Reducing manual programming effort, improving consistency, and accelerating delivery
How our SDTM Automations Work
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Quanticate’s SDTM Automations are built around a structured, metadata-driven process that connects each stage of SDTM generation.
Clinical Data Management Inputs
The process starts in Clinical Data Management, using key study components such as the eCRF from the EDC system and the clinical data extract. These inputs provide the foundation for the SDTM automation and support the creation of the annotated CRF.
Metadata-Driven Mapping
Quanticate applies SDTM mappings from our metadata library to the annotated CRF, helping ensure clinical trial data is accurately translated to CDISC standards and applied consistently across relevant domains.
Automated Specification Development
Information from the annotated CRF is automatically integrated into the SDTM mapping specifications, including direct variable mappings, codelists and controlled terminology. This reduces manual updates and helps minimise the risk of mapping errors.
SAS Code Generation
The SDTM mapping specifications feed into Quanticate’s SDTM code generator, which produces executable SAS code directly from the specifications. This dynamic programming approach can adapt to variations in the specification and reduce repetitive manual programming.
define.xml 2.1-Ready Outputs
Quanticate’s automation tools are define.xml 2.1 ready, helping streamline the creation of required documentation at the end of the SDTM process.
Connected SDTM Delivery
By allowing each stage to feed into the next, Quanticate creates a more efficient and traceable route from collected clinical trial data to standardised SDTM datasets, helping reduce duplication, minimise error risk and support faster delivery.
Flexible to any Study Type
Due to the complexity and variety of clinical trials we are 'constantly' adding extensions and evolving our automations for Therapeutic Area specific requirements. Our SDTM automations provides 100% automation for data collected directly on the CRF, mapping it through to SDTM with speed and efficiency.
For imported data, such as third party labs, our data specifications allow us to align easily with collected CRF data. On typical studies, this accounts for 95% of the data included in SDTM and results in a streamlined process.
On a more complex study involving multiple treatment periods or complex and adaptive visit structures, our tools will still automate 80% of the mappings, leaving our expert programmers and statisticians to provide the human input and oversight for these complex mappings. This combination ensures both efficiency and quality where it is most needed.
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