Regulatory Submission Datasets in the World of Evolving Standards
Dave Christiansen, DrPHChristiansen Consulting,
CDISC Founding Director
“Safety and the Critical Path“ Sept 14-16, 20052005 FDA/Industry Statistics Workshop Washington, DC
CC Christiansen Consulting
© Copyright 2005, David H. Christiansen© Copyright 2005, David H. Christiansen 1-2
Acknowledgments Sally Cassel, Lincoln Technologies Kaye Fendt, Data Quality Research Institute Wayne Kubick, Lincoln Technologies Rebecca Kush, CDISC Randy Levin, FDA Bob O’Neil, FDA Bill Qubeck, Pfizer Norm Stockbridge, FDA Steve Wilson, FDA CDISC ADaM and SDS Teams
© Copyright 2005, David H. Christiansen© Copyright 2005, David H. Christiansen 1-3
Disclaimer
Views expressed in this presentation are those of the speaker and not, necessarily, of the Food and Drug Administration, CDISC or any other organization.
© Copyright 2005, David H. Christiansen© Copyright 2005, David H. Christiansen 1-4
State of Clinical Trial Research - 1995State of Clinical Trial Research - 1995
FDA-regulated products accounted for about 25 cents of every consumer dollar spent in the United States
Yet each company established its own clinical trials content standards independent of other companies in the industry
Technological advances were available to make the submission and review process more efficient
© Copyright 2005, David H. Christiansen© Copyright 2005, David H. Christiansen 1-5
Challenges for Adoption of Standards
Requirements for our industry not clearly defined and articulated
Past efforts not focused on overall clinical data management requirements
Organizations have focused on internal standards vs.industry-level; resistance to share internal standards
May require a change in process for the organization Clinical data standards must accommodate scientific
context and complexity inherent in clinical research
Multiple Organizations with Shifting StandardsOperationOperation
al al DatabaseDatabase
AA
Statistical Statistical Analysis Analysis
SASSAS
Statistical Statistical Analysis Analysis
SASSAS
CRO CRO Statistical Statistical Analysis Analysis
Statistical Statistical Analysis in Analysis in
S+S+
Output Output and and
ReportReport
Output Output and and
ReportReportOutput Output
and and ReportReport
Output Output and and
ReportReport
In-licenseIn-license
In-licenseIn-license
In-licenseIn-license
Out-licenseOut-licenseOperationOperation
al al DatabaseDatabase
CROCRO
OperationOperational al
DatabaseDatabaseAA
OperationOperational al
DatabaseDatabaseBB
Out-licenseOut-license
1-6Kaye Fendt, 2001Kaye Fendt, 2001
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Initial Solutions to the Problem Remote Data Entry (RDE) processes
emerged in the 1970s, but languished for 20 years without significantly impacting the Clinical Trials arena.
CANDAs/ CAPLAs – Too many different standards
The FDA CARS (Computer Assisted Review of Safety) and SMART (Submission Management and Review Tracking) initiatives took initial steps to develop Electronic Review tools.
