NBVA Submission to the FDA Regarding Section 4205 - NBVA.info
Preparing Data for an FDA Submission - Clinical Data ......FDA Submission SCDMWorkshop2019 Fred Wood...
Transcript of Preparing Data for an FDA Submission - Clinical Data ......FDA Submission SCDMWorkshop2019 Fred Wood...
-
© 2019 TalentMine. All Rights Reserved.The contents of this document are proprietary.
For class attendee use only. DO NOT DUPLICATE 1
Preparing Data for an FDA Submission
SCDM Workshop 2019
Fred WoodVice President, Consulting Services
SDTM and SEND Implementation Advisor
• Introduction and Learning Objectives• Regulatory Basis for Standardized Electronic Data– FDA Guidance Documents and Technical Specifications
• The Data Standards– CDISC Overview– The Role of PhUSE
© 2019 TalentMine All Rights Reserved. 2
Workshop Outline• Beyond The Data– aCRF– Define– SDRG– SDSP– Software Programs
• Traceability• The Process• Preparing for a Submission
1
2
-
© 2019 TalentMine. All Rights Reserved.The contents of this document are proprietary.
For class attendee use only. DO NOT DUPLICATE 2
Introduction
• Who am I?• Who are you?
– What functions are represented in this session?– How many years of industry experience?– How many years have you been in your current position?
• Why did you sign up for this workshop?
© 2019 TalentMine All Rights Reserved. 3
Learning Objectives
• Understand the regulatory basis for the requirement for electronic data and standardized electronic study data
• Become aware of the specific data standards the agency expects• Recognize that additional documents/files are required to support the submission of study
data
© 2019 TalentMine All Rights Reserved. 4
3
4
-
© 2019 TalentMine. All Rights Reserved.The contents of this document are proprietary.
For class attendee use only. DO NOT DUPLICATE 3
• Introduction and Learning Objectives• Regulatory Basis for Standardized Electronic Data– FDA Guidance Documents and Technical Specifications
• The Data Standards– CDISC Overview– The Role of PhUSE
© 2019 TalentMine All Rights Reserved. 5
Workshop Outline• Beyond The Data– aCRF– Define– SDRG– SDSP– Software Programs
• Traceability• The Process• Preparing for a Submission
Food & Drug Administration Safety & Innovation Act (FDASIA)
• Signed into law on July 9, 2012, amending the Food, Drug, and Cosmetic Act• Expanded the FDA’s authority and strengthens the ability to safeguard and advance
public health by:• Gives the authority to collect user fees
• Prescription drug provisions (PDUFA VI)• Medical device provisions (MDUFA IV)• Generic Drug User Fee Amendments/Act of 2012 (GDUFA II)• Biosimilar User Fee Amendments of 2017 (BsUFA II, 2017‐2022)
• Promotes innovation to speed patient access to safe and effective products• Increases stakeholder involvement in FDA processes• Enhances the safety of the drug supply chain
https://www.fda.gov/RegulatoryInformation/LawsEnforcedbyFDA/SignificantAmendmentstotheFDCAct/FDASIA/default.htm
© 2019 TalentMine All Rights Reserved. 6
5
6
-
© 2019 TalentMine. All Rights Reserved.The contents of this document are proprietary.
For class attendee use only. DO NOT DUPLICATE 4
PDUFA Fees
7
User Fee Type FY2019 FY 2020Application Fee – Clinical Data Required $2,942,965 $2,588,478Application Fee – No Clinical Data Required $1,471,483 $1,294,239Program Fee $325,424 $309,915
© 2019 TalentMine All Rights Reserved.
MDUFA Fees
8
User Fee Type Standard Fee Small Business510(k)‡ $11,594 $2,899513(g) $4,603 $2,302PMA, PDP, PMR, BLA $340,995 $85,249De Novo Classification Request $102,299 $25,575Panel‐track Supplement $255,747 $63,937180‐Day Supplement $51,149 $12,787Real‐Time Supplement $23,870 $5,968BLA Efficacy Supplement $340,995 $85,24930‐Day Notice $5,456 $2,728Annual Fee for Periodic Reporting on a Class III device (PMAs, PDPs, and PMRs)
$11,935 $2,984
© 2019 TalentMine All Rights Reserved.
7
8
-
© 2019 TalentMine. All Rights Reserved.The contents of this document are proprietary.
For class attendee use only. DO NOT DUPLICATE 5
GDUFA Fees
9
User Fee Type FY 2019 FY 2020ANDA $ 178,799 $ 176,237DMF $ 55,013 $57,795Program Large Size $ 1,862,167 $ 1,661,684
Medium Size $ 744,867 $ 664,674Small Size $ 186,217 $ 166,168
© 2019 TalentMine All Rights Reserved.
BsUFA Fees
10
User Fee Type FY 2019 FY 2020Biosimilar Biological Product Development (BPD) Fee
Initial BPD $ 185,409 $ 117,987Annual BPD $ 185,409 $ 117,987Reactivation $ 370,818 $ 235,975
Application Fee Clinical Data Required $ 1,746,745 $ 1,746,745Clinical Data not Required $ 873,373 $ 873,373
Program Fee $ 304,162 $ 304,162
© 2019 TalentMine All Rights Reserved.
9
10
-
© 2019 TalentMine. All Rights Reserved.The contents of this document are proprietary.
For class attendee use only. DO NOT DUPLICATE 6
PDUFA Reauthorization Performance Goals And Procedures FY 2018-2022 - Data Standards (1)
11
Section 5a and b Highlights• “FDA will develop the staff capacity to efficiently review and provide feedback to sponsors on
the readiness of submitted analysis data sets and programs for statistical review.”
• This staff will support pre‐ and post‐submission discussion of standardized datasets and programs
• Staff will “maintain the knowledge of and engage in collaborations about standards models used in the design, analysis and review of clinical and non‐clinical studies.”
• “FDA will improve staff capacity to assist with FDA development and updating of therapeutic area user guides (TAUGs) to include the appropriate content for the analysis data standards used in submission and review.”
J. ENHANCING REGULATORY DECISION TOOLS TO SUPPORT DRUG DEVELOPMENT AND REVIEW5.a. Enhancing Capacity to Support Analysis Data Standards for Product Development and Review
https://www.fda.gov/downloads/ForIndustry/UserFees/PrescriptionDrugUserFee/UCM511438.pdf© 2019 TalentMine All Rights Reserved.
PDUFA Reauthorization Performance Goals And Procedures FY 2018-2022 - Data Standards (2)
12
• By end of FY 2019, FDA will convene a public workshop to advance the development and application of analysis data standards. This was held on June 12th. Slides can be found here: https://healthpolicy.duke.edu/sites/default/files/atoms/files/ads_master_slide_deck.pdf
• FDA will collaborate with external stakeholders and participate in public workshops held by third parties such as standards development organizations, on development of data standards, processes, documentation and continuous improvement of clinical trials and regulatory science.
• By end of FY 2020, FDA will develop or revise, as appropriate, relevant guidance, MAPPs, SOPPs and training associated with submission and utilization of standardized analysis datasets and programs used in review, and on the processes, procedures, and responsibilities related to the receipt, handling, and documentation of submitted analysis data and programs.
