SEND's Growing Global Relevance
While SEND (Standard for Exchange of Nonclinical Data) originated as a U.S. FDA requirement, its global expansion is accelerating as other regulatory agencies explore the format for preclinical data submission. Most notably, the European Medicines Agency (EMA) launched a Proof-of-Concept (PoC) in January 2024 to assess how CDISC SEND can improve data review, strengthen validation, and enhance the workflow for evaluating study results.
The EMA has stated that it intends to closely align with the FDA’s SEND dataset requirements rather than developing separate European standards. This alignment approach supports the future of SEND by enabling sponsors to prepare datasets once and use them across multiple regions, reducing duplication, improving digitization, and supporting greater automation in regulatory processes. As the PoC progresses, sponsors should continue to monitor EMA updates for official guidance, timelines, and further analytics-driven enhancements.
For organizations looking to streamline their SEND conversion and submissions, our SEND Conversion Service provides expert support to ensure datasets are fully compliant and ready for global regulatory review.
From Compliance to Intelligence: SEND's Expanding Role
When SEND (Standard for Exchange of Nonclinical Data) was first introduced by the FDA's CDER and CBER, it primarily served as a compliance tool standardizing the format of nonclinical data.
Today, SEND is evolving into a strategic enabler of digital transformation in regulatory science. As global regulatory agencies explore the future of SEND and move toward preclinical data submission using structured datasets, the focus has shifted beyond mere compliance. These datasets now support analytics, workflow optimization, and automation, enabling visualization and emerging computational approaches.
By transforming static study reports into machine-readable SEND datasets, SEND provides the foundation for deeper validation and scientific insight, turning regulatory data into a strategic asset.
A Global Perspective: SEND Beyond the U.S.
FDA: The Established Foundation
The U.S. FDA continues to require SEND for preclinical data submission across CDER and CBER. The current implementation follows the SEND Implementation Guide (SENDIG) version 3.1.1, with version 4.0 in development.
Reviewers use SEND datasets to reproduce study findings, ensure consistency, and compare results across compounds or studies. As part of the agency’s ongoing digital transformation, SEND is increasingly integrated into regulatory workflow tools, supporting automation, enhanced validation, and advanced analytics in nonclinical data review.
EMA: Exploring Alignment
The EMA's Proof-of-Concept (PoC) pilot, launched in January 2024, is exploring SEND's potential to enhance preclinical data submission and streamline nonclinical data review. While formal requirements are not yet established, the EMA’s stated approach indicates potential alignment with the FDA’s SEND Implementation Guide (SENDIG).
This alignment strategy, if implemented, would allow sponsors to:
Prepare SEND datasets based on FDA guidance
Submit consistent data to multiple agencies with minimal rework
Focus on data quality, interpretation, and validation rather than managing format differences
Sponsors interested in submitting SEND data to the EMA should consult the agency’s current guidance and stay informed about developments from the ongoing PoC, which supports broader digitization and automation of regulatory workflows.
Global Outlook
Other ICH regions, including Japan's PMDA, are closely monitoring SEND developments. While formal SEND mandates have not yet been established outside the U.S., the trend toward structured, CDISC SEND-aligned data exchange continues to gain attention internationally.
A unified global ecosystem for preclinical data submission and digital regulatory workflows remains a long-term aspiration. Achieving practical harmonization will require ongoing coordination among regulatory authorities, supporting automation, validation, and analytics in nonclinical data management.
Digital Submissions: The Next Evolution
The future of regulatory submissions is moving toward data-first, digital ecosystems. Key trends driving this transformation include:
- Integration with eCTD v4.0 — SEND datasets and metadata are being designed to fit seamlessly into next-generation submission structures
- Enhanced review tools — Regulators are increasingly developing capabilities to analyze SEND data directly within review systems, complementing traditional PDF-based assessments
- Cross-domain integration — Linking nonclinical (SEND) with clinical (SDTM, ADaM) datasets enables a more holistic understanding of safety and efficacy profiles, supporting analytics, workflow optimization, and automation
For organizations looking to ensure their regulatory submission systems are fully compliant and optimized for SEND and eCTD v4.0, our Computer System Validation (CSV) Service provides expert guidance and support.
SEND and Emerging Technologies: Current Reality vs. Future Potential
SEND and the Rise of AI in Regulatory Science
With growing interest in artificial intelligence (AI) and machine learning (ML) across the pharmaceutical industry, structured data standards like SEND are gaining additional strategic value.
AI and ML tools require clean, consistent, and machine-readable data characteristics that SEND datasets provide. However, it is important to distinguish between current applications and future potential for analytics, workflow optimization, and automation in regulatory and nonclinical data management.
