Developing e-Standards for Clinical Trials Data and Analyses

1. Developing e-Standards for Clinical Trials Data and Analyses Steve Wilson Division of Biometrics II, CDER, FDA 22nd Spring Symposium New Jersey Chapter of the American Statistical Association International Harmonization and Electronic Submission Embassy Suites, 121 Centennial Ave, Piscataway, NJ Wednesday, June 6, 2001

2. Disclaimer Views expressed in this presentation are those of the speaker and not, necessarily, of the Food and Drug Administration

3. Acknowledgements • John Clark, Center for Drug Evaluation and Research (CDER), FDA • Michael Fauntleroy, Center for Biologics Evaluation and Research (CBER), FDA • Randy Levin, Center for Drug Evaluation and Research (CDER), FDA

4. Outline • Background / motivation • Statistical review • Electronic submission • Developing guidance for e-standards • Clinical data • Documenting analyses • CTOC and the eCTD • Other data-related issues • Too much data? Thinking parsimoniously • The right data? Quality assurance and safety • Non-clinical data? Stability and Carcinogenicity • The Big Picture: Electronic Submissions -- Data Repository -- Review Tools

5. Background / Motivation • Statistical review • Electronic submission • Regulation • Guidances • MAPPs

6. Background/Motivation Statistical Review • Assess compliance with protocol / blinded analysis plans -- conduct of the study • Check appropriateness of statistical models and conclusions • Verify results reported in the NDA • Answer review questions • Modify models and assess robustness / sensitivity of the results

7. Background/Motivation Statistical Review • Modify data sets and reanalyze • Examine the trial and data for potential bias: • Results by center • Baseline predictors • Important subgroups (sex, age, race, etc,) • Assess impact of audits • Due diligence

8. The Way We Were • Statisticians requested data, program files and documentation (PROC Contents, annotated CRF, description of derived variables, etc.) at Pre-NDA meetings • To assist review, sponsors submitted these electronic files to reviewers as “desk copies” -- no formal archive • Possibly a number of data and program requests during review cycle

9. Background/Motivation Electronic Submission: Regulation • 21 CFR Part 11Electronic Records; Electronic Signatures; Final Rule Electronic Submissions; Establishment of Public Docket; Notice • August 20, 1997 • www.fda.gov/ora/compliance_ref/part11/Default.htm

10. Regulation: 21 CFR Part 11 • ...electronic records as equivalent to paper records... • ...apply to all FDA program areas... • ... intended to permit the widest possible use of electronic technology, compatible with FDA's... responsibility to promote and protect public health...

11. Regulation: 21 CFR Part 11 • ...The use of electronic records as well as their submission to FDA is voluntary... • ...docket No. 92S-0251 ... identify specifically what types of documents or parts of documents are acceptable for submission in electronic form without paper records... • ...consult with the intended agency receiving unit for details

12. Electronic Submission: NDA • Electronic equivalents to paper • Text and CRFs • PDF (Adobe’s portable document format) organized in specified folders • “Navigate” with bookmarks and hyperlinks • CRTs -- the Data • Version 5 SAS transport SAS Institute (SAS technical support TS-140. • Business Case: replace CRTs format...open format published by the -- save trees, already giving it to the statisticians

13. Electronic Submission: GuidanceNDA -- Case Report Tabulations • ...provide a single transport file for each dataset. ... • ...less than 25MB per file... • ...data definition tables ...variable name, a description of the variable, the type of variable (e.g., number, character, date), and codes... • derived variables...method of deriving the variable

14. Electronic Submission: GuidanceNDA -- Case Report Tabulations • ...Variable names are limited to 8 characters... • ...Descriptive name up to 32 characters... • ...Further recommendations...for each specific submission type... • ...discuss the content of the datasets with the review division prior to submission.

15. Appendix 2: Example Content of Specific Clinical Datasets • The following lists contain suggesteddata elements for the individual datasets. • ... serve as a starting point for discussion between you and the review division on the content and organization of the datasets and, therefore, is not all inclusive. • ... refining these data elements ... • ...data needed for each indication varies… specific information ... at the time of the pre-NDA meeting or earlier ...