J. ENHANCING REGULATORY DECISION TOOLS TO SUPPORT DRUG DEVELOPMENT AND REVIEW5.c‐e. Enhancing Capacity to Support Analysis Data Standards for Product Development and Review
https://www.fda.gov/downloads/ForIndustry/UserFees/PrescriptionDrugUserFee/UCM511438.pdf© 2019 TalentMine All Rights Reserved.
11
12
-
© 2019 TalentMine. All Rights Reserved.The contents of this document are proprietary.
For class attendee use only. DO NOT DUPLICATE 7
FDASIA Text on Electronic Submissions
13© 2019 TalentMine All Rights Reserved.
Guidance for Industry: Providing Regulatory Submissions in Electronic Format – Submissions Under Section 745A (a) of the Federal Food Drug, and Cosmetic Act
Guidance for Industry: Providing Regulatory Submissions in Electronic Format – Standardized Study Data
FDA Guidance and Technical Specifications (1)
14© 2019 TalentMine All Rights Reserved.
Data Standards Catalog Study Data Technical Conformance Guide
Guidance for Industry: Product Development Under the Animal Rule
Parent Guidance
Child Guidances
FDA-Specific Validation Rules for SDTM and SEND
Technical Specifications
Guidance for Industry: Providing Regulatory Submissions in Electronic Format — Certain Human Pharmaceutical Product Applications and Related Submissions Using the eCTD Specifications
Mentions
References
13
14
-
© 2019 TalentMine. All Rights Reserved.The contents of this document are proprietary.
For class attendee use only. DO NOT DUPLICATE 8
Guidance for Industry: Providing Regulatory Submissions in Electronic Format – Submissions Under Section 745A (a) of the Federal Food Drug, and Cosmetic Act
Guidance for Industry: Providing Regulatory Submissions in Electronic Format – Standardized Study Data
FDA Guidance Documents (1)
15© 2019 TalentMine All Rights Reserved.
Guidance for Industry: Providing Regulatory Submissions in Electronic Format — Certain Human Pharmaceutical Product Applications and Related Submissions Using the eCTD Specifications
–What is Covered?• Certain INDs• NDAs• ANDAs• Certain BLAs
– Timing: – Guidelines in this document. Specifics in later FR Notice:• NDAs: Studies starting after December 17, 2016• INDs: Studies starting after December 17, 2017
–Other information: • Binding Guidance• Only 6 pages of content• FDA will develop individual guidances to specify the electronic formats for certain submissions.
© 2019 TalentMine All Rights Reserved. 16
Guidance for Industry: Providing Regulatory Submissions in Electronic Format – Submissions Under Section 745A (a) of the Federal Food Drug, and Cosmetic Act
FDA Guidance Documents (2)
https://www.fda.gov/regulatory-information/search-fda-guidance-documents/providing-regulatory-submissions-electronic-format-submissions-under-section-745aa-federal-food-drug
15
16
-
© 2019 TalentMine. All Rights Reserved.The contents of this document are proprietary.
For class attendee use only. DO NOT DUPLICATE 9
• Binding Guidance• Repeats what submission are
covered.• Data must be in a format that
the Agency can process, review, and archive.
• References the FDA Data Standards Catalog.
• Describes Exchange Formats• Mentions CDISC CT, MedDRA.• Reiterates dates.
© 2019 TalentMine All Rights Reserved. 17
Guidance for Industry: Providing Regulatory Submissions in Electronic Format – Standardized Study Data
FDA Guidance Documents (3)
https://www.fda.gov/regulatory-information/search-fda-guidance-documents/providing-regulatory-submissions-electronic-format-standardized-study-data
FDA Guidance Documents (4)
18© 2019 TalentMine All Rights Reserved.
Guidance for Industry: Providing Regulatory Submissions in Electronic Format — Certain Human Pharmaceutical Product Applications and Related Submissions Using the eCTD Specifications
• Binding guidance. • Requirement to submit electronically based on eCTD specifications.• A submission that is not in the format(s) described will not be filed or received, unless it has been exempted.
• Reiterates scope of submission types that must follow this guidance.• References Standardized Study Data guidance and Data Standards Catalog.
• Note: The eCTD is the standard format for submitting applications, amendments, supplements, and reports CDER and CBER.
https://www.fda.gov/regulatory-information/search-fda-guidance-documents/providing-regulatory-submissions-electronic-format-certain-human-pharmaceutical-product-applications
17
18
-
© 2019 TalentMine. All Rights Reserved.The contents of this document are proprietary.
For class attendee use only. DO NOT DUPLICATE 10
The eCTD Structure
19© 2019 TalentMine All Rights Reserved.
• Module 1 is region specific.
• Modules 2‐5 are intended to be common for all regions.
FDA Online Learning: https://www.accessdata.fda.gov/cder/eCTD/index.htm
FDA Guidance Documents (5)
20© 2019 TalentMine All Rights Reserved.
Guidance for Industry: Providing Regulatory Submissions in Electronic Format — Certain Human Pharmaceutical Product Applications and Related Submissions Using the eCTD Specifications
Submission Type Final eCTD Guidance Published to FDA website
Date Requirement Begins
NDA ANDA BLA 2015‐05‐05 2017‐05‐05
Commercial IND Master files other than Type III DMFs
2015‐05‐05 2018‐05‐05
Type III DMFs 2015‐05‐05 2019‐05‐05
19
20
-
© 2019 TalentMine. All Rights Reserved.The contents of this document are proprietary.
For class attendee use only. DO NOT DUPLICATE 11
FDA Technical Specifications:Data Standards Catalog (1)• Lists the data standards and terminologies that FDA supports for use in regulatory submissions
• Includes dates for:• When support begins and ends• When the requirement begins and ends• The submission of data using standards or terminologies not listed should be discussed in advance.
• Where more than one standard is listed, submitters may choose one.• Updated several times a year
21© 2019 TalentMine All Rights Reserved.
FDA Technical Specifications:Data Standards Catalog (2)Data Exchange Standards
• Regulatory Applications (IND, NDA, ANDA, BLA, master files)
• Post‐Marketing Safety Reporting • Documents• Analysis Program Files• Clinical and Animal Study Datasets• Data Definition Files• Structured Product Labeling
Terminology Standards• CDISC• MedDRA• WHO Drug• UNII• SNOMED
22© 2019 TalentMine All Rights Reserved.
21
22
-
© 2019 TalentMine. All Rights Reserved.The contents of this document are proprietary.
For class attendee use only. DO NOT DUPLICATE 12
FDA Technical Specifications:Data Standards Catalog (4)
23© 2019 TalentMine All Rights Reserved.
https://www.fda.gov/downloads/ForIndustry/DataStandards/StudyDataStandards/UCM340684.xlsx
FDA Technical Specifications:Data Standards Catalog (3)
24© 2019 TalentMine All Rights Reserved.
https://www.fda.gov/downloads/ForIndustry/DataStandards/StudyDataStandards/UCM340684.xlsx
23
24
-
© 2019 TalentMine. All Rights Reserved.The contents of this document are proprietary.