Computer Assisted NDAs (CANDAs) and Computer Assisted Product License Applications (CAPLAs)
OperationOperational al
DatabaseDatabaseAA
Statistical Statistical Analysis Analysis
SASSAS
Statistical Statistical Analysis in Analysis in
S+S+
OperationOperational al
DatabaseDatabaseBB
CANDA CANDA from from
Company Company AA
OperationOperational al
DatabaseDatabaseAA
Statistical Statistical Analysis Analysis
SASSAS
Statistical Statistical Analysis in Analysis in
S+S+
OperationOperational al
DatabaseDatabaseBB
CANDA CANDA from from
Company Company BB
OperationOperational al
DatabaseDatabaseAA
Statistical Statistical Analysis Analysis
SASSAS
Statistical Statistical Analysis in Analysis in
S+S+
OperationOperational al
DatabaseDatabaseBB
CAPLA CAPLA from from
BioTech XBioTech X
1-8
SMART Initiative at FDAOperationOperation
al al DatabaseDatabase
From From Company Company
AA
Operational Operational DatabaseDatabase
From Company From Company BB
Operational DatabaseOperational DatabaseFrom Company CFrom Company C
FDA FDA Standard Standard DatabaseDatabase
FDA ToolsFDA Tools
Conversion to Conversion to FDA Standard DB FDA Standard DB
StructureStructure
1-9Kaye Fendt, 2001Kaye Fendt, 2001
© Copyright 2005, David H. Christiansen© Copyright 2005, David H. Christiansen 1-10
Regulatory Environment
Applicants were required to provide CRTs with submissions – CFR 314.50
Clinical reviews were primarily a paper process task – even for CRTs
1992 PDUFA – Initial Prescription Drug User Fee Act added time commitment pressures to reviewers
© Copyright 2005, David H. Christiansen© Copyright 2005, David H. Christiansen 1-11
Regulatory Environment
Constant pressure for FDA scientists to make the “right” decisions in a timely fashion
ICH / ESTRI discussions Electronic submission of CRFs/CRTs Guidance for Industry on Electronic
Submissions – General Considerations 1999
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Setting was Perfect for …
Development and acceptance of clinical trials content standards
Industry acceptance and participation in standards development
Regulatory participation in the standards development process
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The Solution(s) 1990s Electronic Data Capture (EDC) tools
reemerged as a serious interest 21CFR 11 published in March 1997 CDISC started in 1997 FDA Guidance for Industry: Computerized
Systems Used in Clinical Trials published in April 1999
FDA Guidance for Industry: Electronic Submission of NDAs/BLAs, 1999
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A Shared Vision
DataStandard
s
Labs
Regulatory
Biotech
Pharma Tech/
Software
CROs
Other Vendors
Public
Steve Wilson, 2002Steve Wilson, 2002
© Copyright 2005, David H. Christiansen© Copyright 2005, David H. Christiansen 1-15
CDISC History Began in 1997 as a volunteer organization DIA Special Interest Area Community (SIAC)
from 1998-1999 Incorporated as a non-profit organization in 2000 Members and sponsors today include over 150
companies (biopharmaceuticals, CROs, academic institutions, IT providers, etc.)
Global reach, with CDISC Coordinating Committees in Europe and Japan
© Copyright 2005, David H. Christiansen© Copyright 2005, David H. Christiansen 1-16
Clinical Data Interchange Standards Consortium (CDISC)
CDISC is an open, multidisciplinary, non-profit organization committed to the development of worldwide industry standards to support the electronic acquisition, exchange, submission
and archiving of clinical trials data and metadata for medical and biopharmaceutical product
development.The CDISC mission is to lead the development of
global, vendor-neutral, platform-independent standards to improve data quality and accelerate
product development in our industry.
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CDISC Collaborations with Food and Drug Administration (FDA)
Liaisons on SDS, ADaM, SEND, Protocol Representation Teams
SDTM referenced in eCDT Study Data Specification – July 2004
Analysis Dataset Guidance under development at FDA with input from ADaM
DEFINE.XML for SDTM submission metadata referenced in eCDT Study Data Specification – March, 2005
Co-chair HL7 RCRIM Technical Committee with CDISC and HL7
Rebecca Kush, 2004Rebecca Kush, 2004
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FDA Cooperative Research and Development Agreement (CRADA) Warehouse physical design
IBM CRADA Data loader, front-end for reviewer
Lincoln Technologies CRADA Patient Profile Viewer
PPD Informatics CRADA Integrating animal tox data
PharmQuest CRADA
Randy Levin, 2004Randy Levin, 2004
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Alphabet Soup ICH – International Committee on Harmonisation
ICH has developed a Common Technical Document (CTD) that provides for a harmonised structure and format for new product applications
FDA has a draft guidance on a Electronic Common Technical Document (eCTD), including structures for datasets and programs
