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How clinical trial software can optimize clinical trials

Mar 28, 2023 4:00:00 PM


Steven Benham

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What is clinical trial software?

Clinical trial software is used by clinical research organizations (CROs), biotechnology, and pharmaceutical companies to facilitate clinical trials from conception to finish.

For example, specialized clinical trial software can help with:

  • Protocol management
  • CRF design
  • Metadata management
  • Collection and analysis of data
  • Submission of compliant clinical study data to regulatory authorities

Specialized software can help you run clinical trials more efficiently and help you to get quality clinical products to the market faster.

Research organizations are faced with the pressures of study deadlines and a need to stay compliant with regulatory standards. And often, they’re running multiple clinical trials simultaneously. They’ve got to be efficient. They need to be able to see and manage their clinical trials effectively so they can identify process inefficiencies. They also need full transparency of the process from start to finish so they can report on this come submission time. And importantly, they need to collect the required data quickly and accurately.

This is why more and more organizations are engaging the help of clinical trial software companies offering cloud-based solutions.


Where is the industry now with clinical trial software?

The pharmaceutical industry has been slow to try new approaches and emerging software solutions. They’ve been focussed on getting clinical products to the market, despite process inefficiencies.

Traditionally, spreadsheets have been used to record and manage the various aspects of clinical trials, including data collection, study protocol and specifications.

But these traditional ‘manual’ solutions carry a high risk of errors, incomplete data collection, and process bottlenecks. As a result, efficiency, compliance, and patient care are often compromised.

The industry is now recognizing that to stay ahead of competitors and overcome tight timescales, technological cloud-based clinical trial software solutions are key for faster, more efficient clinical trials. The FDA encourages the use of cloud-based solutions to streamline the clinical trial process. The end goal is to have more effective medications and more personalized healthcare.


What solutions do clinical trial software companies offer?

Clinical trial software companies provide different types of software for different stages in the clinical trial process. There are four main types of software to help build and run clinical trials:

  1. Clinical Trial Management systems (CTMS)
  2. Electronic Data Capture system (EDC)
  3. Clinical metadata repository (CMDR)
  4. Clinical trial automation software

 Below, we explore each type of software in more detail.


1) Clinical trial management systems

A clinical trial management system is an integrated cloud-based software platform that’s used for the end-to-end management of clinical trials.

A clinical trial management system is used to:

  • Plan, track, and analyze clinical trials
  • Find and manage participating patient
  • Track participants’ involvement in clinical trials
  • Manage finances

This software can help you improve the quality of your clinical products, reduce the time it takes to get a product to market and ensure compliance with industry standards and regulations.

Clinical trial management systems are often used in conjunction with other clinical trial software that specializes in a specific area, such as EDCs and integrated clinical study automation software.


2) Electronic data capture systems

An EDC is an electronic system used to gather patient data during clinical trials. EDCs typically have a user interface for users to enter data into electronic forms. A validation function will check forms have been filled in accurately and a reporting tool lets users analyze the data collected.

EDCs have been around since the 1990s and are improving all the time. Modern EDCs let you target specific patient profiles or study phases. Examples of modern features include cloud data storage, role-based permissions, CRF designers, clinical data analytics, interactive dashboards, and electronic health record integration.


Leading EDC companies

Leading EDC companies


common-file-text-edit Note

Using an EDC system can help you increase data accuracy, speed up the data collection process, and reduce costs over the lifetime of your clinical trial.


3) Clinical metadata repositories

A CMDR is a centralized location for you to store, manage and find all your study metadata, such as forms, standards and datasets, in one place. A bit like a library, or a single source of truth.

Metadata can be stored in various stages of development. It can be updated, approved, and kept as organizational standards. This gives you easy access to approved metadata you can reuse again and again. This means less time spent creating and approving metadata with every study.

Examples of standardized metadata include case report forms (CRFs), terminologies, datasets, and mappings.

A CMDR can help you with:

  • CRF design
  • Metadata management
  • Standards governance
  • Data warehousing
  • Statistical computing
  • Submission to regulatory authorities

CMDR infographic

What are the main features of a clinical metadata repository?

A good quality clinical metadata repository should have the following features built-in.


User access control

You should be able to control all internal and external user access and assign roles to each individual. For example, being able to assign view-only or edit access to different users. Ideally, it should be possible to set access by standard or study thereby allowing specific users to edit particular standards and studies, but not allowing them to edit others.


Impact analysis

Impact analysis lets you see what upstream and downstream metadata and processes are affected if a particular change is made - before you make that change.

Global traceability and reporting show where standards and study content is being used. For example, you’ll be able to identify asset groups in other standards that use the same CRF, or SDTM datasets that are mapped to the CRF.

Impact analysis lets you make informed decisions on whether a proposed change is worth making, or not.


Change management

There should be a way for team members to request changes to existing metadata content. It must be possible to edit, add, and retire metadata content. The change management process should record what the change is, why it’s been requested, who made the change, who requested the change, when the change was requested, and when the change was made. These changes should go through a thorough governance process, like the example below.





Governance refers to the process that must be adhered to for any change to existing metadata content and organizational standards, or for the creation of new metadata content. A governance process, or workflow, must be built in to make sure that changes are managed and dealt with effectively in a way that suits an organization’s needs.

