Introduction to CDISC

Name: Introduction to CDISC
Brand: Tevello
Price: 47.00 GBP
Availability: InStock

£47.00

Introduction to CDISC

6 hours

5 chapters

Certificate

£47.00

This course includes:

Duration time: 6 hours
6 months access
Certificate of completion
Access on mobile & desktop
Summaries, examples, and practical checklists

How Access Works

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Introduction to CDISC - TTC KW A07

The Introduction to CDISC course is designed for professionals who want a clear, connected understanding of CDISC and the family of data standards that underpin modern clinical development. It is suitable for beginner to intermediate learners in clinical research, including Clinical Data Managers, Statistical Programmers, Biostatisticians, data standards and data science professionals, and professionals working in clinical operations, biometrics, or related functions.

This course is an orientation to the whole CDISC landscape, what each standard is, where it sits in the flow of clinical data, and how they all connect. Rather than teaching one standard in isolation or treating CDISC as a pile of unrelated acronyms, the module maps each standard onto the clinical data value chain, from CDASH and SDTM for getting data in, to ADaM, Define-XML and conformance for getting data out.

In a regulated clinical research environment, standardised data is what makes a submission reviewable, comparable, and trustworthy. This module helps you understand the case for standards, the role of Controlled Terminology and the annotated CRF, and the difference between the standard, the deliverable, and the tooling, so you can navigate CDISC as a system rather than memorise a list of terms. Throughout, we follow one patient's headache in a diabetes study, from a field on a form all the way to a described submission.

Why Learn with TriTiCon

TriTiCon delivers clinical development training based on extensive hands-on experience from real clinical trials and operational roles across sponsors, CROs, and life sciences organisations. The content is developed by professionals who understand both the science and the operational realities of working in a regulated environment.

In the context of CDISC, this practical perspective is essential. While many resources present the standards as dense specifications, TriTiCon focuses on how CDISC fits into real clinical development workflows, including how data flows from collection through analysis to submission, what you actually deliver at each step, and why regulators require standardisation in the first place.

The A07 module is built around a single running example, one patient's headache traced end to end, showing how CDASH, SDTM, ADaM, Controlled Terminology, and Define-XML connect into one coherent story. You will see how each standard does real work, rather than reading an abstract definition of it, which is what makes the acronyms finally click.

Compared with generic data or programming courses, TriTiCon's training emphasises job-relevant understanding, a clear mental model, and the connected overview you need before taking a deep-dive module on any single standard.

What You'll Learn

This module provides a structured, end-to-end view of how CDISC standards carry clinical data along the value chain, from collection to submission. The content is organised into five chapters that build from the case for standards and the standards landscape, through data in with CDASH and SDTM, to data out with ADaM and Define-XML, and a closing recap with the road ahead.

Introduction to CDISC - TTC KW A07

Why Learn with TriTiCon

What You'll Learn

Explain what CDISC is, how it came to be, and why the industry moved to shared data standards

Map the clinical data value chain, from protocol through collection, tabulation, analysis, and results to submission

Place each CDISC standard on that chain: CDASH, SDTM, ADaM, Define-XML, Controlled Terminology, and SEND

Separate every standard into three views: the standard itself, the deliverable you hand over, and the tooling that supports it

Follow data in, from a CDASH-shaped form into SDTM domains, linked by the subject identifier and controlled terminology

Follow data out, from analysis-ready ADaM datasets to a summary table, with traceability preserved at every step

Understand the submission package, Define-XML, the reviewer's guide, and the conformance checks that stand behind it

Recognise the pitfalls and good practices that matter most, and where CDISC is heading next

What CDISC is, the Clinical Data Interchange Standards Consortium, and the collaborative model behind it
A short history, and the problem standardisation was created to solve
The scope of what CDISC maintains today
What regulators expect, from the FDA, PMDA, NMPA, and EMA
Why standards matter: consistency and quality, interoperability, and efficiency

The clinical data value chain: protocol, collect, tabulate, analyse, results, submit
Mapping the standards onto the chain: CDASH, SDTM, ADaM, with Controlled Terminology and Define-XML throughout, and SEND to one side
Three views of every standard: the standard itself, the deliverable, and the tooling
Maturity and adoption: which standards are fixed and required, and which leave room for choice
The running example: the AB-201 diabetes study, and one patient's headache

