Standard for Exchange of Non-clinical Data

Standard for Exchange of Non-clinical Data (SEND) is a regulatory standard designed to facilitate the submission, exchange, and review of non-clinical study data in a consistent format. Developed by the Clinical Data Interchange Standards Consortium (CDISC), SEND is part of a suite of data standards aimed at streamlining the process of submitting data to regulatory authorities such as the United States Food and Drug Administration (FDA).

Overview

SEND is specifically tailored for non-clinical data, which refers to data generated from animal studies that are conducted to assess the safety and efficacy of new pharmaceuticals and chemicals. The standard defines a way to organize and format this data, making it easier for both sponsors submitting data and regulatory reviewers to navigate and analyze the information. SEND is built upon the principles of the Study Data Tabulation Model (SDTM), which is a standard for clinical and non-clinical data.

Importance

The adoption of SEND is crucial for several reasons. Firstly, it enhances the efficiency of the drug development process by reducing the time required for data review and approval. Secondly, it improves data quality and consistency across studies, facilitating better safety assessments and decision-making. Lastly, compliance with SEND is mandatory for certain types of submissions to the FDA, making it an essential standard for pharmaceutical companies and research organizations involved in drug development.

Components

SEND includes several key components:

• Domains: Predefined categories of data, such as demographics, laboratory test results, and findings from pathology reports.
• Variables: Specific attributes within each domain, such as test result values or animal identifiers.
• Controlled Terminology: Standardized terms and definitions used to ensure consistency in data reporting.

Implementation

Implementing SEND requires a thorough understanding of the standard and a detailed mapping of study data to the SEND format. This often involves the use of specialized software tools and may require significant effort to convert historical study data into the SEND format. Organizations must also ensure that their data management practices are aligned with SEND requirements, including data quality checks and validation processes.

Regulatory Requirements

In the United States, the FDA has mandated the use of SEND for certain types of regulatory submissions. This requirement is part of the FDA's broader initiative to standardize electronic submission of study data, which also includes standards like SDTM and Analysis Data Model (ADaM) for clinical data. The specific requirements and timelines for SEND compliance may vary depending on the type of submission and the regulatory pathway.

Challenges and Considerations

While SEND offers numerous benefits, its implementation is not without challenges. These include the need for significant investment in training, software, and process changes, as well as the ongoing effort to keep up with updates and revisions to the standard. Additionally, organizations must carefully manage the transition to SEND to ensure that data quality and integrity are maintained.

Conclusion

The Standard for Exchange of Non-clinical Data represents a significant step forward in the standardization and efficiency of drug development processes. By facilitating the consistent and efficient exchange of non-clinical study data, SEND plays a crucial role in advancing public health and safety.

Standard for Exchange of Non-clinical Data Resources
Need Help Finding a Doctor? Need help finding a doctor or specialist anywhere in the world? Explore our world directory. WikiMD's DocFinder can assist you in locating millions of physicians.	Medical Knowledge Access the latest research - Most recent articles Ongoing trials.

Translate to: East Asian 中文, 日本, 한국어, South Asian हिन्दी, Urdu, বাংলা, తెలుగు, தமிழ், ಕನ್ನಡ,
Southeast Asian Indonesian, Vietnamese, Thai, မြန်မာဘာသာ, European español, Deutsch, français, русский, português do Brasil, Italian, polski