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FDA/DCDISC Workshop

FDA/DCDISC Workshop. 25-Apr-2014. Welcome. Introductions Housekeeping Rules Thanks Colleen Ratliffe What is DCDISC?. Agenda. 9:00-9:15 – Gathering & Welcome 9:15-9:30 - FDA/CDER State of Data Standards Mary Ann Slack, Ron Fitzmartin - CDER

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FDA/DCDISC Workshop

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  1. FDA/DCDISC Workshop 25-Apr-2014

  2. Welcome • Introductions • Housekeeping Rules • Thanks • Colleen Ratliffe • What is DCDISC?

  3. Agenda • 9:00-9:15 – Gathering & Welcome • 9:15-9:30 - FDA/CDER State of Data Standards • Mary Ann Slack, Ron Fitzmartin - CDER • 9:30-9:45 - FDA/CBER State of Data Standards • LiseStevens, CBER • 9:45-10:45 –Challenges with Incoming Data • Doug Warfield, Lisa Lin – CDER, eData Team • 10:45-11:00 – Break • 11:00-11:40 – “The Importance of CDASH – A Statistical Reviewer’s Perspective” • Ben Vali, CDER • 11:40-12:15 –Challenges with Submission Data • DCDISC Team • 12:15-1:00 – Lunch/Networking

  4. Challenges with Submission Data Ingeborg Holt Jane Diefenbach Alan Meier

  5. Technology Provider Perspective Ingeborg Holt Booz Allen Hamilton

  6. Technology Provider’s Task: Apply Knowledge in Order to Solve a Problem • Problem: High incidence of spilt milk • Input: Milk • Functionality: (1) Allow drinking of milk from the cup (2) Minimize spilling when the cup isn’t oriented properly • The ideal conditions for this are: • The problem is clearly defined • The input sources are known and have stable formats • The desired functionality and output are distinctly described

  7. Technology Provider’s Task and Submission Data The problem: Can it be determined from the submission data if the drug under review is safe and effective? The input: Submission Data The functionality: The analyses that need to be performed to determine the quality and completeness of the data and the safety and efficacy of the drug.

  8. The Role of Data Standards is to Regulate the Input • Data standards (CDISC SDTMand ADaM) • Organize submission data in a systematic way • Control terminology • Reduce the work needed to locate and understand the data and create functionality • Increase the potential to reuse functionality

  9. The Problem Definition has Changed How can submission data be better modeled for its intended use, effective reuse in drug safety and public health AND assist drug development the pre-competitive space? How can data collected for answering the question “Is this drug safe and effective” be reused to inform drug safety and public health in other ways? scope How can the question “Is this drug safe and effective” be answered in the more efficiently and effectively? • Is this drug safe and effective? time • Success using data standards has expanded the scope of the problem to be solved

  10. Challenges to Standardized Submission Data • Data standards change and grow as the problem changes and grows • Adherence to principles of the standard • Early communication • Correct implementation of the standard • Requires • Sponsors understand which standards are accepted • Data validation requirements are unambiguous • Single Set of Validation Rules • OpenCDISC rules, FDA rules, rules from other organizations • Rules based on IG versus common sense rules • Checks between standards (SDTM, ADaM) • The implementation guides are as specific as possible and cover expected scenarios • Pharma SUG 2012 paper (Octagon) • EX domain often implemented incorrectly • Time and practice: implementation is improving

  11. Well Defined Functionality and Output • Analyses for safety are well defined • Therapeutic area domains may require special analyses for safety • Efficacy analyses, particularly those using therapeutic area domains, may be complex and present new challenges • Guidance needed for derived variables • How much support should be provided for missing values that can be derived (eg imputing BLFL, STDY) • Should derived SDTM variables be validated?

  12. Technology Provider Perspective on Submission Data • Adherence of submission to data standards is improving • Many of the new challenges result from an expanded problem space • There are areas that need attention and work

  13. Technology Provider’s Responsibility • Good Technology Choices • Designing tools to handle expected change • Terminology changes, variable additions/deletions, validation rule additions/changes • Anticipating therapeutic area domains, interoperability needs • What is the role of the Pre-competitive Community (FDA, CDISC and other Standard Development Organizations, Third Party Data Providers, Technology Providers, Sponsors,…) • Should information technology and data standards usage decisions involve all stakeholders and open discussion about risk/benefit issues • Metadata Repository • Changes to Standards

  14. Adventures in CDISC Consulting and eCTD Preparation Jane Diefenbach, PharmaStat LLC DCDISC Implementation Network at FDA April 25, 2014

  15. Preparing for a data submission • 18 to 24-month lead time • Legacy studies and Phase III may just be starting • Everything is changing: people, processes, knowledge of the product, often even the company structure • When standards change too it can be hard to accommodate them in this environment

  16. Google Images for eCTD Preparation

  17. What needs to happen • Planning • What studies? What data formats? What standards? • Production – legacy studies • Align the studies with a unified modeling plan • Perform the conversions, verify with reanalysis • Production – current studies • Real time conversion and linear data flow is difficult • Documentation, maybe most important

  18. Planning the Submission: Company XYZ Data Flow Studies: 101, 102, 103 104 201, 202 203 301 CDMS CDMS CDMS CDMS CDMS SDTM Item 11 Analysis SDTM SDTM Analysis SDTM ADaM ADaM ADaM CSR CSR CSR CSR CSR eCTD eCTD eCTD eCTD eCTD Integrated Data for ISS SDTM ISE ADaM ADaM eCTD eCTD Credit John Brega 2014

  19. Experience to Date • Work volume is astronomical, easy to underestimate • Clarity of purpose is sometimes absent • Standards are overwhelming; sponsors don’t know what is most important • We imagine perfection at kick off; eventually just need to get done • Downstream changes to standards, modeling are costly; sometimes we need to say Next time

  20. What makes it easier? • Use of CDASH in data collection • Predictability of new standards, fair warning • OpenCDISC – has done more to standardize implementation than anything • Electronic distribution of linked standards (SHARe) and a data standards warehouse • Widespread adoption

  21. What makes it easier? • Communication! • The more we know about how you interact with the data the better we’ll do • Guesswork leads to busy work and busy work does not advance Science or Health

  22. Google Images for CDISC Consulting

  23. Sponsor Company Alan Meier MedImmune LLC

  24. Sponsor Company • Implementation/Acceptance of Standards by Agency • Set time period for accepting submissions in new version • Allows sponsor time to decide when to upgrade • Work with CDISC to implement changes rather than publishing guidance • Saves time searching through documents • Set policy on use of provisional / sponsor-defined domains • Are sponsor-defined non-X_, Y_, Z_ domains acceptable • Will provisional domain templates be accepted

  25. Sponsor Company • ADaM vs Sponsor-Formatted Analysis Data Sets • Will agency be requiring ADaM • Versioning of CDISC Standards • Some products take 10+ years to develop • Acceptance of submission data in multiple versions

  26. DCDISC Can we get an FDA representative on the Steering Committee

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