Statistical Programming Services
Accelerate CDISC SDTM data transformations.
The Challenge
A top 5 pharmaceutical company had well-established — but inefficient — processes to transform raw data into SDTM format. Automating and outsourcing this process would allow them to accelerate their time-to-market at the end of their trials.
How Saama Helps
Saama implemented Source to Submission (S2S), automating the complex SDTM mapping process with artificial intelligence (AI) and machine learning (ML). This eliminated much of the manual work done by SAS programming teams, and also reduced timelines from six weeks to three weeks while maintaining the same data quality. Saama provided resources to conduct the automated mappings, further reducing the burden on internal resources.
