PHUSE US Connect 2020
Presentation Title: DH12: Validation Consistency and Conformance Checking of SEND Datasets
ABSTRACT
Validators can check if nonclinical studies submitted in CDISC SEND format meet FDA business rules, FDA validation rules, CDISC conformance rules and PMDA’s Define.xml rules as applied for SEND. However, these validators cannot check if the SEND Trial Design is modeled correctly according to the Study’s design with sufficient granularity. For example, if a Latin square study is coded in SEND as a parallel design, the SEND dataset cannot be reviewed or analyzed. Since SEND datasets are prepared separately using a CDISC trial design, the SEND data set should be checked to ensure it will generate the same summary results as listed in the audited study report. Manual “spot checks” are insufficient and risky. This paper discusses the best practices for sponsors to make sure that their SEND data set is of high quality and is consistent and conformant with the Study Report using special tools and validators.
INTRODUCTION
Since the FDA mandated that NDA and IND submissions use the CDISC SEND data standard for non-clinical studies, there has been a steady increase in SEND submissions.
Reviewers have always used the Study Report to conduct regulatory reviews independently. SEND data offers reviewers unlimited opportunities to select subject groupings and timing for testing any hypothesis directly with a computer and analysis scripts. To do that with confidence they need to have confidence in the SEND subject level data. Since the Study Report is the only other report that is signed and audited, it is natural that they will look to it as a “calibration” device to make sure that the SEND data does in fact generate the same summary data if the same assumptions are applied. If that consistency cannot be demonstrated or easily proven, or if the consistency is suspect, then the reviewer cannot depend on the SEND data set, even with its richness, to make regulatory decisions. This paper will discuss specific ways that sponsors can ensure that the consistency of the SEND data with the Study report can assured during preparation, and demonstrable after the SEND data set is generated.
Read full paper here: Validation consistency and conformance checking of SEND datasets (lexjansen.com)