An Update on the CDISC SDTM/ADaM Pilot Project Cathy Barrows, Ph.D.

GlaxoSmithKline Co-Leader of CDISC Pilot Project CDISC ADaM Team FDA/Industry Statistics Workshop - 29 September 2006

http://www.cdisc.org/ 2

CDISC Pilot Project was to…

  Demonstrate that data submitted to the FDA using the CDISC Standard will meet the needs and expectations of

both

medical and statistical FDA reviewers.

Produce a worked example implementation of the available CDISC standards. 3

How?

  By conducting a case study   legacy data (real clinical trial data, warts and all)  CDISC SDTM domains and ADaM datasets and associated metadata submission of case study package to FDA for mock review And in the process, identify any issues to be resolved in SDTM and ADaM models 4

FOCUS: the package not the process

 Choices/decisions guided by     timeline realities of a team of volunteers from multiple companies quick, efficient, effective - not necessarily the most preferred option are not making recommendations re process!

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Pilot Submission Deliverables

 Submission package   Includes SDTM datasets, analysis datasets, all relevant metadata, analysis results, abbreviated report Review package tied together using metadata in DEFINE.XML

 Summary report of the pilot submission project   issues encountered, strengths and weaknesses incorporate what we learned from the FDA feedback  Both to be made available to the public on the CDISC website 6

Criteria for success of the Pilot Project

 FDA statistical and medical reviewers will evaluate the submitted datasets (SDTM and AdaM), metadata and documentation  Usable with their tools?

    Reproducibility of analyses, derivations?

Navigable?

Contents – what and where are OK?

etc.

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And the verdict?

    We DID produce an electronic submission that met the reviewers’ needs The overall tone of the reviewers’ feedback was very positive  noted easier learning curve The FDA review was very thorough and they provided constructive criticism Issues encountered both by team and in FDA feedback are already beginning to be addressed by CDISC teams 8

Now to details…

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Who?

   15 core team members from industry FDA involvement      Unprecedented level of involvement Provided co-leadership 18-20 employees involved  12 consistently in contact with team includes medical and statistical reviewers Interactions:     regular team teleconferences Feb. face-to-face meeting to define the project (expectations/requirements) Pre-submission encounter Feedback from review 10

FDA representatives expectations, requirements, wish list

 Key messages:  Consistency, accuracy, completeness are extremely important - follow the specifications!

   Define file crucial, but needs to be accurate Clear mapping between the plans for analysis, the tabulation data, the analysis data, and the analyses performed SDTM and Analysis datasets should be available for

both

medical and statistical reviewers 11

Presubmission “Encounter”

   Important opportunity to communicate about those crucial data-type issues that we run out of time for at “usual” meetings Discussed data to be submitted - structures, variables FDA was able to make specific requests, for example:  Hy’s Law analysis dataset (liver hepatotoxicity) 12

Legacy data used in the pilot submission

  Real clinical trial data, provided by Eli Lilly Data de-identified, documents redacted     Indication: Alzheimer’s Randomized, double-blind, placebo-controlled, parallel-group study Three treatment arms: low dose, high dose, placebo Approximately 300 patients, multiple centers  Representative set of endpoints and analyses included in package 13

CDISC Pilot Submission Package Content

• PDF TOCs and eCTD folder structure M1 (Administrative) Cover Letter PDF Study Report CDISCPILOT01 M5 (Clinical Study Reports) Reviewer’s Guide PDF Datasets Tabulation Study Report PDF DEFINE XML Analysis Annotated CRF PDF Analysis Datasets XPT DEFINE XML SDTM Datasets XPT 14

Legacy documents received Decisions regarding data analysis Map blank CRF to SDTM (aCRF) Create SDTM data metadata Create 0-obs SDTM datasets Write SAP Create analysis data metadata Create 0-obs analysis datasets

Building the CDISC Pilot Submission Package

Receive legacy data Create SDTM datasets (little derived data) Create analysis datasets

Note that “create” includes QC steps.

Coding of events data & con.med. data Generate analyses Write reviewer’s guide Write cover letter Derived data to SDTM Write study report Create DEFINE Finalize SDTM datasets Create analysis results metadata Create XPT files 15

Presentation of the Define

 FDA expectation: Pilot package in Define.xml

 The Define file integrates  tabulation dataset (SDTM) metadata   analysis dataset (ADaM) metadata analysis results (ADaM) metadata

New implementation! Exciting!

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Illustration of the Pilot Submission Package

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Top of Define file Table of Contents

Ideally would also have included a link to reviewer’s guide

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Define file: List of Analysis Datasets

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Define file: Metadata for ADSL

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Define file: Code List

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Define file: Computation Method

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Define file: List of Tabulation Datasets

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Define file: List of Analysis Results

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Define file: Analysis Results Metadata

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Define file: Linked to Study Report

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Inclusion of Programs?

• Elected to not include entire “program” • Included program code in metadata for repeated measures analysis • This WAS used in the review 27

Next Steps:

Wrap up tasks for this iteration

 Some revisions to current package  Implement some of the FDA feedback   Fix a few things that are errors or oversights Incorporate some things we wish we had done  Complete the project report  Publish the package and the project report 28

Future iterations might:

         Fully and completely work this example (rather than a subset) More fully develop the metadata Include datasets in the DEFINE file, instead of separately XPT files Use studies from other therapeutic areas Go beyond a single study Test submitting different sets of sponsor data (e.g., NDA, safety update) Address how to send updates (e.g. additional derived variables) effectively Test newer versions of models, e.g.:     ADaM PK data Pre-clinical data ODM Test other analysis strategies 29

Our Advice Wisdom is scar tissue in disguise It’s worth it!

Or, as one FDA Review Team member said:

In order to get a standard we have to suffer

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