Current State of AI in Regulatory Review
- Regulatory agencies are in the early exploratory stages of applying artificial intelligence (AI) to review processes. Basic automation for data validation and quality checks is being implemented, while SEND-compliant datasets enable more efficient analytics and computational analysis of nonclinical data.
Future Potential of SEND in AI-Driven Regulatory Science
Key emerging capabilities include:
AI-driven anomaly detection and pattern recognition in toxicology
Cross-study computational analyses to identify safety signals
Decision-support tools to assist regulatory reviewers
Having SEND-compliant datasets positions organizations to leverage these capabilities as they mature. SEND provides the foundational infrastructure for automation, analytics, and advanced computational approaches in nonclinical regulatory science though widespread AI adoption in regulatory review is still evolving.
SEND's Role in NAMs and Computational Toxicology
SEND plays a critical role in consortium initiatives advancing New Approach Methodologies (NAMs) innovative tools and models aimed at reducing reliance on animal testing. Consortia such as Biocelerate, the FDA’s Predictive Toxicology Roadmap, NCATS, and CDISC’s cross-domain collaborations are leveraging standardized SEND data to:
Develop and validate computational models for toxicity prediction
Facilitate integration between traditional in vivo and alternative in vitro/in silico data
Enable regulatory consideration of NAM-based evidence through structured, traceable SEND datasets
By creating a consistent foundation for preclinical data submission, SEND helps bridge traditional toxicology and next-generation digital science, supporting a future where regulatory decisions are informed by both empirical and predictive data sources.
Preparing for the Global Future of SEND
Organizations can take actionable steps today to enhance their SEND strategies:
Monitor global alignment efforts — Track developments from the EMA’s PoC and CDISC’s cross-agency initiatives to support global SEND adoption
Ensure quality and consistency — Maintain SEND datasets that accurately reflect study reports and preserve clear traceability to source data
Stay current with SENDIG versions — Understand version requirements and plan for transitions to support ongoing digital transformation and workflow optimization
While substantial harmonization progress is being made, sponsors should recognize that some regional variations in study design, species selection, or endpoints may still require dataset adaptations. The goal is to maximize reusability while maintaining compliance with specific agency requirements.
Conclusion
The future of SEND is increasingly global, digital, and data-driven. With the EMA exploring alignment with FDA standards, sponsors have the opportunity to build SEND strategies that support multiple regulatory pathways moving toward a more efficient “prepare once, adapt minimally” model.
As interest grows in AI, computational toxicology, and NAMs, structured data standards like SEND will become increasingly important for enabling faster insights, more sophisticated analytics, and enhanced regulatory review capabilities. What began as a compliance requirement has evolved into a critical component of digital transformation in drug development connecting global regulators, workflow optimization, data science, and the next era of nonclinical innovation.
FAQs About SEND
1. What is the future of SEND?
SEND is evolving into a global, digital, and data-driven standard. Beyond compliance, it supports AI, analytics, computational toxicology, and streamlined preclinical data submission, enabling sponsors to prepare datasets once and submit across multiple agencies.
2. What is SEND and why is it important?
SEND standardizes nonclinical data for regulatory submissions, ensuring consistency, traceability, and compliance. It also enables better workflow, automation, and digital transformation in regulatory review.
3. How does SEND support preclinical data submission?
SEND provides structured, machine-readable datasets that reduce duplication and improve efficiency. Sponsors can submit data consistently across FDA, EMA, and other agencies, supporting validation and faster regulatory review.
4. How is SEND being adopted globally?
Agencies like the FDA, EMA, Japan’s PMDA, and CDISC are working toward global SEND alignment. Initiatives include Proof-of-Concept pilots, cross-domain collaborations, and adoption of SENDIG versions to harmonize data standards internationally.
5. How does SEND enable AI and advanced analytics?
SEND datasets support automation, AI, and ML tools. They allow anomaly detection, pattern recognition, cross-study analyses, and decision-support systems, improving workflow and regulatory efficiency.
6. What is SEND’s role in NAMs and computational toxicology?
SEND provides a consistent foundation for integrating in vivo, in vitro, and in silico data, supporting predictive models and enabling regulatory consideration of NAM-based evidence.
7. How can organizations strengthen their SEND strategies?
Sponsors should monitor global alignment, ensure dataset quality and traceability, stay current with SENDIG versions, and implement workflow and automation enhancements to maximize reuse and maintain compliance.
8. Why is SEND strategic beyond compliance?
SEND has evolved into a critical tool for digital transformation, AI adoption, and global harmonization. Structured SEND datasets enable faster insights, sophisticated analytics, improved workflow, and more informed regulatory decision-making.