for Pharmaceutical Company
• From protocol to report (full service)
• Strategic (portion of the study outsourced – analysis programs)
In-licensing product from development at another company
• Work with some studies in original company sources
• Need to integrate that data with new studies done
•
International Conference on
Harmonization
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Health Authorities agreed to accept the Common Technical
Document (CTD) for submissions for market authorization
• European Medicines Agency
• US Food and Drug Administration
• Japanese Health Authority
• Canadian Health Authority
Industry guidance available for design, analysis, and
reporting clinical studies
• FDA has specific guidance documents
• ICH guidance documents
• Other health Authorities have guidance documents
In preparing for Product Market
Authorization (Submission of CTD)
• Need to ensure that all relevant guidance documents are reviewed
• Determine the studies needed to provide data required for agreed key
markets (1st countries to receive package, CTD)
• Plan study designs with details around
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Error control
Approaches to handling missing data
Approaches to handling multiple comparisons
Appropriate analysis models given the primary variable for study
Location of studies (multi country study – evaluate issues)
Statistical power and sample size
• Plan for data collection and reporting (standards)
Tools to standardize data collection and
reporting
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MedDRA – Medical Dictionary for Regulatory Activities
• Adverse event reporting
• Medical terminology reporting (Medical history)
CDISC – Clinical Data Interchange Standards Consortium
• SDTM – Standard Data Tabulation Model
• ADaM – Analysis Data Model
eCTD – Electronic Common Technical Document
Clinical Trials web site reporting requirements (FDAAA)
• Web sites
• Reporting clinical studies being run
• Reporting data from completed clinical studies (within 1 year)
MedDRA structure
Adverse event reported by patient
• Reported
Rapid heart rate
Hierarchical structure (text and code) – coded to common
terminology
• System Organ Class
• High level term
• Preferred term
Cardiac
Rhythm abnormality
Tachycardia
If instead of rapid heart rate, a heart rate value was reported
• Reported/Preferred term
• System Organ Class
• High level term
Heart rate120 beats/minute
Investigations
Vital sign
Features of SDTM
•
Domain – aggregation of specific type of information
• DE - Demography – age, sex, race, ethnicity, country, etc.
• VS - Vital signs – pulse, diastolic blood pressure, systolic blood
pressure, respiration rate, temperature, etc.
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Variable – information includes
• VS test name
DIABP
• VS test description
Diastolic Blood Pressure
• VS test units
mmHg
• VS test result
74
• Variable extensions:
position code list
supine, sitting, standing, not specified
method code list
manual, automatic, etc.
Features of ADaM
Similar to SDTM but the data are statistical analysis an
parameters
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Analysis method
Analysis of Variance
Comparison
A vs. B estimate (trt diff)
Statistical test
t-test
Test value
5.66
Prob > |t|
<0.0001
Parameter name
mean
Parameter estimate
5.61
Parameter variability name
Standard Error
Parameter variability estimate
0.99
eCTD Standards
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Common structure – Table of Content
Clinical Section includes
• Section 2: Clinical Overview; Clinical Summary of Pharmacology.
Efficacy, Safety, Benefit/Risk
• Section 5: Study reports for key studies; detailed supporting tables
(Integrated summary of safety and efficacy)
• Regulatory Section:
• Section 1: Specifics around the particular health authority
submission
• Information on communications and interactions during the
program
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• Details specific to local requirements
Delivered as an electronic CTD – electron transfer
Web site expectations of links
• Study design
• Planned analysis
• Study results
• Descriptive statistics
• Adverse Events
• Counts
• Primary variable
• Secondary variable
• Serious events
• Estimate and dispersion
• Estimate and dispersion
• number reporting event
• Number at risk
(exposed)
Presentation of the facts, no discussion or conclusions
Expectations for statisticians
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Ensure link between question (hypothesis), data collected
and analysis methods and reporting (using standards)
• Plan for reporting at the study design stage
• Have analysis plan early
• Plan for handling issues (missing data, multiple testing, variance
/covariance structure)
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• Develop statistical models and programs
• Validate that statistical programs
When data available
• Check model assumptions (distribution, dispersion, model fit)
• Provide data visualization tools to help with interpretation
Provide statistical interpretation of the results
Statistical Contribution to CTD
• Plan for integrated analysis (what should be combined, how, why)
• Prepare subset analysis and interpretation
• May need separate analysis of results in population relevant to
country where submitted (example – Chinese patients)
• Assist in quantifying Benefit/Risk
• Review documents and ensure that statements of statistical nature are
phrased correctly and any interpretation or conclusion can be
supported with the data
• Prepare for challenges to the data from the health authorities (what
might they ask, why)
• Identify any bridging studies which might be needed (Japanese PK
study)
Controversial Design or Analysis
• Plan to discuss with Health Authorities
• Need to supply
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• Written question
• Documentation if appropriate (publication)
• Include justification for selection among options available
May consult with Academic Statistical Expert
Method of discussion
• US FDA – can request a meeting to discuss (Face to face or
teleconference)
• Europe – request consultation – often written request & response
Some areas of interest
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Adaptive study design
• Not an issue for early studies (exploring dose response)
• Needs agreement if in the confirmatory development phase
• Dropping treatments
• Early termination (efficacy related)
Application of new methods
• May need to be used as sensitivity analysis if not routine approach
• Multiple imputation methods for missing data
• New multiple testing methods
• Need to be able to define/support the level of control of error
Data exploitation
• Looking for new insights given a large data set (hypothesis
generation)