the do’s and don’ts of data submission

Geneva Branch

THE DO’S AND DON’TS OF DATA SUBMISSION

- Biometristi Italiani Associati – V Annual Congress Università Bicocca – Milano - 24-25/10/2013 Angelo Tinazzi Cytel Inc., Wilmington Del. USA Succursale de Meyrin – Geneva – Switzerland [email protected]

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Cytel Inc. - Confidential 2 [A. Tinazzi]


Disclaimer

The information contained in this presentation is based on personal

research of the author and does not necessarily represent Cytel Inc..

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A Failied Submission A Failed Submission

Agencies

A world of Standards

eCTD Rules

Meet the reviewer

What Next

Conclusions

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A Failied Submission

Missing Variables and Mislabeled Variables Datasets are presented in a way that remains

confusing despite diligent and repeated efforts to understand the presentation

The problems these issues cause prevent even an initial cursory verification of the primary and secondary endpoints of the XXXXX trial let alone any more sophisticated analysis

A Failed Submission

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A Failied Submission Datasets Deficiency

A Failed Submission

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A Failied Submission Datasets Deficiency

Variable Name

Variable Label

Type Decode/Format

Origin Comment

OCS1DT Date of first recurrence

Num Date9 Derived See derved datasets specs page 125

Variable Name

Variable Label

Type Decode/Format

Origin Comment

OCS1DT Date of first recurrence

Num Date9 Derived Actual date associated with QOC1CD = 1. FRE1SDT = minimum FRE1SDT, where FRE1SDT ≥ RNDT.

No link provided

Variable FRE1SDT and RNDT are not in the same dataset

A Failed Submission

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Datasets Deficiency

illog

ical

Ord

er

A Failed Submission

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Meet the reviewer and always be «honest»

Clear Communication

Create robust Analysis Dataset Specifications Claritiy Use plain

english Traceability

PDUFA V, 21st Century Review, CDER Data Standards, PhUSE/FDA and ADaM: Getting It All Right; Steve Wilson. PhUSE SDE - Durham, North Carolina. Thursday, April 18th, 2013

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THE DO’S AND DON’TS OF DATA SUBMISSION Agencies pushing for Standards

Prescription Drug User Fee Act (PDUFA) Part of the law for Food and Drug Administration

Safety Innovation Act (FDASIA) Passed in 1992 allows FDA to collect fees from

Sponsors (User Fee Programme) In return for meeting review performance goals �Really works �Review time decrease by half (priority) and 37%

(standard) Since 1993 over 1000 drugs were approved Over 50% of new drugs are launching in US

compare to 8% pre-‐PDUFA

A Failed Submission

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Prescription Drug User Fee Act (PDUFA) �Reauthorized for 2013-‐1017 �Performance Goals

“Review and act on 90% ….. Submissions in 10/6 months of the 60 day filing date”

�Improve the efficiency of human drug review through required electronic submissions standardization of electronic drug application data

A Failed Submission

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Prescription Drug User Fee Act (PDUFA) High Quality Standard of Data CDISC data is foundational pre-‐requisite �Makes possible the �Use of standard‐based review tools Development of reusable analysis scripts Analysis across submissions

�In February 2012, FDA requested congress to make standard data required for submissions

A Failed Submission

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Prescription Drug User Fee Act (PDUFA) Timeline �Dec 2012 – Draft Guidance on standards and format

of eSub +12 Months – Final Guidance released +36 Months – All new NDAs/BLAs to use CDISC

End 2015 / 2016 no more an option

A Failed Submission

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A Failed Submission

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CDISC Interchange 2013

What about the other Agencies? A Failed Submission

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THE DO’S AND DON’TS OF DATA SUBMISSION A World of Clinical Standards - CDISC

A Failed Submission

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A Failed Submission

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SDTM Version 3.1.2 Dec-2011 Amendment 1 to the SDTM V1.2 and SDTMIG

V3.1.2 New variables in DM (e.g. DTHDTC/DTHFL and

ACTARM) and AE (e.g. additional coding variables)

SDTM Version 3.1.3 Oncology (efficacy) domains (TU,TR,RS)