Being able to fully track metadata means that it’s easier to see how to improve metadata management. Having governance means there’s a fully traceable audit trail, the ability to do impact analysis, and the ability to see the flow of data through the system.



A quality clinical metadata repository should allow versioning of internal standards across the organization. It should let you update and improve both study level standards and organizational standards. For example, you might want to have various versions of the same CRF for different purposes. And changes to a version of a CRF will have an impact on SDTM mappings and TLFs (tables, listings, and figures).


 Built-in compliance and validation

Compliance and validation ensure that a clinical study meets the expectations of regulatory authorities. It should be built in from the start of a study, through to submission. So, each part of the study should be tested against validation rules to make sure it stays compliant.



A clinical metadata repository should integrate with other systems. This could mean integration with an organization’s systems to allow them to upload data. Or it could mean integration with a SAS based system for pushing and pulling data in different formats, or an EDC system.


The benefits of using a CMDR

The key drivers for using a clinical metadata repository are:

  • Regulatory compliance
  • High data quality
  • Process efficiency
  • Reuse
  • Save time and resources
  • Get to submission faster

And many of these benefits come as a direct result of automation.  


4) Clinical trial automation software

Automated processes and clinical metadata repositories go hand in hand. You’ll find that if you implement a CMDR, you’ll also be able to automate traditionally manual processes.

A clinical metadata repository stores all your organizational standards in one place. This means your content is easily accessible and ready to use across all your studies. A good CMDR also enables auto-generation of study artifacts such as EDC, SDTM, and ADaM specifications.

Automation simplifies processes for clinical studies, from study setup through to submission. It helps to accelerate studies and to reduce human error by removing manual processes. It also makes it easier for companies to comply with regulatory standards because submissions can be easily built to a compliant specification and data quality will be high.

By using a CMDR or other clinical trial automation software, you’ll be able to:

  • Get clinical trials done faster
  • See improved data quality and consistency
  • Analyze data more quickly and effectively
  • Reduce overall costs of the study

Read more about automation in our blog Automating clinical trials: Why it’s essential for success.


ryze CMDR and clinical trial automation software

Our off-the-shelf clinical trial automation software and clinical metadata repository is a fully integrated online platform for facilitating clinical trials.

ryze lets you store metadata content and build studies quickly using automated workflows. It simplifies the study design process and there’s no requirement for programming skills.

Our clinical metadata repository has all the desired features such as impact analysis, change management, and governance. And it has the necessary automated processes needed to generate the study artifacts required to make a submission to the FDA.

You can:

  • Store and manage metadata, across the end-to-end life cycle of your studies
  • Create metadata content from scratch, or upload your existing organizational standards
  • Manage your organizational standards, helping to increase data quality while decreasing downstream costs
  • Make validated CRF designs, EDC designs, and builds
  • Convert data to produce validated SDTM datasets
  • Create valid SDTM and ADaM define.xml files for submission
  • Use the APIs to integrate with external systems


Automated processes in ryze

CRF design and visualizations

ryze makes it quick and easy to make all the different metadata formats you need. You can see how your CRFs will look and how they’ll work in your EDC system before you build it.


Generating annotated CRFs and blankcrf.pdf

Once you have your CRF designs in ryze, it’s easy to add annotations. Or if you have your CRFs standardized with annotations, that’s even better! You can just reuse your annotations.

If you need to make changes, you can instantly preview them. Then when you’re happy, it’s just one click to get your submission ready annotated CRFs in PDF format.

Read more about automating CRF annotations in our blog: Why you should switch to automated CRF annotations.


Generate SDTM datasets from source data

Start by defining the mappings from your source data to your SDTM. Then you can pull data directly from your chosen EDC system to generate your SDTM datasets after you start collecting data.

ryze supports all versions of CDISC standards and SDTM automation. We keep our platform updated in line with CDISC and NCI standards. That way your study designs and datasets are always regulatory compliant.


Generate SDTM and ADaM define.xml

Once you’ve built your study and defined your datasets, it’s just one click to generate your SDTM define.xml, and another click to generate your ADaM define.xml.

You can even generate define.xml from SAS XPT files or old legacy datasets. Learn more about our visual define.xml editor.



ryze lets you integrate with the leading EDCs. You can design your studies with all the features of the EDC you work with. You can see what your forms look like and how they’ll work in your chosen EDC as you design them. When everything’s finished, automatically build the EDC database with just one click.

You can also use our API to integrate with your own internal systems. That means you can set up automatic processes to push source data into ryze and trigger a conversion. Then, pull the datasets back into your system from ryze. You can also pull metadata in ODM and Define-XML formats.


ryze platform integrations and automated processes

Want to find out more about CMDRs and clinical trial automation?

Why not sign up for a free 30-day trial of ryze? You'll also get some training to help you  get the most out of your trial.


Get my free trial



Author's note: this blog post was originally published in August 2020 and has been updated for accuracy and comprehensiveness. 





About the author



Steven Benham

Professional Services Manager | Formedix


Steven Benham has been with Formedix for over six years. Starting originally as a Solutions Consultant, he worked to author and present Formedix training courses for SEND, SDTM, Define-XML, ODM-XML, Define-XML and Dataset-XML.

He has also been involved in a number of clinical data programming projects helping to deliver in Interim Analysis (IA) SDTM and FDA SDTM clinical submissions. He is now the Professional Services Manager and currently oversees all Formedix clients.


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