1 / 35

Is your clinical data ready for submission?

Is your clinical data ready for submission?. Presented by: Gil Harari, Eyal Wultz April 2014. IATI ROUNDTABLE - AGENDA. Strategy and statistical considerations in clinical trials planning (Gil Harari, MediStat) Clinical data submission – which way to go? (Eyal Wultz, Bioforum) Q&A.

raisie
Télécharger la présentation

Is your clinical data ready for submission?

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Is your clinical data ready for submission? Presented by: Gil Harari, Eyal Wultz April 2014

  2. IATI ROUNDTABLE - AGENDA • Strategy and statistical considerations in clinical trials planning (Gil Harari, MediStat) • Clinical data submission – which way to go? (Eyal Wultz, Bioforum) • Q&A

  3. CLINICAL DATA SUBMISSION • Bioforum Regulatory Services • Clinical Data Standardization – importance and priority • Legacy-based submission • CDISC-based submission • Which way to go?

  4. BIOFORUM SERVICES

  5. Bioforum Regulatory Services • Clinical Programming • Pharmacovigilence Operations BIOFORUM REGULATORY SERVICES • Regulatory Operations • Documents publishing • eCTD compilation • Lifecycle management • Adverse events processing and reporting • CIOMS, MedWatch,… • PSURs, DSURs, • Clinical programming – study support (tables, listings, figures) • Prepare data for submissions Over 40 submissions to the FDA, EMA, UK, Germany, Spain Over 100 studies to date

  6. THE IMPORTANCE OF CLINICAL DATA STANDARDS • There has been a sharp increase in Refuse-to-File (RTFs) issued by the FDA from 2009 onwards1 • Main reasons include2 – • Clinical data deficiencies and ‘Data Presentation’ (~39%) • CMC issues (~28%) • eCTD issues (25%) • Other (8%) 1June 2011 issue of Nature Reviews: Drug Discovery, Volume 10, page 403 2Based on publically-available RFTs.

  7. THE IMPORTANCE OF CLINICAL DATAS STANDARDS Sanofi, Bayer’s Lemtrada receives FDA refuse-to-file letter in relapsing MS By Lianne Dane , Created 08/27/2012 - 08:35 Sanofi’sGenzyme unit on Monday announced that it received a refuse-to-file letter from the FDA regarding its application for the approval of Lemtrada (alemtuzumab) as a treatment for relapsing multiple sclerosis. "We have had constructive dialogue with the FDA, and we are very confident in our ability to address the agency’s request and resubmit rapidly," remarked Genzyme CEO David Meeker. Genzyme, which is developing the therapy with Bayer, said regulators requested that the company "modify the presentation of the data sets to enable the agency to better navigate the application." However, the agency did not request additional data or further studies, the company noted. The drugmaker indicated that a filing submitted to the European Medicines Agency was accepted and the review process is underway. Last week, Sanofi announced that it was withdrawing a stronger dose of the therapy, which is sold under the brand name Campath, in the US and EU to prepare for the launch of Lemtrada.

  8. PREPARING CLINICAL DATA FOR SUBMISSION • Submission Data Package • Legacy Package Conversion • CDISC Conversion • Prepare clinical data for Submission

  9. LEGACY-BASED CONVERSION • CRT Changes • Legacy Package Conversion • Standardization changes • Case Report Tabulation • Change study data to comply with FDA Study Data Specification Guidance • Standardize common datasets across all studies

  10. CRT REQUIRED CHANGES • Formats – remove variable formats. Split formatted variables into two variables. • Labels – add labels to datasets and to variables, confirm uniqueness of variable names and labels • Dates/time format – verify consistency throughout the studies • Change variables order – according to FDA guidance • Verify the key variables (subject ID, visit) in all datasets • Split variables with value greater than 200 characters • Split datasets greater than 1GB. • Convert datasets to SAS Transport format.

  11. STUDY STANDARDIZATION • Standardize common datasets across all studies • Compare common domains (demographics, adverse events, labs, physical exams etc.) • Create a standard domain structure specification given the varies studies including • Standard variable names, labels, types, value codes, order • Approach for handling clinical significance and out of range • Standardize dataset names and labels • Change each study according to specification

  12. ANALYSIS DATASETS CHANGES • Analysis datasets are a must! • Apply the same standardization and CRT changes to derived variables • Add core variables (as defined by the FDA) to all datasets (study, center/site, country, treatment, sex, age, race, etc.) • Revise the analysis programs according to the updated clinical data. • Verify existing outputs (tables, listings, figures) haven’t changed

  13. PREPARING CLINICAL DATA FOR SUBMISSION • Submission Data Package • Legacy Package Conversion • CDISC Conversion • Prepare clinical data for Submission

  14. CDISC and its Standards • CDISC – The Clinical Data Interchange Consortium, non-profitable organization, that defines the world-wide standards for representing clinical data, required by the regulatory authorities as part of submissions • SDTM – Study Data Tabulation Model, representing the collected clinical data in standardized structure and controlled terminology. • ADaM – Analysis Data Model, representing study analysis data in defined datasets structure. • CDASH - Clinical Data Acquisition Standards Harmonisation , describes the basic recommended data collection fields for 18 domains • SEND- Standard for Exchange of Nonclinical Data, defining the structure, and format of standard nonclinical tabulation datasets

