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Communicating with Standards Keeping it Simple

Communicating with Standards Keeping it Simple. Pamela Ryley Vertex Pharmaceuticals, Inc. September 29, 2006. Implementing CDISC. Why? What Point in Study to apply CDISC Preparation for submission Database extraction Data collection / Database creation STDM – Okay

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Communicating with Standards Keeping it Simple

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  1. Communicating with StandardsKeeping it Simple Pamela Ryley Vertex Pharmaceuticals, Inc. September 29, 2006

  2. Implementing CDISC • Why? • What Point in Study to apply CDISC • Preparation for submission • Database extraction • Data collection / Database creation • STDM – Okay What about the rest of CDISC? Trial Design, ADaM, LAB Model

  3. Concurrent Changes • New Electronic Data Capture system • New Electronic Reporting and Repository system • New Standards - CDISC • Opportunity to determine where to implement CDISC • Push CDISC strategy back to data collection – data collection items being redefined anyway.

  4. Implementing STDM in Data Collection • Identifying and implementing the use of one to one matches • Implementing logical naming and structure where one to one matches not possible. • Identifying limitations of chosen EDC database and preparing for those.

  5. Implementing STDM in Data Collection Collection variables to reporting variables • eCRF Data • Controlled terminology • Electronically loaded data Efficiency and Reduced Cost

  6. Implementing STDM in Data Collection • Close collaboration between Data Management, Statisticians and Statistical Programming to streamline processing from data capture to reporting. • Education and acceptance of other groups. • Recognition of need and willingness to replace earlier standards

  7. Challenges of Implementing STDM in Data Collection Items without a one to one correlation • Variables that require transposition • Items collected for operational use • Greater detail than required by CDISC • Submissions to other agencies • Exploratory use or Publication • Items of Operational Value

  8. Extending the Implementation Legacy data Mapping • Variables • One to many • Many to One • Controlled Terminology • Add Trial Design Datasets

  9. Extending the Implementation • Increases ability to easily combine data across protocols early in compound development. • Creation of updated set of standard programs that take advantage of features in SAS version 9.

  10. Confirming Structure General Conformance • SAS v9 Proc CDISC • Web SDM Combining data across protocols • Combining legacy and current data • Data as required • Structure & Content

  11. Programming • Benefits of Pushing CDISC standards to data collection • Minimize preparation of submission datasets • Time • Resources used for more valuable endeavors • Consistency & Transparency

  12. Risks of Implementing CDISC in Data Capture • Changes to CDISC • New domains • Modifications to Draft Domains • Modifications to controlled terminology • Broader Limitations • SAS V5 Transport files  xml files • 8 character limitations on numerous variables • Changes to Trial Design, ADaM, LAB Model

  13. Challenges • Trial Design Datasets • Reserved domains • Determining when to use supplemental qualifiers versus creating new domains • Complex Design of Protocols – difficult to fit into CDISC standards • No single source for answers to questions. We do have user groups

  14. Thank You!

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