Data Standards for Drug 
and Biological Product 
Submissions Containing 
Real-World Data  
Guidance for Industry 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
U.S. Department of Health and Human Services 
Food and Drug Administration 
  Center for Drug Evaluation and Research (CDER)   
Center for Biologics Evaluation and Research (CBER) 
 
December 2023 
Real-World Data/Real-World Evidence (RWD/RWE) 
   
Data Standards for Drug 
and Biological Product 
Submissions Containing 
Real-World Data  
Guidance for Industry 
 
Additional copies are available from: 
Office of Communications, Division of Drug Information  
Center for Drug Evaluation and Research 
Food and Drug Administration 
10001 New Hampshire Ave., Hillandale Bldg., 4th Floor  
Silver Spring, MD 20993-0002  
Phone: 855-543-3784 or 301-796-3400; Fax: 301-431-6353 
Email: druginfo@fda.hhs.gov  
https://www.fda.gov/drugs/guidance-compliance-regulatory-information/guidances-drugs 
 
and/or 
 
Office of Communication, Outreach and Development  
Center for Biologics Evaluation and Research 
 Food and Drug Administration 
10903 New Hampshire Ave., Bldg. 71, Room 3128 
Silver Spring, MD 20993-0002 
Phone: 800-835-4709 or 240-402-8010 
Email: ocod@fda.hhs.gov 
https://www.fda.gov/vaccines-blood-biologics/guidance-compliance-regulatory-information-biologics/biologics-guidances     
 
U.S. Department of Health and Human Services 
Food and Drug Administration 
Center for Drug Evaluation and Research (CDER) 
Center for Biologics Evaluation and Research (CBER) 
 
December 2023 
Real-World Data/Real-World Evidence (RWD/RWE) 
 
  Contains Nonbinding Recommendations 
TABLE OF CONTENTS 
 
 
I.  INTRODUCTION AND SCOPE ..................................................................................... 1 
II.  REGULATORY BACKGROUND.................................................................................. 2 
III.  APPLYING CURRENTLY SUPPORTED DATA STANDARDS TO STUDY DATA 
DERIVED FROM REAL-WORLD DATA SOURCES ............................................................ 3 
A.  Challenges in Real-World Data Standardization ........................................................................ 3 
B.  Documentation of Processes for Managing Real-World Data ................................................... 4 
C.  Considerations for Conforming Real-World Data to Currently Supported FDA Study Data 
Standards ................................................................................................................................................ 4 
D.  Considerations for Mapping Real-World Data To Study Data Submission Standards .......... 5 
E.  Considerations for Data Transformations ................................................................................... 6 
APPENDIX:  EXAMPLES OF MAPPING HEALTH CARE DATA TO CDISC SDTM .... 8 
  Contains Nonbinding Recommendations 
Data Standards for Drug and Biological Product Submissions 
Containing Real-World Data 
Guidance for Industry1 
 
This guidance represents the current thinking of the Food and Drug Administration (FDA or Agency) on 
this topic.  It does not establish any rights for any person and is not binding on FDA or the public.  You 
can use an alternative approach if it satisfies the requirements of the applicable statutes and regulations.  
To discuss an alternative approach, contact the FDA staff responsible for this guidance as listed on the 
title page.   
 
 
 
 
I.  INTRODUCTION AND SCOPE 
 
21st Century Cures Act and Real-World Data 
 
The 21st Century Cures Act,2 signed into law on December 13, 2016, is intended to accelerate 
medical product development and bring innovations faster and more efficiently to the patients 
who need them.  Among other provisions, the 21st Century Cures Act added section 505F to the 
Federal Food, Drug, and Cosmetic Act (FD&C Act) (21 U.S.C. 355g).  Pursuant to this action, 
calling for FDA to issue guidance on the use of real-world evidence (RWE) in regulatory 
decision-making, FDA has created a framework for a program to evaluate the potential use of 
real-world data (RWD) to generate RWE to help support the approval of new indication(s) for 
drugs3 already approved under section 505(c) of the FD&C Act (21 U.S.C. 355(c)) or to help 
support or satisfy post-approval study requirements (RWE Program).4 
 