ICH E3, E6 and E9 provide some models XML allows navigation and “smart” datasets
© Copyright 2005, David H. Christiansen© Copyright 2005, David H. Christiansen 1-20
More Alphabet Soup HIPAA - Heath Insurance Portability and
Accountability Act of 1996 Standards for the electronic exchange, privacy and
security of health information. Collectively these are known as the Administrative Simplification provisions
HL7 - Health Level 7 Electronic messaging standards for medical practice
data HHS supports standardized model of an electronic
health record FDA is a sponsor CDISC and HL7 have a formal affiliation
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More Alphabet Soup SNoMed - Systematized Nomenclature of
Medicine Purchased by HHS for $34M National Library of Medicine will make it available
without charge throughout the U.S XML - eXtensible Markup Language
Used by ICH for the electronic Common Technical Document (eCTD) backbone
Used by FDA for the electronic Table of Contents (eTOC)
Proposed by CDISC and FDA to replace pdf for metadata (DEFINE.XML)
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More Alphabet Soup JANUS
Janus is intended to capture all clinical data collected from a clinical trial along with enough of a machine-interpretable description of the study protocol to permit a high degree of automated analysis
A database with a structured data that will utilize tools being developed for FDA medical reviewers
FDA specified vertical data structures for SDTM V3.1 datasets
SDTM (and Janus) currently explicitly exclude Statistical Analysis Datasets
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Primary Reviewer Tasks Involving Submission Datasets
Statisticians Replicate analyses Test assumptions Perform alternative analyses
Medical Reviewers View data used for a specific table View patient profiles
Auditors Compare source data values to CRFs or source documents Verify derivations
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Submission Dataset Concepts Datasets and documentation should be adequate to
allow reviewers to answer the following questions:(1) Do the submitted data and documentation clearly describe the conduct and results of the trial?
(Can the reviewer understand the data and results?)(2) Is the clinical evidence of sufficient quality to ensure that the reported results are accurate and true?
(Does the reviewer believe the data and results?)
© Copyright 2005, David H. Christiansen© Copyright 2005, David H. Christiansen 1-25
Data Sources
• Site CRFs • Laboratories • Contract Research Organizations• Development Partners
OperationalDatabase
•Metadata •Study Data•Audit Trail•Archive
OperationalData
Interchange:ODMLAB
Regulatory Submission
Datasets
•Machine Readable Metadata (Partial)•Study Data Tabulations•Statistical Analysis Datasets•SEND
CDISC Data Models and the Clinical Trial Research Process with Drafts as of May, 2005
ODM = Operational Data Model SMM = Submission Metadata ModelLAB = Laboratory Data Model SDS = Submission Domain StandardsSEND= Standards for the Exchange ADaM = Analysis Dataset Models of Non-clinical Data
SubmissionData
Interchange:SMM
SDTM ADaM SEND
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Evolution of Case Report Tabulations Code of Federal Regulation: 21 CFR 314.50 1988 Guideline on the Statistical Sections 1997 Guidance on Archiving Data: 21 CFR 11 1999 Guidance on Providing Regulatory Submissions in
Electronic Format ICH E3 - Structure and Content of Clinical Study Reports ICH Common Technical Document eCTD and Study Data Specification Guidance for Review Staff and Industry - Good Review
Management Principles and Practices for PDUFA Products
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Regulation and Guidance: Case Report Tabulations (CRTs)
21CFR 314.50 (f) (1) “The tabulations are required to include the data on each patient in each study, except that the applicant may delete those tabulations which the agency agrees, in advance, are not pertinent to a review of the drug`s safety or effectiveness.”
1988 Guideline for the Format and Content of the Clinical and Statistical Sections of an Application defines CRTs as:
“These case report tabulations contain, in an organized fashion , essentially all data (efficacy, safety, pharmacology) collected in the case report.”
“…being entirely comprehensive, (they) serve as an archival or reference document, not as listings suitable for ordinary review.”
“These tabulations are distinct from, and more extensive than, the tabulations of individual patient data called for as parts of the full reports of controlled clinical studies…”
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Guidance: Data Listings
1988 Guideline defines patient data listings as: Demographic and baseline data, effectiveness data, and
safety data from “full reports of controlled clinical studies and the safety portions of reports of all studies.”