16. Appendix 2: Example Content of Specific Clinical Datasets • ... programs that you used in your statistical analysis ... final analysis for principal efficacy and safety data...placed in the appropriate subfolder of the crt folder. • ...The programs should contain sufficient detail to allow the reviewer to follow the logical flow of the program...

17. Appendix 2: Example Content of Specific Clinical Datasets • Concomitant medications • · Drug name • · Drug start date • · Drug stop date • · Drug started before study (yes/no) • · Drug type • · Dose • · Reason for medication • · (Consult the review division...) • ... • Demographics • · Age • · Sex • · Race • · Weight • · Height • · Country • · (Consult the review division …) • Inclusion criteria • · Vary by protocol – consult ... • Exclusion criteria • · Vary by protocol – consult ...

18. Appendix 2: Example Content of Specific Clinical Datasets • Medical history • Disposition • Drug exposure • Efficacy results • Human pharmacology and bioavailability / bioequivalence data • Microbiology data • Physical examination • Adverse events • Vital signs • ECG • Labs

19. Electronic Submission: CBER REVISED Guidance for Industry: Providing Regulatory Submissions to the Center for Biologics Evaluation and Research (CBER) in Electronic Format - Biologics Marketing Applications [Biologics License Application (BLA), Product License Application (PLA) / Establishment License Application (ELA) and New Drug Application (NDA)] 11/12/99 www.fda.gov/cber/guidelines.htm

20. CDER MAPP 7600.6 • Requesting and Accepting Non-Archivable Electronic Records for New Drug Applications • …cannot be accepted in lieu of the archivable electronic record as outlined in the guidance. • SAS transport file to the EDR.

21. Mid-Course Review • Regulation: 21 CFR 11 • Guidances • General considerations • NDA • CBER • MAPP www.fda.gov/cder/regulatory/ersr

22. Regulation Vs. Guidance

23. The Way We Are • Electronic submissions becoming routine for some • Still dealing with paper for a number of others • Statistical reviewers caught in the middle -- CRTs and analysis files • Confusion on both sides

24. Developing Guidance for e-Standards • Leveraging / observing • Standardizing clinical data • Documenting analyses

25. Leveraging /Observing • Leveraging is the creation of relationships and/or formal agreements with others outside the FDA that will ultimately enhance FDA's ability to meet its public health mission. • CRADA -- Cooperative Research And Development Agreement ...appropriate only with collaborators who will make significant intellectual contributions. • Observing -- we can look, but we can’t touch

26. Developing Guidance for e-Standards Standardizing Clinical Data • Recognized need / advantages • CDISC -- Clinical Data Interchange Standards Consortium • Agency working group -- guidance • Safety data and patient profiles • Cautionary note

27. Ref.: CDISC CDISC CDISC (Clinical Data Interchange Standards Consortium) -- an open, multidisciplinary, non-profit organization committed to the development of industry standards to support the electronic acquisition, exchange, submission and archiving of clinical trials data and metadata for medical and biopharmaceutical product development. www.cdisc.org

28. Ref.: CDISC CDISC Goals • Nearly seamless exchange of data within a company, between collaborating companies, and with regulatory agencies – across protocols, companies and compounds • Effortless archiving of data and metadata for future review or regulatory audit • Integration of data from a wide variety of applications and systems • Facilitated reviews of regulatory submissions • Improvements in data quality; ‘cleaner data faster’

29. Ref.: CDISC The CDISC Approach to Submission Standards • Follow the lead of the FDA Submission Guidelines • Consider Regulatory Reviewer(s) as primary customer(s) • Define basic safety metadata standards to guide dataset organization -- not rigid structures • Aim for 80% of domains and 80% of variables • Use representative examples rather than hard rules • Allow flexibility for science and sponsor differences • Start with 12 safety domains; then develop a library for therapeutic areas over time • Post standards openly and encourage ongoing input by all.

30. Ref.: CDISC CDISC: Metadata Description • Specified in Guidelines • Domain Dataset Name (e.g., DEMO) • Description (Demographics) • Location (crt/datasets/1234/demo.xpt) • Metadata model proposes adding Structure • Defines the key structure and unit of analysis for a row or observation • Useful when multiple datasets are needed for the same clinical domain • Differentiates crt datasets from redundant analysis datasets.