This guidance provides recommendations to sponsors for complying with section 745A(a) of the 
FD&C Act (21 U.S.C. 379k-1(a)) when submitting RWD as study data in applicable drug 
submissions.  FDA is issuing this guidance as part of its RWE Program and to satisfy, in part, the 
mandate under section 505F of the FD&C Act (21 U.S.C. 355g) to issue guidance on the use of 
RWE in regulatory decision-making.5   
 
1 This guidance has been prepared by the Center for Drug Evaluation and Research (CDER) in cooperation with the 
Center for Biologics Evaluation and Research (CBER) at the Food and Drug Administration.  
2 Public Law 114-255.  
3 For the purposes of this guidance, all references to drugs include both human drugs and biological products.   
4 See the document Framework for FDAs Real-World Evidence Program (December 2018), available at 
https://www.fda.gov/media/120060/download.  The framework and RWE Program also cover biological products 
licensed under the Public Health Service Act. 
5 See section 505F(e) of the FD&C Act. 
  1  Contains Nonbinding Recommendations 
This guidance addresses considerations for the use of data standards6 currently supported by 
FDA in applicable drug submissions containing study data7 derived from RWD sources.  For the 
purposes of this guidance, FDA defines RWD as data relating to patient health status and/or the 
delivery of health care routinely collected from a variety of sources.  Examples of RWD include 
data from electronic health records (EHRs); medical claims data; data from product and disease 
registries;8 patient-generated data (including data from in-home-use settings); and data gathered 
from other sources that can inform on health status, such as mobile devices.   
 
In general, FDAs guidance documents do not establish legally enforceable responsibilities.  
Instead, guidances describe the Agencys current thinking on a topic and should be viewed only  
as recommendations, unless specific regulatory or statutory requirements are cited.  The use of 
the word should in FDA guidance means that something is suggested or recommended, but not 
required. 
 
 
II.  REGULATORY BACKGROUND 
 
Under section 745A(a) of the FD&C Act, at least 24 months after the issuance of a final 
guidance document in which FDA has specified the electronic format for submitting certain 
submission types to the Agency, such content must be submitted electronically and in the format 
specified by FDA.9  The guidance for industry Providing Regulatory Submissions in Electronic 
FormatStandardized Study Data (Study Data Guidance)10 and the technical specifications 
referenced therein describe electronic submission requirements under section 745A(a) of the 
FD&C Act for clinical and nonclinical study data contained in new drug applications (NDAs), 
abbreviated new drug applications (ANDAs), certain biologics license applications (BLAs), and 
certain investigational new drug applications (INDs) submitted to CDER or CBER.11  Given that 
these electronic submission requirements apply to study data submitted in the covered 
application types, they apply to RWD that is submitted as study data in such applications.  That 
is, RWD submitted as study data to NDAs, ANDAs, certain BLAs, and certain INDs, as further 
described in section II.A of the Study Data Guidance, must be in an electronic format that the 
 
6 For the purposes of this document, the term data standards means defined rules, conventions, guidelines, 
characteristics, methods, formats, and terminologies that provide structure and consistency for exchange and 
utilization of data (see https://www.cdisc.org/standards/glossary). 
7 See FDAs guidance for industry Providing Regulatory Submissions in Electronic FormatStandardized Study 
Data (June 2021).  We update guidances periodically.  For the most recent version of a guidance, check the FDA 
guidance web page at https://www.fda.gov/regulatory-information/search-fda-guidance-documents. 
https://www.fda.gov/regulatory-information/search-fda-guidance-documents/providing-regulatory-submissions-
electronic-format-standardized-study-data  
8 For the purposes of this guidance, the term registries means organized systems that collect clinical or other data in 
standardized formats for populations defined by a particular disease, condition, or exposure. 
9 For additional information on how FDA interprets and intends to implement the electronic submission 
requirements of section 745A(a) of the FD&C Act, see the guidance for industry Providing Regulatory Submissions 
in Electronic FormatSubmissions Under Section 745A(a) of the Federal Food, Drug, and Cosmetic Act (December 
2014). 
10 For additional information, see the guidance for industry Providing Regulatory Submissions in Electronic 
FormatStandardized Study Data (June 2021).     
11 See section II of the Study Data Guidance for more information on the types of submissions subject to electronic 
submission requirements for standardized study data and what submissions are exempt from such requirements. 
  2  Contains Nonbinding Recommendations 
Agency can process, review, and archive, unless such submission is exempt from the electronic 
submission requirements or if FDA has granted a waiver.12  Currently, as stated in the Study 
Data Guidance, the Agency can process, review, and archive electronic submissions of clinical 
and nonclinical study data (including those derived from RWD sources) that use the standards 
specified in the Data Standards Catalog (Catalog).13  As that guidance explains, the Catalog 
provides a listing of currently supported14 and/or required standards, their uses, the date FDA 
will begin (or has begun) to support a particular standard, the date such support ends (or will 
end), the date the requirement to use a particular standard will begin (or has begun), the date 
such requirement ends (or will end), and other pertinent information.   
 
