an overview in clinical data standardization in electronic submissions · 2018-05-04 · cdisc =...
TRANSCRIPT
An Overview in Clinical Data
Standardization in Electronic
Submissions
© 2017 Clinipace Worldwide
Principal Statistical Programmer
Nicola started programming SAS in 2010 for Sanofi-Aventis in Frankfurt
Nicola has worked with various project teams and served statistical programming needs within all major indications
Regular presenter at conferences like PhUSE
Daily work at Clinipace includes:
hands-on application of CDISC standards for regulatory submission
consulting clients regarding the implementation of SDTM, ADaM and define.xml
Nicola Tambascia
© 2017 Clinipace Worldwide
General Overview
Why is standardized data needed?
Authority Guidelines
FDA
PMDA
Others
CDISC Overview
SDTM (SEND)
ADaM
Define.xml
Agenda
© 2017 Clinipace Worldwide
General benefits of standards Improve communication
Save time and resources
Facilitate comparison across studies/projects/submissions
Transparency
Enhances data sharing / collaborations (e.g. after mergers, acquisitions)
Eases the development of software / tools
Main reason: authorities request standardized clinical data
Why is standardized data needed?
Global standards for clinical research data and metadata from collection to submission demo.xpt
PT SEX
101 1
102 2
patinfo.xpt
PATIENT GENDER
101 Male
102 Female
dm.xpt
USUBJID SEX
01-101 M
01-102 F
© 2017 Clinipace Worldwide
FDA Study Data Standards Resources https://www.fda.gov/ForIndustry/DataStandards/StudyDataStandards/ucm2005545.htm
Deadlines: Sponsors whose studies started after
December 17, 2016 must use the data standards listed
in the FDA Data Standards Catalog for NDAs, BLAs and
ANDAs. For Commercial INDs, the requirement starts
after December 17, 2017.
eCTD Technical Rejection Criteria for Study Data were defined
Process on how to request waivers defined
FDA
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FDA Data Standards Catalog (excerpt)
FDA
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More useful information and documents Study Data Technical Conformance Guide v. 3.2 (PDF - 1.17MB) (Oct.
2016) - This guide provides technical specifications, recommendations, and general considerations on how to submit standardized electronic study data.
CDER/CBER Study Data Standardization Plan Recommendations (PDF - 51.74KB) - Recommendations for preparing a study data standards plan for CDER or CBER.
The Business Rules help ensure that the study data are compliant, useful, and will support meaningful review and analysis. This applies to SDTM formatted clinical studies and SEND formatted non-clinical studies. For more information see Section 8 of the Technical Conformance Guide.
The Validator Rules are used by the FDA to ensure data are standards compliant and support meaningful review and analysis.
FDA
© 2017 Clinipace Worldwide
Advanced Review with Electronic Data Promotion Group https://www.pmda.go.jp/english/review-services/reviews/advanced-efforts/0002.html
Documents have been translated into English
Electronic data submission will be required from fiscal year 2016 regarding data of clinical studies (evaluation data) that will be included in the application of new drugs, and those data are expected to be submitted based on CDISC standards such as SDTM and ADaM.
PMDA
© 2017 Clinipace Worldwide
Major differences compared to FDA requirements:
Requires Analysis Results Metadata for the main results of efficacy and safety
Rejection criteria have been set-up on data level
No waiver possible
If submitted until 2020 it has to be in CDISC format
From 2020 onwards submission in CDISC format required
Pre-clinical data (i.e. SEND data) not yet required
Use of SI units recommended
PMDA
© 2017 Clinipace Worldwide
EMA referenced CDISC in a draft guidance on data transparency
Reference was removed from final guidance
EMA focuses more on transparency
CFDA endorses CDISC in a Clinical Trial Data Management Technology Guide
https://www.cdisc.org/resources/impending-regulatory-requirements
https://www.cdisc.org/system/files/all/Education/CFDA_DataTechnicalGuide201607.pdf
Other Authorities
© 2017 Clinipace Worldwide
CDISC = Clinical Data Interchange Standards Consortium
CDISC is a global, open, multidisciplinary, non-profit organization that has established standards to support the acquisition, exchange, submission and archive of clinical research data and metadata.
CDISC standards are vendor-neutral, platform-independent and freely available via the CDISC website.
CDISC
© 2017 Clinipace Worldwide
CDISC Standards
© 2017 Clinipace Worldwide
Study
Data
Tabulation
Model
What is CDISC SDTM?
SDTM defines a standard structure for organizing and formatting data to streamline processes in collection, management and reporting. Implementing SDTM supports data aggregation and warehousing; fosters mining and reuse; facilitates sharing; helps perform due diligence and other important data review activities; and improves the regulatory review and approval process. SDTM is also used in non-clinical data (SEND). SDTM V1.4 https://www.cdisc.org/standards/foundational/sdtm SDTM IG V3.2 https://www.cdisc.org/standards/foundational/sdtmig
© 2017 Clinipace Worldwide
Selected variables from a SDTM demographic dataset
CDISC SDTM Concept Sample
Source: CDISC SDTM/ADaM Pilot Update (dm.xpt)
© 2017 Clinipace Worldwide
Selected variables from a Demography CRF page
Annotated CRF (acrf.pdf)
© 2017 Clinipace Worldwide
Analysis
Data
Model
What is CDISC ADaM?
ADaM defines dataset structures and metadata standards that support:
efficient generation, replication, and review of clinical trial statistical analyses, and
traceability between analysis results, analysis data, and data represented in the Study Data Tabulation Model (SDTM).
ADaM V2.1 & ADaM IG V1.1 https://www.cdisc.org/standards/foundational/adam
© 2017 Clinipace Worldwide
Selected variables from an ADaM questionnaire dataset (adqsadas.xpt of CDISC SDTM/ADaM Pilot Update)
CDISC ADaM Concept Sample
SDTM reference
Communication of analysis performed Variables facilitating analysis
© 2017 Clinipace Worldwide
SDTM vs. Analysis Dataset Model (ADaM)
Topic SDTM ADaM
Requirements standardized structure for - upload into data warehouse - use of standard review tools
standardization as much as possible
analysis-ready: - "One Proc Away "
Characteristics - domain concept, vertical structure - no redundancy - CRF data and trial design data - textual results
- analysis oriented - common group and stratum variables in each dataset - more derived data incl. flags - numeric codes if required for analysis
© 2017 Clinipace Worldwide
Metadata – define.xml
© 2017 Clinipace Worldwide
Traceability - ADaM
© 2017 Clinipace Worldwide
Traceability - SDTM
© 2017 Clinipace Worldwide
CDISC SDTM / ADaM Pilot Update
CDISC SDTM / ADaM Deliverables
