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Clinical Data Standards and Submission Datasets

CDISC SDTM and ADaM Dataset Creation Services

Pubrica’s CDISC programmers prepare submission-ready SDTM and ADaM datasets for sponsors, CROs and biotechnology companies. Each package includes the datasets, Define-XML v2.1 metadata, the cSDRG and ADRG reviewer guides and a validation report, built to the versions the FDA Data Standards Catalog requires for your study. The work is designed to prevent version mismatches, inaccurate metadata and untraceable derivations from stopping a submission at technical validation, so that reviewers can focus on the science.

  • Versions taken from the FDA Data Standards Catalog, which sets the required version for your study by its start date rather than the newest standard available
  • SDTM built to SDTMIG v3.4, the currently required version; the v3.2 requirement has ended
  • ADaM traceable back to SDTM, variable by variable, because traceability is what regulatory reviewers test
  • Define-XML v2.1 that matches the datasets submitted, a common source of validation findings
  • Reviewer guides written for your study: the cSDRG and ADRG explain any deviations before a reviewer has to ask
Get a free quote Deliverables
What CDISC programming covers What is not included

SDTM mapping and datasetsIncluded

ADaM with full traceabilityIncluded

Define-XML v2.1 and reviewer guidesIncluded

Validation and issue resolutionIncluded

Mapping data that was never collectedCannot be done

Raw → SDTM → ADaM → Define-XML → submission

Included in every dataset package
  • Versions from the Data Standards Catalog
  • Traceability tested and documented
  • Validated with issues explained
  • Reviewer guides written for each study
  • Programs and specifications handed over
Quoted per studyBased on domain count and data complexity
sdTCG v6.0March 2025, with the Data Standards Catalog
SDTMIG v3.4Required; v3.2 requirement ended
ISO 9001:2015Quality management certified · cert. H3CR9TCU20251212INDQM10N

Service Scope

Four CDISC Dataset Service Areas, Available Individually

Pubrica offers CDISC SDTM and ADaM conversion as separate services, so you can engage us at any stage, whether you are still planning data collection or already hold the data.

Annotated CRF and mapping specificationsWe prepare the annotated CRF and the mapping specification before any programming begins, because most SDTM problems originate in the specification rather than in the code.
SDTM domains built and validatedDomains built to the implementation guide in force for your submission, with controlled terminology from the correct release, and validated against the conformance rules rather than against a previous study.
ADaM datasets traceable to SDTMADSL and the analysis datasets your statistical analysis plan requires, built so that every derived variable traces back to its SDTM source. This is the core ADaM requirement and the one most often missed.
define.xml, reviewer’s guides and the conformance reportThe metadata deliverables that accompany the datasets, with every conformance finding resolved or explained before submission.

Who We Serve

Organisations We Support with CDISC SDTM and ADaM Conversion

We support sponsors, research teams, institutions and decision makers as well as academic researchers.

Sponsors preparing a regulatory submissionFDA and PMDA require CDISC-conformant data, so the conversion must be prepared to meet the requirements of technical review.
CROs and biometrics teamsAdditional programming capacity, or an independent conformance review before delivery.
Biotechnology companies without in-house programmingStandards work completed correctly from the start, rather than learned during a submission.
Legacy data ownersConversion of older studies for pooling, integrated summaries or submissions that include historical trials.
Medical device and diagnostics teamsStandards-based datasets where the submission route requires them.
Academic trial unitsConversion for a study that is moving to submission, or for a sponsor partner who requires CDISC.

Deliverables

What Every CDISC Dataset Package Includes

Technical validation is the checkpoint every submission must clear before scientific review, and each package is prepared with that checkpoint in mind.

The correct standard version for your study The FDA Data Standards Catalog lists which versions are supported and required, with dates. The requirement attaches to your study by its start date, not to whatever is newest.

Version check exampleSDTM v2.0 with SDTMIG v3.4 is supported and required, and the SDTMIG v3.2 requirement has ended. Submitting to a version the catalog no longer requires, or one it does not yet support, both produce findings.

Traceability a reviewer can follow Every ADaM variable traceable back to its SDTM source, and every SDTM variable back to the raw collection field, documented in the specification rather than left to individual memory.

Traceability check exampleAVAL derived from source data.AVAL = VSSTRESN from VS where VSTESTCD = "SYSBP" and VSBLFL = "Y", with the derivation documented in the ADaM specification and reproduced in the ADRG. Traceability is what reviewers test first.

Define-XML that matches the submitted datasets Metadata describing the actual datasets, with codelists, derivations and value-level metadata consistent with the data files rather than with an earlier version of them.

Validation exampleA Define-XML describing datasets that have since changed is one of the most common findings, and it results from a process failure rather than a technical difficulty.

Reviewer guides that explain the deviations A cSDRG and an ADRG written for your study, covering what was collected, what was mapped unusually, and which validation findings are explained and why.