FDA is issuing this guidance to provide recommendations to sponsors for complying with 
section 745A(a) of the FD&C Act using standards specified in the Catalog when submitting 
study data derived from RWD sources in applicable drug submissions.   
 
 
III.  APPLYING CURRENTLY SUPPORTED DATA STANDARDS TO STUDY DATA 
DERIVED FROM REAL-WORLD DATA SOURCES  
 
A.  Challenges in Real-World Data Standardization  
 
FDA recognizes the challenges involved in standardizing study data derived from RWD sources 
for inclusion in applicable drug submissions.  These challenges include but are not limited to:  
 
  The variety of RWD sources and their inconsistent formats (e.g., EHR, registry) 
 
  The potential use of more than one type of RWD source in a study (such as combining 
EHR and claims data)  
 
  The differences in source data captured regionally and globally using different standards, 
terminologies,15 and exchange formats16 for the representation of the same or similar data 
elements17 
 
  Certain information only existing in non-structured documentation (such as text in 
physician notes) 
 
 
12  Sponsors or applicants may apply for a waiver from the requirement to use specific versions of FDA-supported 
standards for the submission of study data using the waiver request process described in section II.D of the Study 
Data Guidance. 
13 The Catalog is available at http://www.fda.gov/forindustry/datastandards/studydatastandards/default.htm.  
14 For the purposes of this document, the term supported means the receiving Center has established processes and 
technology to support receiving, processing, reviewing, and archiving files in the specified standard. 
15 For the purposes of this document, the term terminologies means the body of terms used for particular technical 
application to standardize a medical term for the submission of nonclinical and clinical study data. 
16 For the purposes of this document, the term exchange format means a data format for converting from one file or 
database structure to another.  For example, XML is commonly used as a data exchange format. 
17 See data elements at https://csrc.nist.gov/glossary/term/data_element.  
  3  Contains Nonbinding Recommendations 
  A wide range of methods and algorithms which could be used to create datasets intended 
to aggregate data 
 
  The many aspects of health care data that can affect the overall quality of the data, 
including business processes and database structure, inconsistent vocabularies and coding 
systems, and de-identification methodologies used to protect patient data when shared 
 
  The various levels of access a sponsor has to any data sources used in the study  
 
Approaches to these challenges will depend on the specific data being used and the research 
being conducted.  For this reason, sponsors should discuss such issues with the appropriate FDA 
review division(s) as early as possible,18 preferably before the sponsor conducts the study.   
 
B.  Documentation of Processes for Managing Real-World Data 
 
During data curation19 and data transformation,20 adequate processes should be in place to ensure 
confidence in the resultant data.  Documentation of these processes may include but is not limited 
to electronic documentation (e.g., audit trails, quality control procedures, etc.) of data additions, 
deletions, or alterations from the source data system to the final study analytic data set(s).  
Sponsors should also document in their applicable drug submission changes to data to conform 
to the current FDA-supported data standards, and the potential impacts of these changes.  For 
more information, see the Study Data Technical Conformance Guide21 (TCG), which 
supplements the Study Data Guidance and standards listed in the Catalog, to provide 
specifications, recommendations, and general considerations on how to submit standardized 
study data and documentation using FDA-supported data standards located in the Catalog.  
 