The data listings requested as part of the report (in an appendix to it) are focused on the particular variables critical to the analyses carried out, allowing the reviewer to examine the individual patient data underlying critical group measurements.
These report listings are generally “subsets of relevant effectiveness and safety variables used in analyses and tables.”
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1997 NDA Guidance: Archiving Submissions in Electronic Format
21 CFR Part 11 - Electronic Records; Electronic Signatures regulation provides for the voluntary submission of parts or all of an application in electronic format
Case Report Tabulations may be submitted as PDF files in two forms:
Domain Profiles - commonly referred to as patient line listings or patient data listings, domain profiles consist of all data collected for a CRF domain (such as demographics, vital signs, labs, efficacy measures) from one study.
Patient Profiles - one or more pages that contain all of the study data collected for an individual patient.
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1999 NDA Guidance: Providing Regulatory Submissions in Electronic Format Each dataset is a single SAS transport file and, in
general, includes a combination of raw and derived data.
Each CRF domain (e.g.,demographics, vital signs, adverse events) should be provided as a single dataset.
In addition, datasets suitable for reproducing and confirming analyses may also be needed.
Patient profiles can also be provided as PDF files
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Common Usage of CRT until 2003 CRTs were interpreted by many (including CDISC) as the CRF
domain datasets Analysis datasets were not CRTs Listings were defined by some as the printed or PDF representation
of a dataset with some additional “selection” variables There was no clear distinction between CRTs and data listings for
datasets In 2003 FDA interpreted 21 CFR 314.50(f)(1) as defining CRTs to
include: Study Data Tabulations Statistical Analysis Datasets Data Listings Patient Profiles
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International Committee on Harmonization (ICH): “E3 Structure and Content of Clinical Study Reports”
ICH E3 study reports provide for: Selected Patient Data Listings (Appendix 16.2) including
discontinued patients, protocol deviations, exclusions, demography, compliance, AEs, etc.
Individual Patient Data Listings (Appendix 16.4) “Data listings (tabulations) of patient data utilized by the
sponsor for statistical analyses and tables supporting conclusions and major findings. These data listings are necessary for the regulatory authority's statistical review, and the sponsor may be asked to supply these patient data listings in a computer-readable form.”
© Copyright 2005, David H. Christiansen© Copyright 2005, David H. Christiansen 1-33
FDA Guidances Relating to the ICH Common Technical Document (CTD)
M4: Common Technical Document for the Registration of Pharmaceuticals for Human Use
M2: eCTD: Electronic Common Technical Document Specification
ICH E3: Structure and Content of Clinical Study Reports Draft FDA eCTD Guidance: Providing Regulatory Submissions
in Electronic Format - Human Pharmaceutical Product Applications and Related Submissions
This guidance makes recommendations regarding the use of eCTD document information backbone files described ICH M2 and M4 and the clinical study report content described in ICH E3.
© Copyright 2005, David H. Christiansen© Copyright 2005, David H. Christiansen 1-34
Draft eCTD Guidance:Case Report Tabulations Data tabulations
Data tabulations datasets Data definitions
Data listings Data listing datasets Data definitions
Analysis datasets Analysis datasets Analysis programs Data definitions
Subject profiles IND safety reports
© Copyright 2005, David H. Christiansen© Copyright 2005, David H. Christiansen 1-35
eCTD Study Data Specifications V 1.1 March, 2005 “Data tabulations are datasets in which each record is a single
observation for a subject.” Specifications are located in the Study Data Tabulation Model (SDTM)
developed by CDISC at www.cdisc.org/models/sds/v3.1/index.html. Each dataset is provided as a SAS Transport (XPORT) file.
“Data listings are datasets in which each record is a series of observations collected for each subject during a study or for each subject for each visit during the study organized by domain.”
Currently, there are no further specifications for organizing data listing datasets. General information about creating datasets can be found in the SDTM implementation guides referenced in the data tabulation dataset specifications.
Each dataset is provided as a SAS Transport (XPORT) file.
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eCTD Study Data Specifications V 1.1 March, 2005 (cont) “Analysis datasets are datasets created to support specific analyses.
