The release of CDISC Open Rules has opened new possibilities for clinical research organizations (CROs) and pharmaceutical and biotech companies looking to ensure their clinical datasets are compliant and submission-ready. As a CRO with deep expertise in CDISC Open Rules, we have been closely involved in developing these machine-executable data conformance rules, and we can help organizations adopt this new open-source project to fit their specific needs.
As a guest speaker in a recent CDISC webinar, Roman Radelicki, Head of Data Technology, SGS, shared invaluable insights on how to build and implement custom rules using CDISC Open Rules. Here's a summary of the key takeaways from his presentation.
Watch the full webinar here
Why build your own CDISC Open Rules?
While CDISC provides a comprehensive set of data conformance rules, there are many scenarios where custom rules are necessary. As Roman explained, custom rules are particularly useful for validating internal data, managing vendor-specific datasets, or working with non-CDISC data formats. For example, Roman demonstrated how to create a rule to check if a test result was completed when a reference range indicator was populated – something not currently covered by the standard CDISC rules. This highlights how customization allows organizations to enforce specific checks that are crucial for data quality but may not be addressed by CDISC’s data conformance rules.
Key tools for building custom rules
Two tools are central to getting started when creating custom rules: the CDISC Open Rules Engine and the Rule Editor.
- CDISC Open Rules Engine: The engine is a command-line tool that allows organizations to validate datasets against CDISC data conformance rules or customized rules. Roman demonstrated how it can be integrated into automated workflows, such as nightly validation of datasets in clinical trials, ensuring that teams can catch issues early in the process
- Rule Editor: This tool is used to create custom rules. The Rule Editor allows you to write rules in YAML format, and it comes with real-time syntax checking to ensure your rules are written correctly. While it requires greater technical setup, it does provide the flexibility to tailor rules to specific validation needs
Practical use cases for custom rules
In his presentation, Roman shared a couple of concrete use cases for creating custom rules that go beyond the standard CDISC governance set, illustrating CDISC Open Rules’ flexibility.
- Data cleaning: Roman explained how a custom rule was created to flag errors based on inclusion/exclusion criteria. For instance, a rule was designed to flag male subjects over the age of 40 or female subjects over the age of 41, ensuring that only eligible participants were included in the study. This type of data cleaning rule helps ensure the integrity of the dataset before submitting it for regulatory review
- Validating non-CDISC data: Another use case involved validating external vendor data that didn’t conform to the standard CDISC structure. Roman demonstrated how the CDISC Open Rules Engine could be used to validate a data transfer by checking if a test result and test name were completed, and that the unit column also would need to be completed. This ability to validate non-CDISC datasets enables you to incorporate external data into your validation processes without the need for extensive reformatting
Why seek expert guidance?
While CDISC Open Rules offers great flexibility, the process of creating and implementing custom rules can be complex. Roman emphasized the importance of governance and organization when developing and using custom rules, especially when scaling across multiple teams. Without proper setup, it can become challenging to manage different sets of rules and ensure consistency in validation. Seeking expert guidance will help to ensure a smoother implementation and effective scaling.
Learn more about SGS’s CDISC Open Rules consultancy services
Conclusion
Building their own CDISC Open Rules provides organizations with the flexibility to adapt data validation processes to their specific needs. Whether it is creating rules for internal data cleaning or integrating non-CDISC datasets, the CDISC Open Rules Engine and Rule Editor are powerful tools for customization. However, to ensure the successful implementation and scaling of these tools, it is important to have a clear governance strategy and technical support.
About SGS
SGS is the world’s leading Testing, Inspection and Certification company. We operate a network of over 2,700 laboratories and business facilities across 119 countries, supported by a team of 99,250 dedicated professionals. With over 145 years of service excellence, we combine the precision and accuracy that define Swiss companies to help organizations achieve the highest standards of quality, safety and compliance.
Our brand promise – when you need to be sure – underscores our commitment to trust, integrity and sustainability, enabling businesses to thrive with confidence. We proudly deliver our expert services through the SGS name and trusted specialized brands, including Brightsight, Bluesign, Maine Pointe and Nutrasource.
SGS is publicly traded on the SIX Swiss Exchange under the ticker symbol SGSN (ISIN CH0002497458, Reuters SGSN.S, Bloomberg SGSN:SW).
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