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CDISC defines SEND as an implementation of the SDTM standard for nonclinical studies. SEND specifies a way to collect and present nonclinical data in a consistent format. SEND is one of the required standards for data submission to FDA. SEND = Standard for the Exchange of Nonclinical Data.
Sponsors are currently focused on processes and tools to receive, transform, store and create submission-ready SEND datasets. Their decisions and implementations are presently driven by the nature and variability of their data sources, understanding of SEND, determining how best to prepare and generate SEND datasets that will successfully load into NIMS, and putting in place quality assurance and data governance controls. These are key foundation steps in any implementation. Let us understand SEND compliance better through SEND implementation objectives, stakeholders, requirements, challenges, and opportunities.
SEND objectives
Sponsors need a shared vision for how SEND implementation will improve their R&D operations. More than implementing a new data format, it should:
SEND stakeholders
Here is a list of all clinical study stakeholders involved in SEND dataset creation and compliance.
Sponsor requirements
CROs can’t implement all SEND compliance requirements, even for sponsors outsourcing 100% of their nonclinical studies. Here are the requirements.
New elements of the sponsor’s study workflow include mapping internal LIMS data extracts to SEND data model, integrating external CRO datasets, dataset versioning and error handling, validation and submission of integrated datasets to FDA, creating Define Files, Validation Reports, and Study Data Review Guides and coordinated response to FDA queries across Study Reports and SEND datasets
Implementation challenges
SEND implementation is more complex and time-consuming than most sponsors expect! Here are a few of the challenges.
Implementation opportunities
The Potential efficiencies arising from SEND compliance include higher initial data quality and fewer protocol amendments with early access to interim datasets. Other benefits include automated dataset integration and versioning, automated study table generation, expedited FDA review and faster response to review questions
As the industry’s experience evolves, it is clear that sponsor implementations will extend into study planning and preparation stages, and expand the needs of their processes and tools to support submission requirements. It is only then that they will likely step into the realm of how they themselves can routinely consume and use standardized data in research and development activities.
MaxisIT
At MaxisIT, we clearly understand strategic priorities within clinical R&D, and we can resonate that well with our similar experiences of implementing solutions for improving Clinical Development Portfolio via an integrated platform-based approach; which delivers timely access to study specific as well as standardized and aggregated clinical trial operations as well as patient data, allows efficient trial oversight via remote monitoring, statistically assessed controls, data quality management, clinical reviews, and statistical computing. Moreover, it provides capabilities for planned vs. actual trending, optimization, as well as for fraud detection and risk-based monitoring.
Moreover, it provides capabilities for planned vs. actual trending, optimization, as well as for fraud detection and risk-based monitoring. MaxisIT’s Integrated Technology Platform is purpose-built solution, which helps Pharmaceutical & Life sciences industry by “Empowering Business Stakeholders with Integrated Computing, and Self-service Analytics in the strategically externalized enterprise environment with major focus on the core clinical operations data as well as clinical information assets; which allows improved control over externalized, CROs and partners driven, clinical ecosystem; and enable in-time decision support, continuous monitoring over regulatory compliance, and greater operational efficiency at a measurable rate”.
10 Jun 2019
1 Aug 2019