The SEND Implementation for Cross-Study Analysis Initiative is pursuing the development of recommendations for the implementation and use of CDISC SEND data packages with the aim of facilitating study analysis. Open-source guidance on SEND as applied to study analysis, intended for use by CROs, regulators, and sponsors, has the potential to contribute to a broader knowledge base across early-stage R&D and support faster, better decision-making.
The CDISC SEND format is growing in adoption across the industry, but variability in its use/implementation results in inconsistent study data packages and reports. In addition to potential process inefficiencies during the production of SEND data sets, this also prevents meaningful and accessible single-study analysis as well as cross-study analysis on a broader scale, limiting the potential value of SEND. An examination of SEND implementation variabilities, as well as existing challenges in the use of SEND data packages for analysis, is needed to enable meaningful analysis use cases.
- Organizations can more easily compare data generated across studies and across CROs, leading to decreased cycle times and more informed decision making
- CROs can generate more efficient processes to deliver data leading to decreased cycle times
- Reduced need for companies to develop and maintain internal SEND standards, saving company resources
- Quality improvements in the data sets due to fewer one-off and custom changes that can lead to errors
- Reduction in rework
How You Can Get Involved
We want to hear from you! All entities involved in the development, review, or application of CDISC SEND data sets, or evaluation of the future use of CDISC SEND data sets for any purpose, are welcome to participate in BioCelerate’s public consultation process. We invite you to:
In case you missed it, check out content from our latest events:
- Recordings from our recent webinar, “Leveraging CDISC SEND Data Sets for Study Analyses“
- Content from our luncheon & overview, “SEND Harmonization Initiative Solutions to Enable Cross-Study Analysis”