A Failed Submission

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SDTM Version 3.1.4 (upcoming) SS (Survival Status) EX/EC Exposure Domains New domains: IS/SR (Immunogenicity/Skin React),

PR (Procedure), DD (Death) TD (Trial Disease Assessment) HO (Healthcare Encounters) AP (Associated Persons)

What’s new in draft SDTM IG 3.1.4, Nicola Tambascia, 28th June 2013, PhUSE SDE Basel

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SDTM Version 3.1.5 (planned) More Oncology Domains More enanchements Lab Findings (e.g. biomarkers) More TA domains

A Failed Submission

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ADaM Latest Release (2012-2013) ADTTE for Time-to-Event Endpoints ADAE for Adverse Events Validation Checks

ADaM To come General Occurrences IG v1.1 ADaM Integration IG 1.0 ADaM Metatadata Guide

A Failed Submission

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Define.xml v2.0 Case Report Tabulation Data Definition Specification, (CRT-DDS) “A critical component of data submission is the define file. A properly functioning define.xml file is an important part of the submission of standardized electronic datasets and should not be considered optional” “Additionally, sponsors should make certain that every data variables code list, origin, and derivation is clearly and easily accessible from the define file. An insufficiently documented define file is a common deficiency that reviewers have noted.”

A Failed Submission

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Define.xml v2.0

A Failed Submission

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Specification for describing data sets (metadata)

Does not describe how this metadata should be displayed; display is not part of the

standard

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Validation Rules

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http://www.fda.gov/forindustry/datastandards/studydatastandards/default.htm


Accepted Standards at FDA

A Failed Submission

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SDTM IG 3.1.3 ADaM IG 1.0 SEND 3.0 Define.xml 2.0 Validation Rules

(OpenCDISC 1.4.1)

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CDISC submission In 2010, CDER received an average of over 650

datasets/week, with 23% of active NDAs containing CDISC/SDTM data In 2011 this number has increased to an average

39% in SDTM and 32% in ADaM

A Failed Submission

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eCTD Rules A Failed Submission

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The Electronic Common Technical Document (eCTD) allows for the electronic submission of the Common Technical Document (CTD) from applicant to regulator The CTD describes the organization of modules, sections and

documents.

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eCTD Rules

ADaM datasets, Define.xml

ADaM SAS programs

SDTM datasets, Define.xml, SDTM

annotated blank eCRF

A Failed Submission

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Module 5: Clinical Study Reports

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eCTD File Format


eCTD Rules

Protocol – pdf (i.e., study001-protocol.pdf) SAP – pdf (i.e., sutdy001-sap.pdf) eCRF – pdf (i.e., sutdy001-blankecrf.pdf) SDTM – xpt (i.e., dm.xpt, ae.xpt, ds.xpt, and etc) ADaM – xpt (i.e., adsl.xpt, adae.xpt, adtteos.xpt,

and etc) SEND – xpt (i.e., dm.xpt, se.xpt, bw.xpt, and etc) CSR – pdf (i.e., sutdy001-csr.pdf) Define.xml – xml or pdf (i.e., define.xml/define.pdf) ADaM SAS programs – txt (i.e., c-adsl-sas.txt) Output SAS programs – txt (i.e., t-14-01-001-ds-

sas.txt )

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eCTD Rules

Naming Conventions Lower case of letter from “a” to “z” Number from “0” to “9” “-” hypen No special character ( #, %, $ and etc) File name should be less than or equal to 64 characters including the appropriate file extension The length of entire path of the file should not exceed 230 characters. (m5/datasets/study001/sdtm/ae.xpt)

A Failed Submission

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eCTD Rules

File Guideline Version – 1.4 thru 1.7 are acceptable Fonts Standard : Arial, Courier New, Times Roman Sizes : range from 9 to 12 point ( Times New

Roman 12-point font is recommended for narrative text )

Page Print area : 8.5 inches by 11 inches Margin : at least ¾ inch

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eCTD Rules

SAS XPT File Guidance Length Variable length is less than or equal to 8 Variable label is less than or equal to 40 Dataset length is less than or equal to 8 Dataset label is less than or equal to 40

Dataset Size – less than 1 GB (LB1, LB2, and so on) The length of character variables should be

minimized (i.e., if the maximum length of USUBJID is 20 character long, keep the length as 20, not 200)

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Meet the reviewer

Pre-NDA Meeting The objective of this meeting is to obtain guidance on certain aspects of the Sponsor’s plans for NDA submission. Specifically, the Sponsor seeks agreement related to activities that must be undertaken prior to the final submission

A Failed Submission

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THE DO’S AND DON’TS OF DATA SUBMISSION Meet the reviewer

Pre-NDA Meeting Does the FDA concur with the Sponsor’s plan

regarding the composition and format of the clinical data submission for the XXXXXXX eCTD NDA?

