Want your SDTM datasets in 1 click?

Map raw datasets to target datasets in ryze, then SDTM automation is just 1 click away


Make compliant SDTM datasets

As it stands, your source datasets (from your library or EDC) need a lot of work to get them into SDTM datasets. That takes time, labor, and programming skills = money.

ryze SDTM automation makes life easy. There’s no coding, and we use templates to speed things up. Our data mapping automation tools help you match the variables in SDTM with the relevant variables in your source datasets. Forget trying to work out what your source dataset headings will be. Once you’re done, press a button for your SDTM datasets and SDTM define.xml files.


Create ADaM datasets, fast

ADaM datasets are essential in your submission for drugs and product approval. And if you don’t get datasets done early on, it can cause delays in future. You even risk not collecting the exact data that’s needed for trial building. Our ADaM automation tools keep you right.

ADaM ryze

What can I do with ryze?

SDTM conversion made easy

See how datasets look

See how your datasets will look to reviewers. Preview in PDF or HTML format, and make any changes until you’re happy.

Easily do CDISC SDTM mapping

Our SDTM data mapping automation tools make the job of creating and describing your SDTM mappings much easier. Whether it’s simple or complex mappings, ryze has a user friendly framework for you.

Get SDTM datasets much faster

According to the industry average, you’ll typically be waiting 8-12 weeks for SDTM datasets. Not ideal when you need to analyze the data and determine safety and efficacy ASAP! With ryze, time from first data to SDTM is as little as 2-4 weeks.

Improve consistency

Reusing datasets and mappings helps to keep consistency across studies and standards. This content has already been approved, so you can use it consistently in future.

Quickly create datasets

Rather than struggling to figure out your source dataset column headings (variables), ryze helps you do this. You’ll get to see what your source datasets will be really early on – well before you’ve collected any patient data.

Automatically convert datasets to SDTM

Once ryze has shown what your source dataset column headings will be, you can design your SDTM datasets. And because you get this way before you’ve collected any patient data, you can do your SDTM mappings early on too. By the time you get trial data back, your datasets are all mapped, and it’s just 1 click in ryze for SDTM automation.

No programming needed - save costs

No need for any programming knowledge. And you don’t need programmers to ‘double program’ data conversions from your specifications. Our easy-to-use mapping language lets you create machine-readable mappings, without any coding. As a result, you save both time and resource costs. 

SDTM dataset conversion

SDTM conversion is when you turn your raw (source) datasets into SDTM datasets. This is done using the SDTM mappings and templates in ryze. You can do this at various stages, from study start to submission. SDTM dataset creation during the clinical trial lets you check your data integrity – as soon as data becomes available.

We can automatically upload your source data into ryze – whether it’s in SAS Transport v5 (.xpt), dataset-XML or CSV formats. Or you can manually upload data, for example, from legacy studies.

Data transformation is simple too. Your data is already mapped at study design. So you can run conversions automatically as soon as your trial data comes in. Not only that, you can automatically download the data in SAS Transport v5 (.xpt), dataset-XML and CSV formats. Our SDTM validation tools ensure that datasets conform to the relevant CDISC standards.

SDTM datasets - SDTM conversion in ryze Clinical trial software

Get SDTM data in just 2-4 weeks and make earlier informed decisions with ryze

Easily make compliant SDTM datasets

Use our clinical trial automation software to make SDTM datasets upfront. You can even create them before you’ve collected any patient data. That way, you get SDTM conversion done early on, and can check that your datasets will meet regulatory requirements. You also get a head start on mapping your ADaM datasets back to SDTM.

Easily design datasets

Templates let you add domains and variables that are compliant with the relevant versions of CDISC standards. Tailor them to your needs by adding additional metadata – such as supplemental qualifiers, derivation methods and value list metadata. Our clinical metadata management tools help ensure that your datasets comply with CDISC Define-XML, CDASH, SEND, SDTM and ADaM standards.

Create standards for reuse

You can arrange your datasets into organizational standards for reuse in future. This increases data quality and saves so much time and resources.

Easily manage CRO specs

Use ryze to make specifications if you’ve got a CRO designing datasets for you. When you get datasets back, simply check them against your original specs to ensure they’re as you expected.

What will my datasets look like?

See how your SDTM datasets will look to regulators reviewing your submission. Either PDF or HTML format. This includes links to pages in external documents, like Annotated CRFs.

Organizations using our clinical trial software

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UCB logo
vertex logo
University of Alabama logo
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University of Utah logo
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Catalyst clinical research logo


SDTM mapping tools

Your study can also manage other metadata in ryze, such as SDTM mappings. These describe how the original (or source) datasets from your EDC system map to the CDISC SDTM standard. Our CDISC SDTM mapping tools let you make and validate simple variable to variable mappings, as well as more complex mappings with many steps.

Upfront mappings

Mapping data upfront helps ensure that all the relevant data is collected. ryze clinical trial building and automation software shows what your EDC datasets will look like – before you get them. So you can do your mappings early on. Then crack on making your SDTM define.xml files once your first EDC datasets are ready.

And if you include SDTM mappings in your organizational standards, you can easily re-use them. That means faster study designs, and better quality data.

Human-readable mappings

In ryze, you make human-readable mappings that clearly describe how datasets and variables in your original (source) datasets map to their equivalents in SDTM. From there you can create a metadata specification for programmers.

Machine-readable mappings

You can also create machine-readable mappings with our easy-to-use mapping language in ryze. No programming knowledge is needed. Once your mappings are done and approved, use them to turn your source datasets into SDTM datasets (using our templates). You’ll save time and money as there’s no need for programmers to double program data conversions from your specifications. Reports give you full traceability of all mappings to ensure data is accurately mapped.

Find out about the biggest challenges with SDTM datasets in clinical trials and how to fix them


What are SDTM standards and ADaM standards?

CDISC built SDTM to provide a standard way to organize and format data in order to streamline the processes of collection, management, analysis and reporting of clinical trial data.

The CDISC ADaM standard is designed to derive data and for analysis in clinical trials.

What are SDTM domains?

SDTM is built on observation classes, each one having associated domains. A domain is a group of observations that share a common topic such as vital signs, adverse events and demographics. Find out more on all you need to know about SDTM.

What is meant by SDTM conversion?

SDTM conversion is when you turn your original (source) datasets into SDTM datasets.

How do you do SDTM dataset creation in ryze?

Our platform is built on new and previous versions of CDISC standards and templates. Select the version of the standard you want and the platform guides you through. Compliance and validation are built in so you cant go wrong!

What is the ryze CDISC SDTM mapping tool?

Our SDTM mapping tool lets you map your source datasets from your EDC system to SDTM datasets and from ADaM datasets back to SDTM easily. Plus you can see what your EDC datasets will look like early on so you can define mappings earlier. You can create metadata specifications for programmers. And there’s no programming required to do your mappings. Once they’re done, you can standardize them and use them over and over again. You’ll save time and money and you can run a report to ensure mappings are accurate.