C.  Considerations for Conforming Real-World Data to Currently Supported 
FDA Study Data Standards 
 
The FDA Data Standards Catalog is updated periodically to reflect changes to the supported and 
required data standards, exchange formats, and terminologies that FDA can process, review, and 
archive.  FDA plans to update the Catalog, and/or issue other guidance documents, to reflect 
standards for study data that are derived from RWD sources as they are developed and evaluated.  
Currently, and absent a waiver, sponsors submitting clinical and nonclinical study data 
(including those derived from RWD sources) in submissions subject to section 745A(a) of the 
FD&C Act are required to use the formats described in the Study Data Guidance and the 
supported study data standards listed in the Catalog.  Sponsors should refer to the specifications, 
recommendations, and general considerations provided in the TCG when submitting study data 
 
18 See the draft guidance for industry Formal Meetings Between the FDA and Sponsors or Applicants of PDUFA 
Products (December 2017) available at the FDA guidance web page.  When final, this guidance will represent 
FDAs current thinking on this topic. 
19 For the purposes of this document, the term data curation means processing of source data through the application 
of standards for exchange, integration, sharing, and retrieval. 
20 For the purposes of this document, the term data transformation means the process of converting data from one 
format or structure into another format or structure. 
21 The Study Data Technical Conformance Guide is available at https://www.fda.gov/industry/fda-resources-data-
standards/study-data-standards-resources. 
  4  Contains Nonbinding Recommendations 
in an applicable submission to FDA.  When seeking to conform RWD to data standards 
supported by FDA, sponsors should consider the relevant data transformations, conversions, or 
mappings22 that may be needed to produce study datasets in required formats in an applicable 
drug submission.  
 
Sponsors should discuss, as early as possible, with the appropriate FDA review division, any 
planned submission of study data derived from RWD sources in an applicable submission and 
their approaches to mapping and transformation of data.  Such discussions should include 
approaches for taking data from its original RWD format to intermediary format(s), including 
those used for analysis, and ultimately to the study data set prepared for submission to FDA 
(using the applicable FDA-supported data standards as listed in the Catalog).  Sponsors should 
describe these approaches, including in the protocol, data management plan, and/or final study 
reports.   
 
FDA recognizes that a range of approaches may be used to apply the supported study data 
standards (e.g., Clinical Data Interchange Standards Consortiums (CDISCs) Study Data 
Tabulation Model (SDTM) or Analysis Data Model (ADaM)) to RWD sources such as EHR or 
claims data.  FDA encourages sponsors to discuss such approaches with FDA.23  With adequate 
documentation of the conformance methods used and their rationale, study data derived from 
RWD can be transformed into SDTM and ADaM datasets and submitted to FDA in an applicable 
submission.   
 
D.  Considerations for Mapping Real-World Data To Study Data Submission 
Standards 
 
FDA is aware that, for nearly every data domain,24 there is wide divergence in the terminologies 
used and their precise meaning between RWD sources and FDA-supported/required data 
standards.  Examples range from the meaning and specific terms used for race/ethnicity, 
terminology systems for medications, and interpretation of the measurements of vital signs from 
health care records.  Even for seemingly similar variables, there can be differences in the way 
these variables are defined between RWD sources and FDA-supported data standards.  For 
example, sex as a variable may be codified in CDISCs terminology as a concept based on 
physical characteristics, whereas EHRs may, in some cases, use gender identity.  In such cases, 
sponsors should document the potential impact of mapping the sex variable or other variables to 
CDISCs terminology on the study findings.   
 
The sponsor should select an appropriate mapping approach that best fits the characteristics of 
the data and the nature of the study.  Sponsors should explain the rationale for the chosen method 
 