Programs are scripts used with selected software to produce reported analyses based on these datasets.”
Each dataset is provided as a SAS Transport (XPORT) file. Programs should be provided as both ASCII text and PDF files and should
include sufficient documentation to allow a reviewer to understand the submitted programs.
It is not necessary to provide analysis datasets and programs that will enable the reviewer to directly reproduce reported results using agency hardware and software. Currently, there are no other additional specifications for creating analysis datasets.
“Subject profiles are displays of study data of various modalities collected for an individual subject and organized by time.”
Each individual patient’s complete patient profile is in a single PDF file or a book-marked section of a single PDF file for all patients.
© Copyright 2005, David H. Christiansen© Copyright 2005, David H. Christiansen 1-37
So what are CRTs? Original regulation was written in the era of paper
submissions At one point, CRTs were collected or raw data Currently defined as all data submitted No clear distinction between data tabulations and
listings No clear distinction between derived variables on
data tabulations and analysis datasets
© Copyright 2005, David H. Christiansen© Copyright 2005, David H. Christiansen 1-38
Statistical Review of Clinical Trials Data
Efficacy and safety Confirmatory/Exploratory– focus on evaluating
sponsor’s results Check appropriateness of statistical models and
conclusions – programs & analysis datasets Assess quality/completeness of data Evaluate the impact of sponsor’s analytical decisions –
derived variables, missing/messy data (“quirks” – R. Helms) – sensitivity analyses
Answer new, review-related statistical questions Communication with sponsors Archive results
Steve Wilson, 2005Steve Wilson, 2005
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Statistical Review Environment
No programmers Multiple projects Increasingly electronic world Understaffed Without documentation standards,
every review is an adventure
Steve Wilson, 2005Steve Wilson, 2005
© Copyright 2005, David H. Christiansen© Copyright 2005, David H. Christiansen 1-40
Submission Files
CRTs Data Submitted to FDA
Data TabulationsObservations in SDTM Standard Format
Analysis FilesCustom datasets to support an analysis
Data ListingsDomain views by subject, by visit
Patient ProfilesComplete view of all subject data
DefineMetadata Description
Document
Steve Wilson, 2005Steve Wilson, 2005
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SDTM & Analysis Files:Today’s Mantra
BOTH ARE NEEDED FOR
REVIEW!(for now)
Steve Wilson, 2005Steve Wilson, 2005
© Copyright 2005, David H. Christiansen© Copyright 2005, David H. Christiansen 1-42
Specifications: eCTD File Organization
Steve Wilson, 2005Steve Wilson, 2005
© Copyright 2005, David H. Christiansen© Copyright 2005, David H. Christiansen 1-43
SDTM & Analysis Datasets
Currently, SDTM describes observations from a clinical trial
SDTM data (with appropriate tools) are particularly useful in medical officer evaluation of safety
It is well recognized that datasets that are used in the analysis have been restructured and contain additional information (derived variables, flags, comments, etc.)
To facilitate communication between statistical reviewers and sponsors, there is a need to standardize the documentation and content of these datasets
The CDISC/ADaM Team has a guidance describing the documentation of analysis files.
Steve Wilson, 2005Steve Wilson, 2005
© Copyright 2005, David H. Christiansen© Copyright 2005, David H. Christiansen 1-44
Goals of Draft Guidance: Datasets & Documentation Designed for Review Enable reviewers to understand, replicate,
explore, confirm, reuse, etc. Clear, unambiguous communication of
decisions, analysis and results Underlying principles:
Can a reviewing statistician understand? Can a reviewing statistician efficiently:
Quality Assure? Validate? Analyze?