  15. FDA’S VIEWPOINT ON CDISC • SDTM and ADaM are the only two standards supported at FDA for submission of study data • “By supported, we mean that the listed FDA component has established processes and technology infrastructure to support the receipt, processing, review, and archive of study data using these standards. The submission of standardized study data using any standard not listed… should be discussed with the Agency in advance” FDA Study Data Standard Catalog • Submitting Non-standard legacy data • “The submission of non-standardized datasets is not recommended… There are no further specifications for organizing legacy datasets” FDA Study Data Specifications, 7/18/2012

  16. FDA’S VIEWPOINT ON CDISC (cont.) • The FDA has published several new guidances on standardized study data for electronic submissions • The FDA has listed the CDISC standards as the only acceptable standards to be used for study data submission • The FDA will still accept legacy-based clinical data for studies that are starting within 24 months after the FDA register their new notice (planned within the next 6 months) • After that, only CDISC-based clinical data will be accepted

  17. INDUSTRY PERSPECTIVE • More sponsors are now submitting CDISC-based clinical data • However, not all CDISC-based submissions are equal… • From CDER1 • “CDER has received numerous “SDTM-like” applications over the past several years in which sponsors have not followed the SDTM Implementation Guide completely” • “aspects of particular sponsor implementations have actually resulted in increased review difficulty for CDER reviewers” 1CDER Common Data Standards Issues Document, Dec 2011

  18. SDTM CONVERSION – EXAMPLE Lab - external Lab - CRF LB SDTM

  19. DATA VALIDATION WITH CDISC • Conversion with CDISC is ‘invasive’ -> validation is rigorous • For SDTM • ‘Mirror’ programming • OpenCDISC® • Manual verification • For ADaM • ADaM-SDTM comparison • Double programming for imputed variables • Compare to CTR (if applicable)

  20. STUDY DATA SUBMISSION PACKAGE • Standardized clinical Data • Standardized analysis data • Analysis Programs • Define.pdf/xml for clinical and analysis data • Annotated CRF • Reviewers guide • Programs Guide

  21. CDISC VS. LEGACY – SUMMARY • Legacy • Pros • Less invasive -> less effort in conversion and verification • Cons • Not recommended by FDA (but acceptable in the short term in certain cases) • CDISC • Pros • FDA’s favorite • Cons • Usually more invasive • More effort performing conversion • More validation required

  22. TIMES ESTIMATES CDISC – ~3-5 months 1.5-2.5 months ADaM creation and verification 1 week 3 weeks 2 weeks 1.5-2.5 months SDTM conversion and verification Define xml Define xml PKG 2-3 weeks Analysis data conversion & verification Legacy – 5-10 weeks 2-3 weeks 1 week 1 week 1 week Clinical data preparation & verification Define. pdf Define. pdf PKG

  23. SUBMISSION OPTIONS • Legacy only • SDTM & ADaM • SDTM & legacy analysis datasets • The analysis datasets will be revised to use the new SDTM domains • Hybrid • Important studies – SDTM + ADaM or SDTM + Legacy Analysis • Less important studies – Legacy

  24. SUBMISSION OPTIONS (cont.) As recommended by the agency, sponsor should consult with the designated project manager at the FDA prior to work inception

  25. Thank you www.bioforum.co.il

  26. Legacy-based conversion

  27. LEGACY CONVERSION - WORKFLOW

  28. Approved Spec Project Timelines • Studies materials LEGACY CONVERSION – WORKFLOW (cont.) • Submission Std. & CRT Spec • Submission Std. & CRT Spec • Study-specific spec • Revise clinical data • Revise annotated CRFs • Submission-ready clinical data • Submission-ready clinical data • Analysis data spec • Revise analysis data • Adjust TLG programs • Submission-ready analysis programs, analysis data • Comments for derived vars • Study Submission documentation • Define.pdf1 • Reviewer’s guide • Analysis programs guide • 1 Two Define.pdf files are required – one for clinical data and one for analysis data

  29. PREPARING CLINICAL DATA FOR SUBMISSION • Study submission package • Legacy Package Conversion • CDISC Conversion • Prepare clinical data for Submission

  30. CDISC-based conversion

  31. LEGACY CONVERSION - WORKFLOW

  32. Domains Programming • Source – target mapping • Mapping practices • Controlled terminology SDTM Conversion • Conversion Verification • ‘Mirror’ Programming • Open CDISC • Manual verification

  33. Datasets Programming ADaM • Datasets Verification • ADaM-SDTM comparison • Double programming for imputed variables • Compare to CTR (if available)

  34. DOCUMENTATION & PACKAGING Same process is applicable for Legacy and CDISC conversion • Comments for derived vars • Raw/SDTM domains • Analysis/ADaM domains • SAP & CTR • Study Submission metadata and documentation • Define.xml or Define.pdf1 • Reviewer’s guide • Analysis programs guide • 1 Two Define.xml/pdf files are required – one for clinical data and one for analysis

  35. Thank you www.medistat.co.il www.bioforum.co.il

More Related