Elke Sennewald , 22 September 2011

1. Trial Design Introduction ElkeSennewald, 22 September 2011

2. Trial Design Domains • Information about study design • No subject data • Describe the overall trial design and plan via data representation

3. Why Do Trial Design • Rapidly understanding the design of the study • Standard and relatively simple data structures • Relatively small number of rows of data and easy to comprehend • Useful for both FDA reviewers and internal sponsor use • Information can be centrally accessible and searchable

4. Trial Design Datasets Trial Arms (TA) Trial Elements (TE) Trial Visits (TV) Trial Inclusion /Exclusion (TI) Trial Summary (TS) Start thinking about this before you start the other SDTM datasets!

5. Trial Summary (TS) Dataset • Summary of trial information • No link to subject-level data in SDTM • TSGRPID used to group multiple related parameters such as Dose, Units, Frequency etc • TSSEQ used as a key for multiple records with the same parameters • Common questions: • What need to be included? • Why are we generating this?

6. Trial Inclusion/Exclusion (TI) • Not subject-oriented • Link to IE domain • STUDYID, IECAT, IETESTCD, IETEST • Subject IETEST/IETESTDC must match Trial Inclusion/Exclusion IETEST/IETESTCD • Best to create TI first, before you tackle IE • Common questions: • How to truncate if >200 characters? • Truncation – potential for duplicate IETEST values • Protocol amendment: do we need to add to TI only the changed criteria or all criteria? • Local amendment

7. TA / TE / TV datasets A data representation on the different epochs, arms and visit structure in the study Where to start? Is there a systematic approach?

8. Example 1 – Trial Design Schema Drug A Follow-up Screen Drug B Follow-up

9. Epoch Drug A Follow-up Screen Drug B Follow-up EPOCH Screening Follow-up Treatment

10. Arm / Treatment Strategy Drug A Follow-up ARM(Treatment Strategy) Screen Drug B Follow-up Screening Follow-up Treatment 1 2

11. Arm / Treatment Strategy Drug A Follow-up Screen Study Cell Drug B Follow-up Screening Follow-up Treatment 1 Screen Drug A Follow-up 2 Screen Drug B Follow-up

12. Trial Design Matrix Screening Follow-up Treatment A Screen Drug A Follow-up B Screen Drug B Follow-up

13. TE (Trial Elements) Screen Drug A Drug B Follow-up • What are the elements? • Unique study cell values (=ELEMENT)

14. Screen Run-In Placebo Screen Run-In Drug A Screen Run-In Drug B Trial Arms and Elements Overview Screen Run-in Placebo Trial Elements describes the Elements and the rules for the start and end of each. Drug A Drug B Trial Arms describes the Elements in each Arm, their order and Epoch, and any branching or transition rules. Placebo Drug A Drug B Epochs are described only in Trial Arms, and have no separate table. Screening Run-In Treatment Trial Visits describes the planned Visits for each Arm, and any start and end rules. Visit 1 Visit 2 Visit 3 Visit 4 Visit 5

15. Trial Design Matrix Screening Run-in Treatment P Screen Run-in Placebo A Screen Run-in Drug A B Screen Drug B Run-in

16. Creating Trial Elements (1) • Usually the most challenging dataset • Not a duplication of EX (Exposure) • Assign an element code (ETCD) to each value, define the start of each element (TESTRL) and end of each element (TEENRL or TEDUR) • Start rules are the most important • Subject data must exist to support the creation of these • Start of next element defines end of previous

17. Example pseudocode: EXSTDTC where EXTRT = RUN-IN DRUG Example pseudocode: DSSTDTC where DSDECOD = INFORMED CONSENT Creating Trial Elements (2) Screen Run-in Placebo Trial Elements describes the Elements and the rules for the start and end of each. Drug A Drug B

18. TE -> SE (Subject Elements) • Shows the trial progress of each subject • Whether a subject passes through each element • Timing of each element

19. EXSTDTC where EXTRT = RUN-IN DRUG DSSTDTC where DSDECOD = INFORMED CONSENT Creating Subject Elements

20. Trial Arms (TA) Dataset High level treatment plan Composed of Elements from Trial Elements Go back to the Trial Design Matrix 1 study cell = 1 row of record in TA So in our example we expect 9 rows of record Planned ARM values in DM correspond to ARM values in Trial Arms Names of ARM should reflect the protocol

21. Screen Run-In Placebo Screen Run-In Drug A Screen Run-In Drug B Creating Trial Arms Placebo Drug A Drug B

22. Trial Visit (TV) Dataset • Describe the planned visits in a trial • VISITNUM and TRSTRL is required • ARMCD expected • VISIT and VISITDY permissible • 1 record per planned visit per arm • A “visit” may span over several days (eg screening visit) • What is really the start and end of a visit? • Create Subject Visits dataset from Visit based SDTM datasets

23. TV -> SV (Subject Visits) • Shows the actual visits of each subject • Compare against the scheduled/planned visits or assessments in TV • Include unscheduled visits • Designation of VISITNUM becomes crucial • Whole number for planned visits • Decimals for unscheduled visits in SV – and slot into right place

24. Creating Trial Visits • Planned schedule of Visits • Challenge is in defining start and end of a visit • ARM/ARMCD can be used if schedule varies by Arm

25. Summary • Construction of TA/TE/TV • Study Schema  Epoch  Arm  Study Cells • Unique study cells = rows in TE • All study cells = rows in TA • If all arms have same visits, then 1 set of visits for all arms. Otherwise 1 set of visits for each arm. • Complex study designs • Systematic approach will make life easier • Think at protocol/CRF design stage – don’t wait till the end • Details vs ease of use