Reviewer guide exampleUnexplained findings in a validation report usually prompt a question from the reviewer. The same findings, explained in the guide, usually do not.

The samples shown are illustrative and anonymised. Hover over a sample to replay it.

Compliance and Standards

CDISC and FDA Data Standards References

The Data Standards Catalog sets the required versions, and the implementation guides describe how to meet them.

sdTCG v6.0

Study Data Technical Conformance Guide (March 2025)

Sets out how standardised study data must be submitted, alongside the Data Standards Catalog, which determines the versions your study must use.

SDTM, ADaM, CDASH and Define-XML (the standards themselves)

SDTMIG v3.4 for tabulation, the ADaM implementation guide for analysis datasets, Define-XML v2.1 for metadata, and CDASH upstream where collection can still be influenced.

Reviewer guide templates (cSDRG and ADRG)

Community templates for the study data and analysis data reviewer guides, where deviations are explained before a reviewer asks about them.

ISO9001:2015

Quality management (cert. H3CR9TCU20251212INDQM10N)

Our certified quality system governs how work is run, recorded and released.

Responsible Use of AI

Our Approach to AI Use in CDISC Programming

AI tools can generate SDTM that passes the conformance rules while still mapping the wrong source variable. Validation checks structure; it does not detect a correctly programmed but incorrect specification.

How We Use AI ToolsDrafting mapping specifications from an annotated CRF, which a programmer then reviews variable by variable; finding controlled terminology matches; and flagging and grouping conformance findings for review.
Where We Do Not Use AIWe do not accept mapping decisions without review, release derivations without a second programmer’s check, or deliver anything into a submission without a named programmer and a reviewed conformance report.
What Your AI Declaration Should IncludeYour declaration states the tool, the stage at which it was used and the human oversight applied. Journals, funders and the ICMJE January 2026 update now expect this, and an undeclared tool found later is treated as a research integrity matter.

Why We Do Not Publish AI Accuracy Figures

Accuracy figures for AI tools are usually reported by the companies that sell them.

Pubrica therefore does not quote a self-generated accuracy figure, because it would carry the same conflict of interest. Instead, we tell you which tool was used on your project, at which stage, and what a specialist changed afterwards.

Methodology

How Our CDISC Programming Process Works

The process begins with the Data Standards Catalog, because the required version determines every later step.

Step one

Standard Version Selection and Gap Analysis

We establish the required standard versions for your study from the Data Standards Catalog and assess the raw data against SDTM requirements.

Step two

SDTM Mapping and Domain Creation

We write the mapping specification, build the domains, apply controlled terminology and document the mapping field by field.

Step three

ADaM Analysis Dataset Creation

We build the analysis datasets from SDTM with traceability preserved, derivations specified and the structure your statistical analysis plan requires.

Step four

Define-XML, Validation and Reviewer Guides

We produce Define-XML v2.1, run validation, resolve or explain the findings, and write the cSDRG and ADRG.

Our Experts

Your CDISC Programming Team

A named team of subject specialists stays with your project from scoping to delivery. Your project coordinator introduces each team member by name before work begins.

Subject matter expertClinical or scientific expert matched to your topic

Reviews the scientific content for accuracy and confirms that each conclusion is supported by the evidence. Each expert is matched to your field of research.

Responsible forScientific accuracy and interpretation
Reviews againstThe study protocol and current literature
FieldMatched to your topic
BiostatisticianStatistical input where the work reports analysed data

Checks that statistical methods, tables and conclusions are consistent with the analysis plan and that the analysis can be reproduced.

Responsible forStatistical accuracy
Reviews againstICH E9 and the statistical analysis plan
ToolsR, SAS, Stata, Python
Data specialistData handling, cleaning and documentation

Prepares, cleans and documents the data so that every step from raw data to final output can be traced and reproduced.

Responsible forData handling and documentation
Reviews againstThe data management plan and applicable data standards
OutputDocumented, reproducible datasets
Second reviewerIndependent check of code and outputs

Independently checks code, tables and outputs against the analysis plan. Discrepancies are logged and resolved before delivery.

Responsible forIndependent quality control
Reviews againstThe analysis plan and outputs
Signed off byProject lead

Packages

CDISC Dataset Service Packages

Pricing depends on the number of domains, the condition of the raw data and whether data collection followed CDASH.

SDTM

SDTM package

Tabulation datasets

Quoted per projectBased on domains and data condition

Delivery Quoted by scope

  • ✓Version check against the Data Standards Catalog
  • ✓Mapping specification written
  • ✓Domains built with controlled terminology
  • ✓Define-XML v2.1
  • ✓Validation with findings explained
  • ✓cSDRG written

The condition of the raw data affects the cost more than the number of domains, so we review the data before quoting.