Do not use «Open Question», always propose solutions and ask for confirmation

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CDER/CBER’s Top 7 CDISC Standards Issues Dhananjay Chhatre, eData Management Solutions Team, Office of Business Informatics CDER, U.S. FDA Amy Malla, Review Management, CBER, U.S. FDA

More details in the backup slides

Top 7 CDER/CBER CDISC Issues A Failed Submission

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http://www.fda.gov/Drugs/DevelopmentApprovalProcess/FormsSubmissionRequirements/Electro nicSubmissions/ucm248635.htm

May-2011: CDER published Common Data Standards Issues

Dec-2011: v1.1 is published Issued by CDER to convey Common Issues Requests for future submissions Study Data Specifications v2.0, July 18, 2012

CDER Common Data Standards Issues A Failed Submission

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Sponsors should refer to the latest version of SDTM IG

Sponsors should refer to Amendment 1 to SDTM V1.2

Sponsors should ensure that every data variable’s codelist, origin and derivation is clearly and easily accessible in define file

SDTM should be consistent with submitted analysis datasets


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Traceability Understanding relationship between the analysis

results the analysis datasets and the SDTM domains

Establishing the path between an element and its immediate predecessor

Two levels: Metadata traceability Relationship between an analysis result and analysis dataset(s) Relationship of the analysis variable to its source dataset(s)

and variable(s) Data point traceability Predecessor record(s)

CDER Common Data Standards Issues


A Failed Submission

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Traceability CDER Common Data Standards Issues


A Failed Submission

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Controlled Terminology Use existing CDISC terminology If available CDISC terminology is insufficient,

sponsors should create their own terminology Documentation on sponsor-specific terminology

should be included in define.xml

http://www.cancer.gov/cancertopics/cancerlibrary/terminologyresources/cdisc



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MedDRA and Common Dictionary Sponsors should exactly follow spelling and case MedDRA version should be consistent across

trials within the submission Dictionary name and version should be

documented in define.xml

More details in the backup slides


CDER Common Data Standards Issues

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PhUSE SDE; ADaM Review from a CDER Statistical Reviewer's Perspective; Behrang (Ben) Vali. FDA ‘Traceability’ is the key for reviewers Less is NOT more ADaM appropriately emphasizes this Derived Variables SHOULD ONLY exist in

ADaM datasets SDTM Datasets SHOULD ONLY present the

observed data from the CRF


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A Failed Submission

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THE DO’S AND DON’TS OF DATA SUBMISSION What Next

More Metadata Oriented e.g. Results Metadata

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Also addressed in the FDA Guidance «Semantic Interoperability»

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The FDA/PhUSE Collaboration

A Failed Submission

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The FDA/PhUSE Collaboration – Optimizing the Use of Data Standards

A Failed Submission

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Other PhUSE Initiatives

A Failed Submission

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More requirements to come The agency uses it to facilitate use of a risk-based approach for the timely identification of clinical investigator sites for on-site inspection by CDER during the review of marketing applications Experiences in Preparing Summary Level Clinical Site Data within NDA’s Submission for FDA’s Inspection Planning. Xiangchen (Bob) Cui, PharmaSUG 2013

A Failed Submission

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Data Sharing A Failed Submission

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Communication, clarity and honesty play a key role in data submission Traceability Use of Standards There are still Regional Differences (e.g. Japanese HA looks more closely at details)

THE DO’S AND DON’TS OF DATA SUBMISSION Conclusions

A Failed Submission

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Communication, clarity and honesty play a key role in data submission Traceability Use of Standards There are still Regional Differences (e.g. Japanese HA looks more closely at details)

