Organizing and preparing research datasets for regulatory compliance can be a complex and time-consuming challenge. The life science industry’s Standard for Exchange of Nonclinical Data (SEND) initiative sets out detailed guidance to standardize the organization and formatting of datasets to facilitate their review by sponsors, CROs, and regulatory agencies.
The use of SEND is mandated as part of submissions of new drugs for approval by the FDA, meaning understanding and adhering to the guidance has become essential for research groups carrying out preclinical work. These guidelines, however, are multi-faceted and ensuring compliance can be an intimidating task, with errors leading to delays or rejection, increasing timeframes, workloads, and costs.
With this in mind, we’ve prepared a 5-step checklist to make sure that your data is SEND-compliant. It’s important to consider SEND guidelines throughout the process, not only before submission, to prevent costly surprises.
Step 1: Validate Structure Against SENDIG
The SEND Implementation Guide (SENDIG) forms the basis of any compliant submission, and ensuring that your datasets strictly adhere to the guide should be the first step. Even small structural deviations can lead to submission rejection or Information Requests (IRs). You should make sure:
- Each variable, domain, and relationship is aligned with defined standards, including variable naming, domain structure, and metadata consistency.
- You’re validating against the correct SENDIG version for your study. SENDIG is designed for data generated from typical toxicology studies, while SENDIG-DART is for embryo-fetal development studies, SENDIG-Genetox is for genetic toxicology studies, and SENDIG-Animal Rule is for studies conducted under FDA Animal Rule regulations.
- You’re effectively using the tools available. Instem’s SEND Checker, a feature of Submit™, performs comprehensive reviews of datasets to ensure they comply with SENDIG.
Step 2: Verify Data Quality and Completeness
Once you’ve made sure the structure is sound, the next focus is data integrity. A dataset that passes structural checks can still fail if the values are incomplete, inconsistent, or incoherent. A structurally valid dataset that tells a conflicting or unclear story can impact regulators’ confidence in your submission. Discrepancies within datasets, or between data and the study report, are common reasons for FDA feedback. You should ensure that:
- You perform data integrity checks for missing values or logical consistency across domains.
- You have cross-referenced the dataset with your audited draft or final study report.
- You enlist expert advice for complete confidence in your submission. Instem’s SEND Advantage™ Services include SEND Comply, a service through which SEND experts perform deep, comprehensive validation and conformance checks.
Step 3: Review Controlled Terminology Mapping
Standardization refers not only to how data is structured but also to how it is described. Using the proper CDISC Controlled Terminology (CT) ensures your data is machine-readable and interpretable by reviewers. Incorrect or inconsistent terminology will lead to automated validation errors and potential misinterpretation by regulators. What to do:
- Map all data values to CDISC-approved terminology. This includes lab tests, anatomical locations, dosing routes, and outcomes.
- Avoid using custom lab codes, site-specific abbreviations, or legacy terms that aren’t harmonized.
- Implement a centralized terminology manager or template across studies to enforce consistency. Automation helps reduce human error, so don’t rely on manual mapping or memory. SENDirect™ will automatically convert data to SEND Controlled Terminology.
Step 4: Generate High-Quality Supporting Documents
Your dataset needs context, and requires define.xml and nSDRG (non-clinical Study Data Reviewer’s Guide) files to provide background and clarity. These documents are essential for helping reviewers understand your data structure, terminology, and any deviations. Missing, inaccurate, or unclear metadata and reviewer guides can cause confusion and delay. These files are the FDA’s primary reference for understanding how and why your datasets are structured the way they are. Make sure:
- Your define.xml and nSDRG files are submission-ready and compliant with CIDSC and PHUSE guidelines. They should accurately describe the dataset structure, controlled terms, and study-specific notes.
- You don’t leave the generation of these files to the end of the process. Review them early and often to avoid last-minute delays and to ensure alignment with your datasets.
- You maximize the accuracy and efficiency of supporting document generation using bespoke tools. Instem’s Submit includes DefineNow™ to create and validate define.xml, while GuidePro™ will auto-generate the nSDRG with PHUSE-compliant templates.
Step 5: Perform Final Submission Readiness Review
Before hitting ‘send’ on your submission, conduct a holistic review of your entire SEND package. This is an opportunity to catch issues that could delay approval. You should:
- Run a final checklist for each element of the submission: are all the required domains present, has each file passed structural and terminology validation, do data, reports, and supporting documents tell the story?
- Use expert advice and additional review where possible. SEND Advantage Services uses industry-leading specialists to provide comprehensive checks on quality, compliance, and validation to ensure confidence in your submission.
Conclusion
High-quality, SEND-compliant datasets are critical to regulatory success. Performing robust checks throughout dataset generation and validation helps speed up the review process and improve submission outcomes. SEND guidelines are designed to drive the generation of safe, effective therapies, and well-executed processes help ensure that you can focus on what matters most: bringing safe and effective drugs to market faster.
If you want to learn more about the expert advice that Instem’s SEND Advantage Services can offer, or the bespoke software available in Submit, contact one of our experts today.
References
1. SEND | CDISC. March 30, 2021. Accessed July 31, 2025. https://www.cdisc.org/standards/foundational/send
2. Choudhary S, Walker A, Funk K, Keenan C, Khan I, Maratea K. The Standard for the Exchange of Nonclinical Data (SEND): Challenges and Promises. Toxicol Pathol. 2018;46(8):1006-1012. doi:10.1177/0192623318805743
3. SENDIG v3.1.1 | CDISC. March 30, 2021. Accessed July 31, 2025. https://www.cdisc.org/standards/foundational/send/sendig-v3-1-1
4. SENDIG-DART v1.2 | CDISC. June 28, 2023. Accessed July 31, 2025. https://www.cdisc.org/standards/foundational/send/sendig-dart-v1-2
5. SENDIG-Genetox v1.0 | CDISC. June 28, 2023. Accessed July 31, 2025. https://www.cdisc.org/standards/foundational/send/sendig-genetox-v1-0
6. SENDIG-Animal Rule v1.0 | CDISC. September 17, 2019. Accessed July 31, 2025. https://www.cdisc.org/standards/foundational/send/sendig-animal-rule-v1-0
7. Controlled Terminology | CDISC. Accessed July 31, 2025. https://www.cdisc.org/standards/terminology/controlled-terminology
8. SEND Implementation FAQ – WORKING GROUPS – PHUSE Advance Hub. Accessed July 31, 2025. https://advance.hub.phuse.global/wiki/spaces/WEL/pages/26804754/SEND+Implementation+FAQ