22 For the purposes of this document, the term mapping means the process of defining data element relationships 
between two distinct data models. 
23 Questions regarding data standards for electronic study data can be submitted to CDER-edata@fda.hhs.gov  or 
CBER-edata@fda.hhs.gov for submissions to CDER or CBER, respectively. 
24 For the purposes of this document, the term data domain means a collection of logically related observations 
(with a common, specific topic) that are normally collected for all subjects in a clinical investigation.  NOTE: The 
logic of the relationship may pertain to the scientific subject matter of the data or to its role in the trial/study.  
Example domains include laboratory test results, adverse events, concomitant medications 
(https://www.cdisc.org/kb/articles/domain-vs-dataset-whats-difference). 
  5  Contains Nonbinding Recommendations 
in the Study Data Reviewers Guide.25  Additionally, documentation of the sponsors rationale 
for choosing particular data elements from currently supported study data standards to represent 
study data derived from RWD sources is critical.  The sponsor should provide a description of 
the general approach and anticipated impact of data mapping as a part of to the Study Data 
Reviewers Guide to highlight the domains involved.  Furthermore, the sponsor should include a 
data dictionary that documents the definition of every data element derived from RWD sources 
that were mapped to the study data standard and all relevant information about the element, such 
as its relationships to other data, origin, usage, and format.  The Study Data Reviewers Guide 
can also be used to guide reviewers to detailed mappings which can be placed in the Define-
XML file26 and data domain files (see the Appendix for illustrative examples of possible ways to 
use Define-XML for this purpose).  At any time, sponsors can consult the most recent version of 
the TCG to see FDAs current thinking on the use of Define-XML and the Study Data 
Reviewers Guide.   
 
E.  Considerations for Data Transformations 
 
Sponsors may encounter challenges when transforming RWD into data that are consistent with 
FDA-supported data standards.  Examples of these challenges include (but are not limited to) 
management of semantic concepts (terms) that are present at multiple locations in a health record 
(such as medication information), inconsistent coding or miscoding of concepts (e.g., drugs or 
diagnoses), changes in data collection or coding practices (e.g., International Classification of 
Diseases-9 (ICD-9) and ICD-10 codes) that occurred during the study, or missing information 
(either because information is not typically recorded in health care settings or due to inconsistent 
data entry).   
 
Sponsors should document data challenges encountered during transformation to an FDA-
supported data standard and a justification of their approach to enable the application of an FDA-
supported data standard.   Detailed representation of the mapping of standards and terminologies 
used when transforming data to current study data standards can be handled using the Define-
XML (see the Appendix) and domain data files.  In addition, for more complex discussions, 
narrative descriptions should also be presented in the Study Data Reviewers Guide, either in the 
body or as an appendix, with appropriate directions for reviewers to the Define-XML and 
dataset/domains for more detail, if needed.   
 
 
  
 
25 For the purposes of this document a Study Data Reviewers Guide means a document provided by sponsors to 
FDA to describe any special considerations or directions or conformance issues that may facilitate an FDA 
reviewers use of the submitted data and may help the reviewer understand the relationships between the study 
report and the data.  For more information, see the Study Data Technical Conformance Guide, available at 
https://www.fda.gov/regulatory-information/search-fda-guidance-documents/study-data-technical-conformance-
guide-technical-specifications-document. 
26 See description of Define-XML file at https://www.cdisc.org/standards/data-exchange/define-xml.  
  6  Contains Nonbinding Recommendations 
APPENDIX:  EXAMPLES OF MAPPING HEALTH CARE DATA TO CDISC SDTM 
 
Differences in the coding systems used between real-world data (RWD) and traditional clinical 
trial data can usually be addressed using the Define-XML file, which is included in all standard 
Study Data Tabulation Model (SDTM) submissions.  The Define-XML file, along with the 
appropriate use of Alias data element, provides one mechanism for communicating the 
transformation of external coding systems to the appropriate SDTM controlled terminology.27 
 
An example of this approach involves race/ethnicity data, where the Food and Drug 
administration (FDA) anticipates both heterogeneity among electronic health records (EHRs) as 
well as between EHR and Clinical Data Interchange Standards Consortium (CDISC) 
terminologies.  In the guidance for industry Collection of Race and Ethnicity Data in Clinical 
Trials (October 2016), FDA recommends that at least five specific categories be used to define 
race: 
 
(1) American Indian or Alaska Native  
(2) Asian  
(3) Black or African American  
(4) Native Hawaiian or Other Pacific Islander 
(5) White 
 