For class attendee use only. DO NOT DUPLICATE 13
FDA Technical Specifications:Study Data Validation Rule Types
25
• The publication of rules by SDOs that assess conformance to their published standards.
• FDA Business and Validator rules to assess that the data support regulatory review and analysis.
• FDA eCTD Technical Rejection Criteria for Study Data that assess conformance.
© 2019 TalentMine All Rights Reserved.
Study Data TCG 8.2
SDTMIG v3.2 Conformance Rules v1.0
26© 2019 TalentMine All Rights Reserved.
Accessed via https://www.cdisc.org/standards/foundational/sdtmig
25
26
-
© 2019 TalentMine. All Rights Reserved.The contents of this document are proprietary.
For class attendee use only. DO NOT DUPLICATE 14
FDA Technical Specifications:Business and Validator Rules
• Business rules describe the business requirements for regulatory review to help ensure that study data is compliant and useful and supports meaningful review and analysis.
• The business rules are accompanied with validator rules that provide detail regarding FDA's assessment of study data for purposes of review and analysis.
• Validator rules assess conformance with the standard.
© 2019 TalentMine All Rights Reserved. 27
Study Data TCG Section 8.2.1
FDA Technical Specifications:Business Rules
28© 2019 TalentMine All Rights Reserved.
Accessed via: https://www.fda.gov/forindustry/datastandards/studydatastandards/default.htm
• Help ensure that study data is compliant and useful and supports meaningful review and analysis.
• Many of these are replicated in the Study Data TCG.
27
28
-
© 2019 TalentMine. All Rights Reserved.The contents of this document are proprietary.
For class attendee use only. DO NOT DUPLICATE 15
FDA Technical Specifications:Validator Rules
29© 2019 TalentMine All Rights Reserved.
Accessed via: https://www.fda.gov/forindustry/datastandards/studydatastandards/default.htm
A Note on the Validation Process (not in the Study Data TCG)
30© 2019 TalentMine All Rights Reserved.
• Automated validation tools have limitations.• Sponsors should consider a “human” validation.• Automated tools identify many of the most common errors and inconsistencies with the SDTM and SDTMIG, but:– The number of checks is small compared to the number of implementation decisions.– Not every SDTM/SDTMIG convention can be represented in computer‐executable code.
– Some may not provide clear explanations of how to fix errors:• Source‐data vs. data‐conversion issues
– The creativity of humans will always outpace the development of checks to limit that creativity.
29
30
-
© 2019 TalentMine. All Rights Reserved.The contents of this document are proprietary.
For class attendee use only. DO NOT DUPLICATE 16
Where Humans Are Needed for Validation/Conformance
• Domain Selection• Supplemental Qualifiers vs. Findings About• Proper use of variables that don’t have CDISC Controlled Terminology• Relating Records• Trial Design and Related Tables
© 2019 TalentMine All Rights Reserved. 31
Author reference: https://www.lexjansen.com/pharmasug/2010/CD/CD16.pdf
FDA Technical Specifications:Technical Rejection Criteria (1)
32© 2019 TalentMine All Rights Reserved.
Background• These are eCTD validation criteria.• Originally published in November 2016. Latest is January 2019.• Applies to clinical studies for which .xpt files are being submitted. • Applies to all nonclinical studies.• Effective Date TBD. FDA has not yet published the 90‐day notice.• When a submission is technically rejected, the submission
sequence is not transferred from the FDA Electronic Submission Gateway into the FDA electronic document rooms.
https://www.fda.gov/media/100743/download
31
32
-
© 2019 TalentMine. All Rights Reserved.The contents of this document are proprietary.
For class attendee use only. DO NOT DUPLICATE 17
FDA Technical Specifications:Technical Rejection Criteria (2)
33© 2019 TalentMine All Rights Reserved.
https://www.fda.gov/media/100743/download
FDA Technical Specifications:Technical Rejection Criteria (3)
34© 2019 TalentMine All Rights Reserved.
Requirements:• 1734: A Trial Summary dataset (ts.xpt) dataset must be present for each study in
Modules 4 and 5. The study start date, a parameter listed by the FDA in the TCG, determines whether standardized study data is required.
• 1735: The correct STF file‐tags must be used for all standardized datasets in Modules 4 and 5.
• 1736: A Demographics dataset must be submitted for all studies on Modules 4 and 5. For ADaM data, an ADSL dataset and define.xml must be submitted in Module 5.
• 1789: All files in the study section must be in the STF (eCTD study‐tagging file).
eCTD STF: https://www.fda.gov/media/76790/download
33
34
-
© 2019 TalentMine. All Rights Reserved.The contents of this document are proprietary.
For class attendee use only. DO NOT DUPLICATE 18
Basics• First Issued in 2014• Replaces the Study Data Specifications (2004‐2012), the CDER Data Standards Check‐List (2011), and
the Common Data Standards Issues documents (2011)• Provides recommendations on how to submit required standardized study data• Is non‐binding, but adherence to the recommendations facilitates regulatory review• Updated at least twice a year, usually in March and October.Contents Overview• Requests a Study Data Standardization Plan (SDSP)• Recommends a Study Data Reviewer’s Guide (SDRG.pdf) “as an integral part”• Requests that datasets have their contents described with complete metadata in the define.xml file• References the FDA Study Data Standards Catalog• References Technical Rejection Criteria for Study Data• Recommends evaluation of study data against conformance (i.e., validation) rules
© 2019 TalentMine All Rights Reserved. 35
FDA Technical Specifications:Study Data Technical Conformance Guide (TCG)
https://www.fda.gov/media/122913/download
1. Introduction2. Planning and Providing Standardized Study Data
• Study Data Standardization Plan• Study Data Reviewer’s Guides
3. Exchange format – Electronic Submissions• XML• SAS xpt
4. Study Data Submission Format – Clinical and Nonclinical• Study Data Tabulation Model• Analysis Data Model• Standard for Exchange of Nonclinical Data• Data Definition Files For SDTM, SEND, And ADaM
5. Therapeutic Area Standards
6. Terminology• CDISC Controlled Terminology• MedDRA• UNII• WHO Drug Global• National Drug File Reference Terminology• SNOMED CT• LOINC
7. Electronic Submission Format• eCTD Specifications
8. Study Data Validation and Traceability
Appendices on Interoperability, Trial Summary Parameters for Submission, CoDEx, Folder Structure
Study Data Technical Conformance Guide Contents
© 2019 TalentMine All Rights Reserved. 36
35
36
-
© 2019 TalentMine. All Rights Reserved.The contents of this document are proprietary.