Steve Wilson, 2005Steve Wilson, 2005
© Copyright 2005, David H. Christiansen© Copyright 2005, David H. Christiansen 1-45
Draft Guidance: Standard Metadata/Documentation
1. Analysis 2. Analysis Datasets 3. Analysis Variables
Steve Wilson, 2005Steve Wilson, 2005
© Copyright 2005, David H. Christiansen© Copyright 2005, David H. Christiansen 1-46
Challenges Still need to get reviews done Transitioning from/adapting to current Industry
practice -- Next Steps vs. “Vision” Getting experience Work with minimal resources Good review practice Moving target – efficacy and safety Adopting to Change
–Training/communication/resources/tools Science Communication: External and Internal Maintaining/improving Collaboration
Steve Wilson, 2005Steve Wilson, 2005
© Copyright 2005, David H. Christiansen© Copyright 2005, David H. Christiansen 1-47
Good Review Management Principles and Practices for PDUFA Products
New guidance for FDA review Defines FDA reviewing steps
Application completeness Pre-submission Application receipt Filing Review Planning Review Advisory Committee Wrap-up and Labeling Action
© Copyright 2005, David H. Christiansen© Copyright 2005, David H. Christiansen 1-48
Application Completeness “A complete application will receive a comprehensive
and complete review within a specified time frame.” Must be readable and well organized Should eliminate the need for unplanned amendments Incomplete if it “meets the regulatory criteria for filing but
lacks important information needed to complete the review and regulatory decision-making process, is disorganized, or does not conform to the recommended format for electronic submissions.”
© Copyright 2005, David H. Christiansen© Copyright 2005, David H. Christiansen 1-49
Evolution of Analysis-Level Metadata from Statistical Models
ANALYSIS NAME – A unique identifier for this analysis. DESCRIPTION – A text description of the contents of the
display. This will normally contain more information than the title of the display.
REASON – The rationale or authority for performing the analysis. Suggested controlled terminology will facilitate classification and searching.
DATASET – The name of the analysis dataset(s) used should be linked to the analysis dataset used for this analysis. Also may include the specific selection criteria to identify the appropriate records selected for this analysis.
DOCUMENTATION – Contains the information about how the analysis was performed.
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Analysis-Level Metadata (cont.) DOCUMENTATION – Contains the information about
how the analysis was performed. Could be a text description, or a link to other documents
Protocol Statistical Analysis Plan (SAP) Analysis generation program (i.e., a statistical software program
used to generate the analysis result) Contents will depend on:
The level of detail required to describe the analysis Whether or not the sponsor will be providing a corresponding
analysis generation program Sponsor-specific requirements and standards
© Copyright 2005, David H. Christiansen© Copyright 2005, David H. Christiansen 1-51
Analysis Metadata ExampleSubject Characteristics by Assigned Treatment Group for ITT Population
Placebo Active Total Number of subjects randomized
nn
nn
nn
Treatment Received Placebo Active
nn n
n nn
nn nn
Age in Years Mean±SD xx±x.x xx±x.x xx±x.x Age Groups N(%) 21-30 31-40 41-50 51+
nn(xx%) nn(xx%) nn(xx%) nn(xx%)
nn(xx%) nn(xx%) nn(xx%) nn(xx%)
nn(xx%) nn(xx%) nn(xx%) nn(xx%)
Race N(%) Caucasian Asian ……
nn(xx%) nn(xx%) nn(xx%)
nn(xx%) nn(xx%) nn(xx%)
nn(xx%) nn(xx%) nn(xx%)
Sex N(%) Female Male
nn(xx%) nn(xx%)
nn(xx%) nn(xx%)
nn(xx%) nn(xx%)
Baseline Height (cm) Mean±SD xxx±xx.x xxx±xx.x xxx±xx.x Baseline Weight (Kg) Mean±SD xxx.x±xx.xx xxx.x±xx.xx xxx.x±xx.xx Baseline BMI (Kg/M2) Mean±SD xx.xx±x.xxx xx.xx±x.xxx xx.xx±x.xxxx
© Copyright 2005, David H. Christiansen© Copyright 2005, David H. Christiansen 1-52
Analysis Metadata Example
Analysis-level Metadata Analysis name Description Reason Dataset Documentatio
n Table 1.1 Demographic
and Subject Characteristics, ITT Population
Pre-specified in Protocol
pathname/ADSL.xpt - select records where ITT=Y
SAP Section X.Y pathname/ Tab1_1.SAS
Table 1.2 Subject Disposition Summary
Pre-specified in Protocol
pathname/ADSL.xpt
FDA request xx.xxx
CDISC ADaM Team, 2005CDISC ADaM Team, 2005