RWD sources, however, may not follow the same system of coding.  Given that FDA 
recommends using the race and ethnicity categorization outlined in the Collection of Race and 
Ethnicity Data in Clinical Trials guidance mentioned above, a sponsor should map the RWD 
terminology system to the relevant SDTM terminology.  To achieve this objective, the Alias 
element in Define-XML file can be used to document the conversions to a single nomenclature 
while ensuring traceability.28   
 
Table 1 illustrates how race can be transformed from non-standardized to standardized data using 
FDA-supported data standards.  In Table 1, the Alias column shows the original codes present in 
an EHR system and the Code column shows the relevant mapped term in the current FDA-
supported CDISC controlled terminology:  
   
 
27 For the purposes of this document, a controlled terminology means a finite set of values that represent the only 
allowed values for a data item.  These values may be codes, text, or numeric.  (CDISC Glossary at 
https://www.cdisc.org/standards/glossary.)  
28 For the purposes of this document, traceability means documentation of curation and transformation procedures 
used throughout the data life cycle. 
  8  Contains Nonbinding Recommendations 
Table 1: Approach To Using Define-XML To Indicate Decision Involved in Transforming Non-
Standardized Data (Race Data) To Standardized Data (i.e., SDTM and ADaM) 
Illustrative example of an approach representing cross-mapping of coding systems, in this case for Race data, to CDISC coding 
in the Define-XML file.  Note that this table does not recommend how to map coding systems to CDISC terminology.  
Additionally, this table demonstrates only one possible approach out of many for representing the mapping choices made.   
 
Race [RACE, C74457]   
Permitted Value (Code)*  Display Value (Alias)** 
AMERICAN INDIAN OR ALASKA NATIVE [C41259]  American Indian or Alaska Native, 
Native American, Native of Alaska; Context: 
EHR Mapping 
ASIAN [C41260]  Asian, Chinese; Context: EHR Mapping 
BLACK OR AFRICAN AMERICAN [C16352]  Black or African American, Black; Context: 
EHR Mapping 
NATIVE HAWAIIAN OR OTHER PACIFIC ISLANDER  Native Hawaiian or Other Pacific Islander, 
[C41219]  Samoan; Context: EHR Mapping 
OTHER [*]  Other; Context: EHR Mapping 
WHITE [C41261]  White, Mexican; Context: EHR Mapping 
 
*Permitted Value (Code): vocabulary that is provided in the study data tabulations and conformant with CDISC controlled 
terminologies. 
**Display Value (Alias): vocabulary that was used in the original data set (i.e., EHR value).  Code/Alias: Respective CDISC 
elements. 
 
Differences in controlled terminology between RWD systems and FDA submission data 
standards may make mapping terminology challenging.  Furthermore, FDA is aware that in non-
interventional studies,29 a sponsor may use data aggregated from multiple RWD systems.  Such 
situations can complicate the use of terminologies further, since different RWD sources, such as 
EHRs, might use different coding systems for the same concept or might use the same coding 
system but use different default codes for the same item.   
 
Various approaches can be applied to permit the use of RWD in applicable drug submissions.  
Examples of potential approaches are: (1) translating the codes to their mapped structured 
definitions with subsequent mapping to appropriate CDISC controlled terminologies, which 
provides the most detail but is labor-intensive; or (2) alternatively mapping all original codes to 
the least granular analogous codes, and then mapping those to CDISC controlled terminologies, 
which is less labor-intensive yet necessitates that detail of a more specific categorization will not 
be represented in the submitted, standardized dataset.  It is up to the sponsors to determine the 
best approach to mediating data transformation, as well as to document and justify their approach 
accordingly.  However, if details that are essential to the consideration of the safety and 
effectiveness of a drug are absent, the latter approach may not be appropriate.  Whatever 
approach is used, the application of Alias to achieve CDISC standard controlled terminology is 
one mechanism to document the normalization of nomenclature into a format developed by 
CDISC.   
 