For class attendee use only. DO NOT DUPLICATE 19
• Introduction and Learning Objectives• Regulatory Basis for Standardized Electronic Data– FDA Guidance Documents and Technical Specifications
• The Data Standards– CDISC Overview– The Role of PhUSE
© 2019 TalentMine All Rights Reserved. 37
Workshop Outline• Beyond The Data– aCRF– Define– SDRG– SDSP– Software Programs
• Traceability• The Process• Preparing for a Submission
CDISC AcronymsCDISC Clinical Data Interchange Standards ConsortiumSDTM Study Data Tabulation ModelADaM Analysis Data ModelSEND Standard for the Exchange of Nonclinical DataCDASH Clinical Data Acquisition Standards HarmonizationODM Operational Data ModelLAB Laboratory Data ModelPRM Protocol Representation ModelMSG Metadata Submissions GuidelineBRIDG Biomedical Research Integrated Domain GroupSHARE Shared Health and Clinical Research Electronic Library
© 2019 TalentMine All Rights Reserved. 38
37
38
-
© 2019 TalentMine. All Rights Reserved.The contents of this document are proprietary.
For class attendee use only. DO NOT DUPLICATE 20
CDISC Foundational Standards:Collection and Tabulation
39
• The Study Data Tabulation Model is a standard for the submission of tabulation data. This is data “as collected”. It is the foundation for five implementation guides.
• The Study Data Tabulation Model Implementation Guide is intended to guide the organization, structure, and format of standard clinical trial tabulation datasets.
• Standard for Exchange of Nonclinical Data (SEND) is an implementation of the SDTM standard for nonclinical studies. It specifies a way to collect and present nonclinical data in a consistent format.
• Clinical Data Acquisition Standards Harmonization (CDASH)consists of a set of content standards (element name, definition, and related metadata) for a basic set of global data collection fields (based upon the SDTM) that will support clinical research studies.
ww.cdisc.org
Other CDISC Foundational Standards
40
• The Analysis Data Model (ADaM) is a set of guidelines and examples for analysis datasets used to generate the statistical results for submission to a regulatory authority such as FDA. It specifically addresses needs of statistical reviewers.
• The Protocol Representation Model (PRM) provides a standard for planning and designing a research protocol with focus on study characteristics such as study design, eligibility criteria, and requirements from the ClinicalTrials.gov, World Health Organization (WHO) registries, and EudraCT registries. PRM assists in automating CRF creation and EHR configuration to support clinical research and data sharing.
• The Lab Model (LAB) was created for the transfer of lab data from vendors to sponsors. It can be implemented in ASCII, SAS, or XML.
ww.cdisc.org
© 2019 TalentMine All Rights Reserved.
39
40
-
© 2019 TalentMine. All Rights Reserved.The contents of this document are proprietary.
For class attendee use only. DO NOT DUPLICATE 21
© 2019 TalentMine All Rights Reserved. 41
Clinical Data Flow and CDISC Standards
Protocol Form SetupData
CaptureData
StorageAnalysis/ Reporting Submission
Protocol Representation
CDASH(Clinical Data Acquisition
Standardization and Harmonization)
SDTMIG (Study Data
Tabulation Model IG)
ADaM (Analysis
Data Model)
SDTM and ADaM
Lab Data
Lab Model
© 2019 TalentMine All Rights Reserved. 42
Nonclinical Data Flow and CDISC Standards
Multiple Data Capture Systems
NonclinicalDatabase
Study Report
SEND Datasets
Submission
SENDIG
41
42
-
© 2019 TalentMine. All Rights Reserved.The contents of this document are proprietary.
For class attendee use only. DO NOT DUPLICATE 22
SDTMThe Model
SDTMIG SENDIGImplementation Guides
SDTMIG-MD
SDTMIG-PGx
SDTMIG-AP
Implementation Guide
Supplements
SENDIG-DART
SENDIG-AR
The SDTM and Implementation Guides
43© 2019 TalentMine All Rights Reserved.
TAUGs
QRS Supplements
Metadata Submission Guidelines
UserGuides/Other
CoDEx for SEND 3.0
• CDISC SDTM w/ SDTMIG for clinical tabulation datasets• CDISC ADaM w/ ADaMIG for clinical analysis datasets• CDISC SDTM w/ SENDIG for non‐clinical tabulation datasets
Data Standards to Be Used
© 2019 TalentMine All Rights Reserved. 44
Study Data TCG, Sections 4.1.1‐ 4.1.3
43
44
-
© 2019 TalentMine. All Rights Reserved.The contents of this document are proprietary.
For class attendee use only. DO NOT DUPLICATE 23
Describe:• Names for commonly submitted datasets• Names for commonly used variables (columns)• Extensive harmonized controlled terminology (data
values)• A set of business rules for implementing SDTM concepts
45
The SDTM and SEND Implementation Guides
© 2019 TalentMine All Rights Reserved.
• Verified collected data - In the study database- In electronic transfers (e.g., lab, ECG, and PK data)- Missing values are missing values
• The SDTMIG and the SENDIG do not tell sponsors what to submit.• The sponsor decides what data to collect, based on science and regulation.• Once the determination has been made on the data to be collected, the SDTMIG and SENDIG provide the structure and format.
• SEND datasets will not replace discussions, summaries, or other information in study reports. • No data should be imputed in SDTM datasets (Study Data TCG, Section 4.1.1.2).
SDTM Datasets
© 2019 TalentMine All Rights Reserved. 46
45
46
-
© 2019 TalentMine. All Rights Reserved.The contents of this document are proprietary.
For class attendee use only. DO NOT DUPLICATE 24
SDTM and SEND Dataset Definitions
47
• Variable (Column) Names• Variable Labels• Data Types• Controlled Terminology• Variable Roles• Implementation Advice• Specific Variable (Column) Order
© 2019 TalentMine All Rights Reserved.
Identifying Information
Lab Test and Category
© 2017 Accenture All Rights Reserved.
SDTM Lab Dataset Example (1)
48
Controlled Terminology
(Content)
47
48
-
© 2019 TalentMine. All Rights Reserved.The contents of this document are proprietary.
For class attendee use only. DO NOT DUPLICATE 25
© 2019 TalentMine All Rights Reserved.
Results and Normal Ranges
Lab Name, Specimen, and Timing
49
SDTM Lab Dataset Example (2)
Controlled Terminology
(Content)
ADaM Standards• ADaM Standard v2.1• ADaMIG v1.1• ADaM BDS for TTE Analysis v1.0• ADaM OCCS v1.0
© 2019 TalentMine All Rights Reserved. 50
49
50
-
© 2019 TalentMine. All Rights Reserved.The contents of this document are proprietary.
For class attendee use only. DO NOT DUPLICATE 26
ADaM Datasets• ADaM datasets should be derived from the data contained in the SDTM datasets.• ADaM standard has variables that allow for traceability to SDTM datasets. • To ensure traceability, all SDTM variables utilized for variable derivations in ADaM should be included in the ADaM datasets when practical. Any submission with analysis data should contain an ADSL.
© 2019 TalentMine All Rights Reserved. 51
(Study Data TCG Section 4.1.2.2)
Controlled Terminology• The FDA expects sponsors to utilize controlled terminology wherever available.• Sponsors should use the most recent version of the dictionary available at the start of a clinical or nonclinical study.
• A submission of study data should describe (e.g., in the SDSP, SDRG) the impact, if any, of the use of different versions on the study results.