© Copyright 2005, David H. Christiansen© Copyright 2005, David H. Christiansen 1-53
Analysis Program Documentation Programs used to generate an analysis using
submitted Analysis Dataset(s) as input Programs may be used for several purposes
Replicate analysis Exploratory analysis Auditing
Programs may be used at different levels As documentation As “code fragments” Execute in FDA environment
© Copyright 2005, David H. Christiansen© Copyright 2005, David H. Christiansen 1-54
Analysis Program Functionality Written documentation of the statistical process
and the dataset analyzed Statistical software program code fragments that
describe the statistical process and the analysis dataset used
Statistical software programs that compute the results but do not format the results in the same manner as the table or figure in the final report
Statistical software programs that exactly replicated the table or figure in the final report
Written documentation of the statistical process and the dataset analyzed
Statistical software program code fragments that describe the statistical process and the analysis dataset used
Statistical software programs that compute the results but do not format the results in the same manner as the table or figure in the final report
Statistical software programs that exactly replicated the table or figure in the final report
© Copyright 2005, David H. Christiansen© Copyright 2005, David H. Christiansen 1-55
Analysis Dataset Creation Documentation
Documents the creation of the submitted Statistical Analysis Datasets
Programs may be used for several purposes Replicate datasets Create similar datasets for exploratory analysis Auditing
Programs may be used at different levels As documentation As “code fragments” Execute in FDA environment
© Copyright 2005, David H. Christiansen© Copyright 2005, David H. Christiansen 1-56
Analysis Dataset Creation Documentation (cont.)
The source of the Statistical Analysis Dataset should be clearly documented, allowing the reviewer to trace back data items to their source
Documentation may depend on the source of Statistical Analysis Datasets Created from the Study Data Tabulation datasets
(sequential processing) Created in a separate work process from the
operational database (parallel processing)
© Copyright 2005, David H. Christiansen© Copyright 2005, David H. Christiansen 1-57
Issues:Submission of SAS Programs
Purpose? Replicate analysis Exploratory analysis Auditing
Which SAS programs? Dataset creation programs Analysis programs
How will programs be used? As documentation As “code fragments” Execute in FDA environment
© Copyright 2005, David H. Christiansen© Copyright 2005, David H. Christiansen 1-58
Issues: Submission of SAS Programs (cont.)
Sponsors/CRO work flows vary Proprietary programs Dataset size restrictions in Guidelines Standardized report programs are
complicated Macros are difficult to transport and
understand Need to start dialogue with FDA statisticians
© Copyright 2005, David H. Christiansen© Copyright 2005, David H. Christiansen 1-59
Implementation in the Real World
In theory, theory and practice are the same. In practice, they’re not. - Yogi Berra
How do we incorporate evolving standards into REAL work processes?
Need to balance present needs with future gains
Transitioning from/adapting to current Industry practice -- Next Steps vs. “Vision” – Steve Wilson, FDA
© Copyright 2005, David H. Christiansen© Copyright 2005, David H. Christiansen 1-60
Analysis Dataset Creation: Parallel and Sequential Data Flow
ODB
Study Data Tabulations
Statistical Analysis Datasets
Operational Database Extraction Programs
Analysis Dataset Creation Programs
Operational Database Extraction and Analysis Dataset Creation Programs
ODB
Operational Database Extraction Programs
Study Data Tabulations
Statistical Analysis Datasets
© Copyright 2005, David H. Christiansen© Copyright 2005, David H. Christiansen 1-61
So where are we?
Technology is evolving Regulations are evolving Standards are evolving Even definitions are evolving
© Copyright 2005, David H. Christiansen© Copyright 2005, David H. Christiansen 1-62
How can we survive?
Start now, develop a plan that will deal with present and adapt for the future
Design for flexibility Design with basic principles and concepts
of clinical trials, statistics and data management in mind
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