Deliverables Request a quote
Full

SDTM and ADaM

A complete submission package

Quoted per projectBased on study size and analysis complexity

Delivery Quoted by scope

  • ✓Everything in the SDTM package
  • ✓ADaM datasets built to the analysis plan
  • ✓Traceability documented variable by variable
  • ✓Analysis results metadata where required
  • ✓ADRG written
  • ✓Programs and specifications handed over

SDTM and ADaM are built together because ADaM decisions often require changes to SDTM, and separating the two across teams introduces inconsistency.

Deliverables Request a quote
Check

Pre-submission review

A package built elsewhere

Quoted per projectBased on package size

Delivery Quoted by scope

  • ✓Version compliance checked
  • ✓Validation rerun independently
  • ✓Traceability tested on a sample
  • ✓Define-XML checked against the actual datasets
  • ✓Findings reported by severity

A pre-submission review costs less than a technical rejection or an information request during regulatory review.

Deliverables Request a quote

Send your annotated CRF or raw data structure and we will run a free gap analysis against SDTM, so you know what is missing while it can still be collected.

Benefits

Benefits of Pubrica CDISC SDTM and ADaM Conversion

Four reasons clients commission this service.

01Preparation for technical reviewConformance findings are the most common cause of technical rejection, and they can be avoided. Pubrica resolves or explains every finding before delivery rather than leaving it in the report.
02Documented traceabilityEvery ADaM derivation traceable to its SDTM source, which is what a reviewer follows when they want to know where a number came from.
03Built to the right versionImplementation guide and controlled terminology versions chosen for your submission date rather than copied from the last study, and stated in the metadata.
04Full documentation handed overMapping specifications, define.xml and the reviewer’s guide are handed over, so the next study or team does not need to start from the code.

Quality Assurance

Our Service Commitments and Limitations

Our service terms are set out in full below, before you commit.

Our revision commitment

Revision Support Within the Agreed Scope

We continue working within the agreed scope until the work meets the agreed requirements. We offer continued revision rather than a refund, because a refund ends the engagement without delivering the work.

01

Unlimited revisions within the agreed scope

There is no limit on revision rounds or time within the agreed scope. If the work does not meet what we agreed, we revise it. Changes that widen the scope are quoted separately, and we confirm which applies before work starts.

02

Corrections at Our Cost

If the work needs correction because of an error in our analysis or writing, we correct it at no cost.

03

Delivery on the agreed date

We agree a delivery date that we can meet. If a milestone is at risk, we tell you early rather than on the day.

04

Mutual NDA on request

Signed in both directions before you send anything, at no cost. We are also happy to sign your NDA instead of ours.

05

Final decisions remain with you

We advise, give our view and tell you clearly when we disagree, but decisions about what is published in your name are always yours.

9.4/10

Average client rating

From 3,000 responses to Pubrica’s own post-delivery survey, sent to every client at handover between January 2024 and June 2026. This figure comes from our own records.

Service limitations. We cannot guarantee outcomes decided by others, such as an editor’s decision, a funding panel’s decision or a regulator’s assessment. Within the agreed scope, we guarantee the work: completed to the standards named on this page, delivered on the agreed date and corrected at our cost if we made an error.

FAQs

CDISC SDTM and ADaM FAQs

If your question is not answered here, please ask an expert. No quote is required.

Whichever the FDA Data Standards Catalog requires for your study, which depends on your study start date rather than on what is newest.

SDTM v2.0 with SDTMIG v3.4 is supported and required, and the SDTMIG v3.2 requirement has ended. We check the catalog for your specific study rather than applying a default.

It makes SDTM mapping interpretive rather than mechanical, which increases the cost and introduces decisions that must be documented and justified.

It is fully recoverable. An early gap analysis against SDTM shows what is missing while it can still be collected, which is when it is least expensive to address.

Yes. You receive the programs, specifications and documentation, because it is your submission and you may need to rerun it during review under time pressure.

A package that only the vendor can regenerate becomes a problem when an information request arrives.

Some can, and that is normal. Not every finding indicates an error; some reflect legitimate study characteristics that the rules cannot accommodate.

What matters is that each one is explained in the reviewer guide. An unexplained finding generates a question; the same finding explained usually does not.

Related Services

Related Research Services

Datasets are one part of a submission and are reviewed alongside the submission documents.

1THE ANALYSISsame team

BiostatisticsAnalysis and statistical programming. Statistical analysis planThe analyses that ADaM datasets must support.

2THE DOCUMENTS ALONGSIDEin the same submission

Clinical study reportWritten to ICH E3 from the same outputs. CTD module summariesClinical summaries in Modules 2.5 and 2.7.

3BEFORE DATA COLLECTIONwhere costs are determined

REDCap database buildCollecting data to CDASH reduces conversion cost. Clinical trial supportSupport across the study.

Request a Free SDTM Gap Analysis of Your Annotated CRF

A gap analysis identifies what is missing while it can still be collected, which is when it is least expensive to address.

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