• If a sponsor identifies a concept for which no standard term exists, FDA recommends that the sponsor submit the concept to the appropriate terminology maintenance organization as early as possible to have a new term added to the standard dictionary.
© 2019 TalentMine All Rights Reserved. 52
(Study Data TCG, Sections 6.1.2 and 6.1.3).
51
52
-
© 2019 TalentMine. All Rights Reserved.The contents of this document are proprietary.
For class attendee use only. DO NOT DUPLICATE 27
CDISC Controlled Terminology (1)
53
• Available for SDTM, SEND, CDASH, ADaM, and PRM• Standard values used with data items within CDISC‐defined datasets. • Harmonized with the National Cancer Institute's Enterprise Vocabulary Services (EVS)• Supports the needs of all CDISC foundational standards and all CFAST disease/therapeutic‐area standards.
• Updated quarterly• Available in Excel, text, odm.xml, pdf, html, and OWL/RDF formats• Also includes a CDISC Glossary of clinical‐study terms• New‐term request can be found at https://ncitermform.nci.nih.gov/ncitermform/?version=cdisc
© 2019 TalentMine All Rights Reserved.
CDISC Controlled Terminology (2)
54© 2019 TalentMine All Rights Reserved.
• Codelist metadata in first row (blue)• Extensible means that sponsors can add to the list as long as the concept does
not exist• Codelist Code (Column A) is inherited by all values (Column B)• Each value has its own code (Column A)• Column E contains the Submission Value to be used in the SEND datasets
https://www.cancer.gov/research/resources/terminology/cdisc?redirect=true
53
54
-
© 2019 TalentMine. All Rights Reserved.The contents of this document are proprietary.
For class attendee use only. DO NOT DUPLICATE 28
CDISC Controlled Terminology (3)
55© 2019 TalentMine All Rights Reserved.
Example of html version:
Main directory: https://evs.nci.nih.gov/ftp1/CDISC/ Link to above display: https://evs.nci.nih.gov/ftp1/CDISC/SDTM/SDTM%20Terminology.html
Controlled Terminology Summary for Tabulation DataData SDTM Location Controlled Terminology
Lab Tests LBLOINC Logical Observation Identifiers and Codes (LOINC)
Adverse Events AETERM MedDRA (Medical Dictionary for Regulatory Activities )
Trial Indication TSPARMCD = INDIC (Trial Indication)TSPARMCD = TDIGRP (Diagnosis Group)
SNOMED (Systematized Nomenclature of Medicine )
Medication Coding CMDECOD, CMCLAS, CMCLASCD WHO Drug Global
Ingredients TSPARMCD = TRTUNII, COMPTRT, CURTRT UNII (Unique Ingredient Identifier)
Pharmacologic Class TSPARMCD.PCLASS MED-RT (Medication Reference Terminology; was NDF-RT prior to June 2018)
Everything Else Variable and Parameter Names and Values CDISC Controlled Terminology
External dictionary usage should be documented both in the data definition file as well as the Trial Summary (TS) domain if using SDTM IG v3.1.2 or greater or SEND IG v3.0 or greater (Study Data TCG, Section 4.1.4.5).
© 2019 TalentMine All Rights Reserved. 56
55
56
-
© 2019 TalentMine. All Rights Reserved.The contents of this document are proprietary.
For class attendee use only. DO NOT DUPLICATE 29
• Chronic Hepatitis C • Chronic Obstructive Pulmonary Disease (COPD)• Colorectal Cancer • Dyslipidemia • Diabetes• Diabetic Kidney Disease• Duchenne Muscular Dystrophy• Ebola• Huntington’s Disease• Influenza
• Kidney Transplant• Major Depressive Disorder• Malaria• Prostate Cancer• QT Studies• Rheumatoid Arthritis• Schizophrenia• Traumatic Brain Injury• Tuberculosis
57© 2019 TalentMine All Rights Reserved.
Therapeutic-Area Standards Accepted by FDA
Study Data TCG Section 5
CDISC Data Exchange Standards
58
• The Operational Data Model (ODM) is a vendor-neutral, platform-independent, XML-based format for interchange and archive of data from clinical trials, including study data, metadata, and administrative data.
• Study/Trial Design Model (SDM) v1.0 allows organizations to provide rigorous, machine-readable, interchangeable descriptions of the designs of their clinical studies, including treatment plans, eligibility and times and events.
• The CDISC define.xml standard is a Study Data Specification. It is a replacement for the traditional define.pdf, allowing much greater flexibility in the metadata describing the submitted data in a machine-readable format.
• Dataset-XML, initially named “StudyDataSet-XML”, is a new standard used to exchange study datasets in an XML format. The purpose of Dataset-XML is to support the interchange of tabular data for clinical research applications using ODM-based XML technologies.
ww.cdisc.org
© 2019 TalentMine All Rights Reserved.
57
58
-
© 2019 TalentMine. All Rights Reserved.The contents of this document are proprietary.
For class attendee use only. DO NOT DUPLICATE 30
• SAS Version 5 Transport files• Column width should be set to the longest data value.• Files should be split if they exceed 5 GB. Both the split files and the original larger dataset should be submitted.
Study Data Exchange Format
© 2019 TalentMine All Rights Reserved. 59
Study Data TCG, Section 3.3.1 and 3.3.2
eCTD Folder Structure for Datasets
Study Data TCG Section 7.1
60
59
60
-
© 2019 TalentMine. All Rights Reserved.The contents of this document are proprietary.
For class attendee use only. DO NOT DUPLICATE 31
• Variable and Dataset Names: alphanumeric characters only• Variable and Dataset Labels: special characters are allowed but:– No unbalanced apostrophes (e.g., Parkinson’s)– No unbalanced single or double quotes– No unbalanced parentheses or brackets– No use of “” whatsoever
• It should be noted that CDISC uses only letters, numbers, and underscores.• For legacy studies started on or before December 17, 2016, it is permissible to use the underscore character in variable names and dataset names.
Study Data TCG, Sections 3.3.3 through 3.3.7
Study Data Exchange Content Restrictions
© 2019 TalentMine All Rights Reserved. 61
The Role of PhUSE• In 2013, an effort was begun to develop technologies, position papers, and supplemental implementation advice to support and improve the implementation of (CDISC) data standards.
• PhUSE is not developing standards. • FDA is highly involved. • Working Groups were formed
© 2019 TalentMine All Rights Reserved. 62
https://www.phusewiki.org/wiki/index.php?title=CSS_Working_Groupshttps://www.phuse.eu/working‐groups
61
62
-
© 2019 TalentMine. All Rights Reserved.The contents of this document are proprietary.
For class attendee use only. DO NOT DUPLICATE 32
PhUSE Optimizing the Use of Data Standards WG (1)• Identify specific gaps preventing FDA and industry from optimizing the use of standards and collaborate to close those gaps.