An example where concepts and terminology do not map precisely and directly is the SDTM 
intervention domain capturing drugs prescribed.  Domains containing drugs prescribed data may 
be mapped to a template SDTM intervention domain.  (FDA anticipates that an EHR system may 
 
29 For the purposes of this document, a non-interventional study is a type of study in which patients are not assigned 
to a study arm according to a protocol, but instead receive the drug of interest during routine clinical care. 
  9  Contains Nonbinding Recommendations 
use prescription coding from RxNorm,30 FDAs National Drug Code (NDC),31 or other such 
systems.)  Additionally, and unless a sponsor uses EHR data where the prescription dispensing 
information is retained or opts to link EHR information with medical claims data, uncertainty 
will persist regarding the actual prescription (e.g., whether a generic pharmaceutical agent was 
substituted).  In such cases, sponsors may apply the Alias element within Define-XML to 
normalize the coding systems (as illustrated in Table 2), where the final dataset (see Table 3) will 
have prescription dosing information uniformly reflecting the less specific prescription coding 
system. 
 
The standard modeling would be accompanied by the Define-XML code list as follows: 
 
Table 2: Approach To Using Define-XML To Indicate Decision Involved in Transforming Non-
Standardized Data (Drugs Prescribed) to Standardized Data (i.e., SDTM and ADaM) 
Illustrative example of an approach to representing cross-mapping of coding systems, in this case for prescription data, to 
CDISC coding in the Define-XML file.  Note that this table does not recommend how to map coding systems to CDISC 
terminology.  Additionally, this table demonstrates only one possible approach out of many for representing the mapping choices 
made. 
Permitted Value (Code)*   Display Value (Alias)**   
FLUoxetine   FLUoxetine 40 milligram (mg) Oral Capsule, RxCUI = 383919, 0093-
7198-56, FLUoxetine 40 mg Oral Capsule Generic Permitted; Context: 
EHR Mapping 
PROzac   PROzac 40 mg Oral Capsule, RxCUI = 313989, 0777-3107-30; Context: 
EHR Mapping 
*Permitted Value (Code): vocabulary that is provided in the study data tabulation. 
**Display Value (Alias): vocabulary that was used in the original data set (i.e., EHR value).  Code/Alias: Respective CDISC 
elements. 
 
The standard modeling of prescription data in the domain file would appear as shown below 
(Table 3): 
 
Table 3: Example of the Drugs Prescribed Data in the Respective Domain Upon Mapping 
Illustrative example of an approach to representing the values from data, in this case for prescription data, to CDISC format in 
the relevant data domain file.  Note that this table does not recommend how to map data to CDISC standards.  Additionally, this 
table demonstrates only one possible approach out of many for representing the mapping choices made.  The column headers 
represent CDISC data elements.  For more information, see https://www.cdisc.org/standards/foundational/sdtm. 
Original  --TRT   --MODIFY   --Alias   --DOSE   --DOSU   --ROUTE   --DOSFRM  
Value (from    
original 
dataset) 
FLUoxetine  FLUoxetine  To be populated Generic Drug  40   mg   ORAL   CAPSULE  
40 mg Oral     by the sponsor  Name in WHO 
Capsule   to assist in  Drug32 
coding to  (either from 
standard  original data 
terminology   system or 
assigned by 
medical coding 
 
30 See https://www.nlm.nih.gov/research/umls/rxnorm/index.html. 
31 See https://www.fda.gov/drugs/drug-approvals-and-databases/national-drug-code-directory. 
32 World Health Organization's Drug Dictionary, see https://who-umc.org/whodrug/. 
  10  Contains Nonbinding Recommendations 
vendor for 
sponsor)  
FLUoxetine  FLUoxetine  (same as  (same as  40   mg   ORAL   CAPSULE  
40 mg Oral     above)   above) 
Capsule 
Generic 
Permitted  
RxCUI =  FLUoxetine  (same as  (same as             
383919   above)   above) 
0093-7198- FLUoxetine  (same as  (same as             
56   above)   above) 
PROzac 40  PROzac   (same as  (same as  40   mg   ORAL   CAPSULE  
mg Oral  above)   above) 
Capsule  
RxCUI =  PROzac   (same as  (same as             
313989   above)   above) 
0777-3107- PROzac   (same as  (same as             
30   above)   above) 
 
Although only a few examples are presented here, sponsors should use elements of the Define-
XML file and relevant domain data files to communicate how the health care terminology of all 
data domains were normalized to CDISC standard terminology.  As in the examples shown 
above, the technical details of all transformations are best placed in the data files.   
 
 
  11