31. Ref.: CDISC CDISC Metadata Example: Dataset Redundancy • Is the lab value normal? (1 rec/pat/visit/lab test) • Did the lab value change over time? (1 rec/pat/visit)

32. Ref.: CDISC CDISC: Submission Dataset Definition

33. Ref.: CDISC CDISC and HL7 The Associate Charter Agreement signed by HL7 and CDISC calls for the creation of a Clinical Trials Special Interest Group (CTSIG) within HL7 that will convene jointly with representatives from the existing CDISC Working Teams.

34. Ref.: CDISC Developing Guidance for e-Standards Documenting Analyses: Analysis Dataset Models (AdaM) • DRAFT: Guidelines for the Creation of Analysis Files and Associated Documentation for Submission to the FDA • PURPOSE: provide guidelines for the creation of files and associated documentation that are submitted to the FDA statistical reviewer in support of the primary and important secondary study objectives

35. eIND, eCTD and CTOC • eIND -- electronic Investigational New Drug • CBER Pilot • eCTD -- electronic Common Technical Document • CTOC -- Cumulative Table of Contents • XML • Pilots

36. Other Data-Related Issues • Too much data? • Oncology clinical trials • The right data? • Quality Assurance • Safety • Non-clinical data? • Carcinogenicity • Stability

37. Too Much Data? Thinking Parsimoniously A Proposal for Oncology Trial Data Draft Guidance: • Cancer Drug and Biological Products — Clinical Data in Marketing Applications • Contact: Grant Williams, CDER www.fda.gov/cder/guidance/3983dft.htm

38. Too Much Data? Thinking Parsimoniously A Proposal for Oncology Trial Data Investigator to sponsor: “Why all these data?” Answer: “FDA might want it.” Sponsor to FDA: “How much data do you need? Answer: “Good question, we’ve never been asked.” Grant Williams, May 2001

39. Too Much Data? Oncology Proposal “The Agency recognizes that the collection, quality control, and entry of data in a database is an expensive and time-consuming process…In fact, many of these data may not be called for in a marketing application for therapy…We therefore encourage discussion of specific data requirements at end-of-phase-2 meetings to minimize unnecessary data collection” Draft Guidance for Industry: Cancer Drug and Biological Products -- Clinical Data in Marketing Applications

40. Too Much Data? Benefits of data reduction • Decrease cost • Increase numbers of patients in trials • Improve quality of important data • Decrease audit citations Grant Williams, May 2001

41. The Right Data • Quality Assurance • Safety

42. The Right Data?Metrics for Data Monitoring and Data Management -- A Proposal • Extremely difficult during review to assess the impact of data monitoring and data management on the reported results of the trial. • May lead to inefficiencies in the review process • Government trial experiences -- time was spent thinking and worrying about this issue

43. The Right Data? Describing Data Monitoring and Management Sample “Confidence Codes” I Empty field -- imputed value E Empty field -- filled-in after check with source documents / investigator C Failed edit check -- confirmed as actual value R Failed edit check -- value was replaced when checked against source documents/investigator P Failed edit check -- suspicious and not able to confirm as correct / retained S Failed edit check -- not able to confirm / imputed

44. The Right Data? Describing Data Monitoring and Management

45. Non-Clinical Data? • Carcinogenicity • Stability

46. Carcinogenicity • NDA Electronic Submission Guidance: Appendix 1: Example Nonclinical Pharmacology AndToxicology Datasets And Data Elements • Guidance for Industry: Statistical Aspects of the Design, Analysis, and Interpretation of Chronic Rodent Carcinogenicity Studies of Pharmaceuticals • www.fda.gov/cder/guidance/815dft.pdf

47. Electronic Submissions -- Data Repository -- Review Tools Submission metadata Documents Product information Investigator Information Clinical trials Nonclinical data Clinical data Esub Drug registration and listing Data metadata EDR Submission metadata Documents Data repository Product information Investigator Metadata Admin Listing Nonclinical Clinical Clinical trials Site Review environment COTS tools Admin viewer Dataset viewer PI viewer Metadata viewer Investigator viewer CA tool CTOC viewer Document viewer Listing viewer Profile viewer Clinical trial viewer PK tool Stability data viewer Site viewer Bioequivalence tool From Randy Levin, CDER, FDA

48. THANK YOU wilsons@cder.fda.gov 301 827-5583