• Current projects:• Best Practices for Data Collection Instructions• Best Practices for Metadata Documentation (define.xml versus reviewer's guide)• CDISC Implementation Primer• Clinical Legacy Data Conversion Plan & Report• Data Reviewer's Guide in XML• Data Standards for Non‐Interventional Studies• Define‐XML V2.0 Completion Guidelines and Stylesheet Recommendations• Industry Experiences Submitting Standardised Study Data
© 2019 TalentMine All Rights Reserved. 63
PhUSE Optimizing the Use of Data Standards WG (2)Archived Deliverables– ADRG Completion Guidelines and Examples– nSDRG Completion Guidelines and Template– SDRG Completion, Template, and Examples
© 2019 TalentMine All Rights Reserved. 64
https://www.phuse.eu/css‐archive‐deliverables
63
64
-
© 2019 TalentMine. All Rights Reserved.The contents of this document are proprietary.
For class attendee use only. DO NOT DUPLICATE 33
Additional PhUSE Working Groups
65
Data Transparency Clinical Trials Data Transparency Toolkit
Data De‐identification Toolkit
De‐identification Standards
EMA Policy 0070 Interpretations
GDPR Impact on Data Collection Practices
Policy, Guidance & Materials Reviews
Educating for the Future
Data Engineering Data Science Design Thinking
Emerging Trends & Technologies
Blockchain Technology
Cloud Adoption in the Life Science Industry
Data Visualisation for Clinical Data
Going Translational with Linked Data
Investigating the Use of FHIR in Clinical Research
Key Performance Indicators & Metrics
Machine Learning & Artificial Intelligence
Open Source Technologies in Clinical Research
Real World Evidence
Nonclinical Topics Data Consistency: SEND Datasets and the Study Report
Demystifying Define‐XML Codelists for Nonclinical Studies
Industry SEND Progress Survey
Modeling Endpoints: How to Model Anti‐Drug Antibody Data in Nonclinical Studies
Nonclinical Script Assessment
Nonclinical Study Data Reviewer's Guide
SEND Implementation User Group
SEND Dataset QC Best Practices
Optimizing the Use of Data Standards
Best Practices for Data Collection Instructions
CDISC Implementation Primer
Data Reviewer's Guide in XML
Data Standards for Non‐Interventional Studies
Industry Experiences Submitting Study Data to Regulatory Authorities
Integrated SDTM and ADaM Reviewer's Guide
SDTM ADaM Implementation FAQ
Standard Analyses & Code Sharing
Analyses & Displays White Papers
Best Practices for Quality Control & Validation
Code Sharing (Repository)
Communications, Promotion and Education
GPP in Macro Development
Test Data Factory
© 2019 TalentMine All Rights Reserved.
• Introduction and Learning Objectives• Regulatory Basis for Standardized Electronic Data– FDA Guidance Documents and Technical Specifications
• The Data Standards– CDISC Overview– The Role of PhUSE
© 2019 TalentMine All Rights Reserved. 66
Workshop Outline• Beyond The Data– aCRF– Define– SDRG– SDSP– Software Programs
• Traceability• The Process• Preparing for a Submission
65
66
-
© 2019 TalentMine. All Rights Reserved.The contents of this document are proprietary.
For class attendee use only. DO NOT DUPLICATE 34
• Introduction and Learning Objectives• Regulatory Basis for Standardized Electronic Data– FDA Guidance Documents and Technical Specifications
• The Data Standards– CDISC Overview– The Role of PhUSE
© 2019 TalentMine All Rights Reserved. 67
Workshop Outline• Beyond The Data– aCRF– Define.xml– Reviewer’s Guides– SDSP– Software Programs
• Traceability• The Process• Preparing for a Submission
Annotated Case Report Form(aCRF)• Should be provided as a PDF file named “acrf.pdf”.• Should include all available forms used to collect source data, including treatment assignment
forms.• The text “NOT SUBMITTED” should be annotated onto the aCRF where data are recorded on the
CRF but not submitted, and an explanation for why data was not submitted should appear in the Study Data Reviewer’s Guide.
• Create as a native PDF document. Avoid scanned copies.• Include pages (screens) from any patient reported outcomes devices.
Study Data TCG, Section 4.1.4.6
© 2019 TalentMine All Rights Reserved. 68
67
68
-
© 2019 TalentMine. All Rights Reserved.The contents of this document are proprietary.
For class attendee use only. DO NOT DUPLICATE 35
Data Definition Files (define.xml)• These are the “Table of Contents” for the submitted datasets.• Provide separate files for SEND, SDTM, and ADaM.• Version 2.0 is preferred.• Provide a printable PDF version (define.pdf) if the define.xml cannot be printed. This was an issue with define.xml v1.0.
(Study Data TCG, Section 4.1.4.5).
© 2019 TalentMine All Rights Reserved. 69
Define.xml: Dataset Metadata
70
• Every submitted (e.g., tabulation, analysis) dataset is accompanied by information of up to five levels:
– Dataset level
– Variable level
– Value level
– Codelist level
– Derivation level (algorithms used)
© 2019 TalentMine All Rights Reserved.
69
70
-
© 2019 TalentMine. All Rights Reserved.The contents of this document are proprietary.
For class attendee use only. DO NOT DUPLICATE 36
Define.xml: Dataset-Level Metadata (1)
© 2019 TalentMine All Rights Reserved. 71
Define.xml: Dataset-Level Metadata (2)
© 2019 TalentMine All Rights Reserved. 72
71
72
-
© 2019 TalentMine. All Rights Reserved.The contents of this document are proprietary.
For class attendee use only. DO NOT DUPLICATE 37
Define.xml: Variable-Level Metadata (1)
© 2019 TalentMine All Rights Reserved. 73
Define.xml: Variable-Level Metadata (2)
© 2019 TalentMine All Rights Reserved. 74
73
74
-
© 2019 TalentMine. All Rights Reserved.The contents of this document are proprietary.
For class attendee use only. DO NOT DUPLICATE 38
Define.xml: Variable-Level Metadata (3)
© 2019 TalentMine All Rights Reserved. 75
• Origin or source of each variable — removed from the models, but should be included in the define file. – Assigned: coded terms – Collected: collected data – Derived: age– Protocol: vital signs position– eDT: lab data received electronically
© 2019 TalentMine All Rights Reserved. 76
Define.xml: Variable-Level Metadata (4)
75
76
-
© 2019 TalentMine. All Rights Reserved.The contents of this document are proprietary.
For class attendee use only. DO NOT DUPLICATE 39
• Origin or source of each variable — removed from the models, but should be included in the define file.
© 2019 TalentMine All Rights Reserved. 77
Define.xml: Variable-Level Metadata (4)
SDTMIG SENDIGCollectedDerivedAssigned ProtocoleDT
CollectedDerivedOtherNot Available
Define.xml: Value-Level Metadata (1)
78© 2019 TalentMine All Rights Reserved.
77
78
-
© 2019 TalentMine. All Rights Reserved.The contents of this document are proprietary.
For class attendee use only. DO NOT DUPLICATE 40
Define.xml: Value-Level Metadata (2)
79© 2019 TalentMine All Rights Reserved.
Define.xml: Codelist-Level Metadata
80© 2019 TalentMine All Rights Reserved.
79
80
-
© 2019 TalentMine. All Rights Reserved.The contents of this document are proprietary.