THE DO’S AND DON’TS OF DATA SUBMISSION Conclusions

Data Submission

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New Geneva offices – November 2012


Questions

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THE DO’S AND DON’TS OF DATA SUBMISSION More details on the following topics

• Top 7 CDER/CBER CDISC Issues • CDER Common Data Standards Issues

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THE DO’S AND DON’TS OF DATA SUBMISSION Top 7 CDER/CBER CDISC Issues

1. Waste of Space i.e. actual length = 8, allotted length = 200 Impact on dataset size compounded by large number of

rows In the CDISC IG, an example references a column

length of 200. It appears this example was taken to heart by industry

2. Extras (Domains, Variables, SUPPQUAL) Use common sense and discuss with review team on

whether all information in supp- datasets are necessary (e.g. Initials)

If “important” variables (support key analyses) are placed in SUPPQUAL, discuss with the review team


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3. Validation Errors Validation process results in error log -> read it! Errors and warnings that CAN be fixed, SHOULD

be fixed Some errors/warnings will inherently exist because

of your study design i.e. no baseline result, no exposure record

Others won’t Don’t simply address and dismiss these errors in a

“Reviewer’s Guide”


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3. Validation Errors – Common Errors Codelist mis-match for extensible codelists End date is prior to start date Required and expected variables should be present

in the dataset Variable labels in the dataset should match CDISC

naming conventions AE set to serious but no qualifier exists that has

been set to “Y”


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4. Extended Codelist Submissions include codelists where variable

values are not included in the codelist Incorrect define.xml 5. ISO Dates (YYYY-MM-DDThh:mm:ss) Clarification needs to occur in CDISC IGs

regarding when to input times and when to omit

If time was captured in CRFs, include in tabulations data


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6. Traceability No traceability between source data and datasets Need linkage: CRF -> SDTM -> ADaM -> CSR SDTM datasets should be created from CRFs If instead CRFs -> Raw -> SDTM, your analysis (and

hopefully ADaM) datasets should be created from those same SDTM datasets, not the raw datasets

Features exist in the ADaM standard that allow for traceability of analyses to ADaM to SDTM

Creating SDTM and Analysis data from the raw data is incorrect (especially when submitting only SDTM and analysis data)

Raw data should create SDTM, and SDTM should then create Analysis


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7. Inadequate Documentation Often times not all aspects of the standard apply to

your study/submission Submit supporting documentation in the form of a

“Reviewer’s Guide” to explain how the data standard was implemented: What is in the custom domains? What is in the suppqual’s? Insufficient codelists? Unfixable errors/warnings and why? Derivation of key analysis variables


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Reccomendations Start implementing CDISC as soon as possible �Pre-‐NDA/BLA is too late Pre-‐IND is the best time for planning

Communicate with FDA �Follow FDA guidelines and recommendations (e.g.

CDER Data Standards Common Issues Document) �Data validation errors and warning that CAN be

fixed, SHOULD be fixed


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THE DO’S AND DON’TS OF DATA SUBMISSION CDER Common Data Standards Issues

SDTM Datasets SUPPQUAL Should not be used as a waste basket

DM Strongly preferred to use additional variables in

Amendment 1 DS EPOCH should be used to distinguish between multiple

disposition events If DEATH occurs, it should be documented in the last record

with the associated EPOCH

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SDTM Datasets AE Provide variables for MedDRA hierarchy Sponsors should include all AEs, not only the

one caused by the study treatment AESOC = MedDRA-defined, primary mapped

SOC AEBODSYS = SOC used for analysis

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SDTM Datasets Custom Domains Only to be used for data that does not fit in a

published domain LB Ideal filesize < 400 megabytes Larger files should be split according to LBCAT,

LBSCAT; Nonsplit dataset should also be included

Discuss with your review division

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SDTM Datasets Permissible variables that CDER expects to see --BLFL (LB, VS, EG, Pharmacokinetics, Microbiology) EPOCH --DY and --STDY in SE and Findings

No imputations allowed Dates in ISO 8601 Missing dates are missing dates

USUBJID No leading or trailing spaces allowed Should match across all datasets (SDTM, ADaM) on a

character basis

the do’s and don’ts of data submission

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