CDASH: standardising how data is collected, designed to flow cleanly into tabulation
SDTM: organising collected data into standard domains, such as DM and AE
Required, expected, and permissible variables, linked by the unique subject identifier
Controlled Terminology and the annotated case report form (aCRF)
Following one patient's headache from the form into the SDTM adverse event dataset

ADaM: analysis-ready datasets built from SDTM, with traceability as a defining principle
ADSL, one row per patient, and analysis datasets such as ADAE
From ADAE to a result: an adverse event summary table by treatment group
Define-XML and the reviewer's guide: describing the datasets so the submission explains itself
The submission package, conformance checks and their severities, and SEND for nonclinical data

The value chain reassembled: one patient, one headache, one traceable thread
The full picture of standards, deliverables, and tooling in one view
Pitfalls and good practice: think downstream, mind your versions, protect traceability, check conformance throughout
Where CDISC is heading: automation, the CDISC Library, Dataset-JSON, and the digital protocol
Your next steps: the deep-dive modules on each standard, taken in the order data flows

Anders Mortin

Clinical Data Management Expert

TriTiCon delivers clinical data management training based on extensive hands-on experience from real clinical trials across sponsors, CROs, and life sciences organizations. The training is developed by industry professionals who work directly with clinical data, systems, documentation, and cross-functional trial teams.

30+

Years Experience

50+

Clinical Trials

This course is ideal for Clinical Data Managers, Statistical Programmers, Biostatisticians, Data Standards and Data Science professionals, Clinical Trial Managers, and clinical operations or CRO staff who work with, or alongside, standardised clinical data.

It is particularly relevant for people who keep hearing acronyms like SDTM, ADaM, and Define-XML and want a clear, connected picture of what they are and how they fit together, before diving into any one of them in depth.

Yes, a foundational understanding of clinical trials and clinical data management is expected.

This is an introductory module on CDISC, but it builds on the basics. Participants should already be comfortable with concepts such as a case report form, a dataset, and a statistical output. We recommend our introductory modules A01 and A02 first. No prior CDISC experience is required.

Estimated learning time is approximately 3–6 hours, depending on your pace and background.

Yes! Once enrolled, you can access all course materials at any time and progress at your own pace. There are no deadlines or live sessions required.

Yes! Upon completing the course content and passing the certification test, you'll receive a certificate of completion. Note: The certificate supports professional development but is not a license or regulatory credential.

This is a practical, orientation-focused course.

Rather than drowning you in specifications, it follows a single running example, one patient's headache in a diabetes study, from a field on a form all the way to a described submission. You see how CDASH, SDTM, ADaM, Controlled Terminology, and Define-XML connect into one coherent flow.

The content is designed to give you a working map you can apply immediately in sponsor, CRO, and data-standards environments.

Yes. CDISC standards are required for study data submitted to major regulators, and the course explains that landscape: what the FDA and PMDA require, what the NMPA has adopted, and what the EMA encourages.

It also shows where the exact required standards and versions are defined, such as the FDA's Data Standards Catalog, and why conformance checking matters before submission.

Most courses teach one standard in isolation, or treat CDISC as a pile of unrelated acronyms.

This course does the opposite: it gives you the whole map first. You see how every standard sits on the clinical data value chain and how they connect, so the acronyms become a system you can navigate rather than a list to memorise.

It's the ideal orientation before taking a deep-dive module on any single standard.

This course supports professionals aiming for or currently working in roles such as Clinical Data Manager, Statistical Programmer, Biostatistician, Data Standards Specialist, or Clinical Data Scientist.

It strengthens a foundational literacy in CDISC that is increasingly expected across clinical data roles, and gives you the vocabulary and mental model to work confidently with standardised data and the teams who produce it.

The structured overview provided in this module is the natural first step before the deep-dive modules on each standard.

No. This is a conceptual orientation, not a coding course. It's written for anyone who works with or around clinical data. You'll understand what each standard does and how they connect, without needing to write a line of SAS or R.

No, and that's by design. This module gives you the connected overview, the map of how everything fits together.

A single Phase II diabetes study, AB-201, and one patient's headache. You follow that headache from a field on a case report form, through SDTM and ADaM, into a summary table and a described submission, so every standard is shown doing real work rather than explained in the abstract.

For the major submission markets it is effectively required. The FDA and PMDA require standardised study data and can refuse a non-conforming submission; the NMPA has adopted the core standards; and the EMA accepts and encourages them. The course explains exactly where those requirements are defined.