For class attendee use only. DO NOT DUPLICATE 41
Define.xml: Computational Algorithms
81
Method Type Description
Algorithm to derive AEENDY Computation AEENDY = AEENDTC -RFSTDTC+1 if AEENDTC is on or after RFSTDTC. AEENDTC - RFSTDTC
if AEENDTC precedes RFSTDTC
Algorithm to derive AESTDY Computation AESTDY = AESTDTC - RFSTDTC+1 if AESTDTC is on or after RFSTDTC. AESTDTC - RFSTDTC
if AESTDTC precedes RFSTDTC
Algorithm to derive the AETRTEM flag Computation AETRTEM = "Y" if Adverse Event was not present prior to the RFSTDTC, or it was present
prior to the RFSTDTC but increased in severity during the treatment period. Null otherwise.
Algorithm to derive AGE Computation Age at Screening Date (Screening Date - Birth date). For the complete algorithm see the
referenced external document.
Algorithm to derive LBBLFL Computation Safety subjects only: LBBLFL = "Y" for last record with non Null LBORRES on or before the
first dose date (RFSTDTC). Null otherwise.
Algorithm to derive LBDY Computation LBDY = LBDTC-RFSTDTC+1 if LBDTC is on or after RFSTDTC. LBDTC - RFSTDTC if LBDTC
precedes RFSTDTC.
Algorithm to derive LBNRIND Computation Reference Range Indicator based upon standard results and ranges.
© 2019 TalentMine All Rights Reserved.
Study Data Reviewer’s Guide (cSDRG and nSDRG)• Describes any special considerations or directions that may facilitate an FDA reviewer’s use of the submitted data
• Helps the reviewer understand the relationship between the study report and the case report tabulation data
• The Study Data TCG does not define a specific template, but an example of a Study Data Reviewer’s Guide, including a template, completion guidelines and examples, can be found on the PhUSE website (https://www.phuse.eu/css‐deliverables).
© 2019 TalentMine All Rights Reserved. 82
(Study Data TCG, Section 2.2, 1st paragraph
81
82
-
© 2019 TalentMine. All Rights Reserved.The contents of this document are proprietary.
For class attendee use only. DO NOT DUPLICATE 42
cSDRG Contents
83
• The cSDRG (cSDRG.pdf) should include, but is not limited to the following: • Study protocol title, number, and version • Study design • Study overview• CRF data not submitted• Domains present and whether are standard, custom, efficacy, safety, or
have SUPP‐‐ datasets• Data conformance summary• Legacy Data Conversion Plan and Report (as appendix)
© 2019 TalentMine All Rights Reserved.
cSDRG Study Overview Examples
84
• Are the submitted data taken from an ongoing study?• If yes, describe the data cut or database status.• Were the SDTM datasets used as sources for the analysis datasets? • If no, what were the sources of analysis datasets? • Do the submission datasets include screen failures?• If yes, which datasets include screen failure data?• Were any domains planned, but not submitted because no data were collected? • If yes, list domains not submitted.• Are the submitted data a subset of collected data?• If yes, describe the reason that all collected data were not provided.• Is adjudication data present?• If yes, describe the implementation approach and location of the adjudication data.
© 2019 TalentMine All Rights Reserved.
83
84
-
© 2019 TalentMine. All Rights Reserved.The contents of this document are proprietary.
For class attendee use only. DO NOT DUPLICATE 43
Legacy Data Conversion PlanShould:• Describe the legacy data and the process intended for the conversion• Present the results of the conversions, issues encountered and resolved, and outstanding issues• Be included in the cSDRG
© 2019 TalentMine All Rights Reserved. 85
Study Data TCG, Section 8.3.2.2
Study Data Reviewer’s Guide Resources (1)
86
https://www.phusewiki.org/wiki/index.php?title=Study_Data_Reviewer%27s_Guide
85
86
-
© 2019 TalentMine. All Rights Reserved.The contents of this document are proprietary.
For class attendee use only. DO NOT DUPLICATE 44
Study Data Reviewer’s Guide Resources (2)
87
https://www.phuse.eu/css‐deliverables
Analysis Data Reviewer’s Guide (ADRG) (1) Provides the FDA reviewers with context for analysis datasets and terminology Purposefully duplicates limited information found in other submission documents in order to
provide FDA reviewers with a single point of orientation to the analysis datasets The Study Data TCG does not define a specific template for the Analysis Data Reviewer’s Guide,
but an example of an Analysis Data Reviewer’s Guide, including a template, completion guidelines and examples, can be found on the PhUSE website(https://www.phuse.eu/css‐deliverables).
© 2019 TalentMine All Rights Reserved. 88
Study Data TCG, Section 2.3
87
88
-
© 2019 TalentMine. All Rights Reserved.The contents of this document are proprietary.
For class attendee use only. DO NOT DUPLICATE 45
Analysis Data Reviewer’s Guide (ADRG) (2)• Recommended as an important part of a standards‐compliant analysis data submission for clinical trials
• Provides FDA reviewers with context for analysis datasets and terminology• Provides a summary of ADaM conformance findings• Purposefully duplicates limited information found in other submission documents in order to provide FDA reviewers with a single point of orientation to the analysis datasets
• Specific template not provided, but an example, template, and completion guidelines can be found on the PhUSE website (https://www.phuse.eu/css‐deliverables).
Study Data TCG Section 2.3
© 2019 TalentMine All Rights Reserved. 89
• One per submission• Describes the submission of standardized study data.• Assists FDA in identifying potential data standardization issues early in the development
program. • Sponsors may also initiate discussions at the pre‐IND stage. • Prepare and include as part of IND.• Update / submit as additional studies are planned.
Study Data Standardization Plan (1)
Study Data TCG, Section 2.1
© 2019 TalentMine All Rights Reserved. 90
89
90
-
© 2019 TalentMine. All Rights Reserved.The contents of this document are proprietary.
For class attendee use only. DO NOT DUPLICATE 46
91
The Standardization Plan should include, but is not limited to the following: 1. List of the planned studies 2. Type of studies3. Study designs (e.g., parallel, cross‐over)4. Planned data standards, formats, and terminologies and their versions, or a
justification of studies that may not conform to the currently supported standards
© 2019 TalentMine All Rights Reserved.
Study Data Standardization Plan (2)
Study Data Standardization PlanPhUSE Resources
https://www.phusewiki.org/wiki/index.php?title=Study_Data_Standardization_Plan_(SDSP)
92
91
92
-
© 2019 TalentMine. All Rights Reserved.The contents of this document are proprietary.
For class attendee use only. DO NOT DUPLICATE 47
• Sponsors should provide the software programs used to create all ADaM datasets, and to generate tables and figures associated with primary and secondary efficacy analyses.
• The specific software utilized should be specified in the ADRG.• Software programs should include sufficient documentation to allow the reviewer to understand the submitted programs.
• Software programs should be provided as ASCII text files.
Study Data TCG, Section 4.1.2.10
© 2019 TalentMine All Rights Reserved. 93
Software Programs
• Introduction and Learning Objectives• Regulatory Basis for Standardized Electronic Data– FDA Guidance Documents and Technical Specifications
• The Data Standards– CDISC Overview– The Role of PhUSE
© 2019 TalentMine All Rights Reserved. 94
Workshop Outline• Beyond The Data– aCRF– Define– SDRG– SDSP– Software Programs
• Traceability• The Process• Preparing for a Submission
93
94
-
© 2019 TalentMine. All Rights Reserved.The contents of this document are proprietary.
For class attendee use only. DO NOT DUPLICATE 48
Traceability• Traceability can be enhanced when studies are prospectively designed to collect data using a standardized CRF, e.g., CDASH.
• Traceability can be further enhanced when a flow diagram is submitted showing how data move from collection through preparation and submission to the Agency.
© 2019 TalentMine All Rights Reserved. 95
Study Data TCG Section 8.3.1
Traceability and Legacy Data Conversion• Sponsors should use processes for legacy data conversion that account for traceability. • To mitigate traceability issues, FDA recommends:
• Prepare and submit a Legacy Data Conversion Plan & Report.• Incorporate the Legacy Data Conversion Plan & Report into the cSDRG in order to record significant data issues, clarification and explanations of traceability.
• In some cases legacy data may also need to be submitted.• Sponsors should provide two separate CRF annotations:
• Based on the original legacy data• Based on the converted SDTM data.
• It may be helpful to provide mapping specifications from legacy to SDTM data (not in Study Data TCG).
© 2019 TalentMine All Rights Reserved. 96
Study Data TCG Section 8.3.2
95
96
-
© 2019 TalentMine. All Rights Reserved.The contents of this document are proprietary.
For class attendee use only. DO NOT DUPLICATE 49
• Introduction and Learning Objectives• Regulatory Basis for Standardized Electronic Data– FDA Guidance Documents and Technical Specifications
• The Data Standards– CDISC Overview– The Role of PhUSE
© 2019 TalentMine All Rights Reserved. 97
Workshop Outline• Beyond The Data– aCRF– Define– SDRG– SDSP– Software Programs
• Traceability• The Process• Preparing for a Submission
Study Start (1)• Ideally, create database based on the STDM.• Ideally, create CRFs based on CDASH and using CDASH/SDTM Terminology.• Create define.xml file(s) for datasets to be submitted. • Create the aCRF.• Develop protocol with the goal of being consistent with CDISC Controlled Terminology.
© 2019 TalentMine All Rights Reserved. 98
97
98
-
© 2019 TalentMine. All Rights Reserved.The contents of this document are proprietary.
For class attendee use only. DO NOT DUPLICATE 50
Study Start (2)• If using legacy database, create all mapping specifications to SDTM domains, variables, and terminology.
• Develop SDTM‐compliant data‐transfer specifications for data from external vendors (e.g., Labs, ECGs, PK). If not, create mapping specs.
• Create SDTM/SDTMIG Trial Design Domains– This information should be able to be obtained from the protocol and/or CRFs– Doing this at the beginning can help eliminate inconsistencies with the protocol and CRFs
© 2019 TalentMine All Rights Reserved. 99
• Introduction and Learning Objectives• Regulatory Basis for Standardized Electronic Data– FDA Guidance Documents and Technical Specifications
• The Data Standards– CDISC Overview– The Role of PhUSE
© 2019 TalentMine All Rights Reserved. 100
Workshop Outline• Beyond The Data– aCRF– Define– SDRG– SDSP– Software Programs
• Traceability• The Process• Preparing for a Submission
99
100
-
© 2019 TalentMine. All Rights Reserved.The contents of this document are proprietary.
For class attendee use only. DO NOT DUPLICATE 51
Preparing for Submission: Data Packages
© 2019 TalentMine All Rights Reserved. 101
Component Tabulation Analysis Legacy DataDatasets Based on the SDTMIG, SENDIG Based on the ADaMIG Sponsor formatDefine.xml √ √ √aCRF Mappings to SDTMIG/CDASH N/A Annotated to legacy
datasetsReviewer’s Guide cSDRG, nSDRG ADRG cSDRG, nSDRGSDSP One for a submission N/ASoftware Programs Possible if LDC √ Not mentioned in TCG,
but folder exists in eCTD
CRO
Vendor
SponsorInternal Data
EDC
SubmissionData
Preparing for Submission:Identify Data Sources and Paths
102© 2019 TalentMine All Rights Reserved.
101
102
-
© 2019 TalentMine. All Rights Reserved.The contents of this document are proprietary.
For class attendee use only. DO NOT DUPLICATE 52
Preparing for Submission:Make Decisions
103
What standard(s) will be used? Will there be an internal standard to which CROs/vendors will be held? Will there be legacy‐data conversion?
© 2019 TalentMine All Rights Reserved.
Preparing for Submission:Determine Responsibilities
104
Who will manage the standard(s)? If there are multiple partners for conversion or creation of
SDTM datasets, who will: Ensure consistency of data? Manage resolution of differences?
Who will ensure datasets are compliant? Via validation tools Via human review
Who will prepare other necessary documentation? cSDRG SDSP define.xml
© 2019 TalentMine All Rights Reserved.
103
104
-
© 2019 TalentMine. All Rights Reserved.The contents of this document are proprietary.
For class attendee use only. DO NOT DUPLICATE 53
Learning Objectives Reviewed
• Understand the regulatory basis for the requirement for electronic data and standardized electronic study data
• Become aware of the specific data standards the agency expects• Recognize that additional documents/files are required to support the submission of study data
© 2019 TalentMine All Rights Reserved. 105
FDA Study Data Standards Resources
106
http://www.fda.gov/forindustry/datastandards/studydatastandards/default.htm
1. FDA Data Standards Resources• FDA Data Standards Catalog v6.1 September 9, 2019• Study Data for Submission to CDER and CBER• Data Standards and Terminology Standards for Information Submitted to CDRH• Study Data for Submission to CDER and CBER
2. FDA Guidance Documents• Electronic Submissions Guidance List• Providing Regulatory Submissions in Electronic Format - Standardized Study Data:
Guidance for Industry (Dec. 2014)• Providing Regulatory Submissions in Electronic Format - Submissions Under
Section 745A(a) of the FD&C Act: Guidance for Industry (Dec. 2014)• Providing Regulatory Submissions in Electronic Format - Certain Human
Pharmaceutical Product Applications and Related Submissions Using the eCTD Specifications: Guidance for Industry(May 17, 2015)
3. Technical Guides• Study Data Technical Conformance Guide v. 4.3, March 2019• Technical Rejection Criteria for Study Data
4. Standardization Plan Recommendations• CDER/CBER Study Data Standardization Plan Recommendations
© 2019 TalentMine All Rights Reserved.
105
106
-
© 2019 TalentMine. All Rights Reserved.The contents of this document are proprietary.
For class attendee use only. DO NOT DUPLICATE 54
Fred WoodVice President, Consulting ServicesSDTM and SEND Implementation [email protected]
Data Standards Consulting Group, A Division of TalentMineProviding Expert Consulting and Training on:• SDTM• ADaM• CDASH• SEND
107© 2019 TalentMine All Rights Reserved.
Contact Information
107