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SEND harmonization & cross-study analysis: A proposal to better harvest the value from SEND data.

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Summary
This summary is machine-generated.

The Standard for Exchange of Nonclinical Data (SEND) has variability issues, impacting pharmaceutical data analysis. Harmonizing SEND implementation can improve nonclinical research productivity and enable cross-study analyses.

Keywords:
BioCelerateCross-study analysisSENDToxicology dataUS FDA

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Area of Science:

  • Pharmacovigilance and Regulatory Science
  • Data Standards in Drug Development
  • Nonclinical Data Management

Background:

  • The Standard for Exchange of Nonclinical Data (SEND) is crucial for US FDA submissions in the pharmaceutical industry.
  • The SEND Implementation Guide (SENDIG) offers flexibility, leading to significant variability in dataset creation.
  • This variability complicates data analysis and hinders cross-study comparisons.

Purpose of the Study:

  • To identify common areas of variability within SEND datasets.
  • To propose strategies for managing this variability.
  • To enable valuable cross-study analysis use cases.

Main Methods:

  • Analysis of common variability in specific SEND domains.
  • Illustrative example using animal age data extraction to demonstrate complexity.
  • Development of a conceptual solution framework.

Main Results:

  • Significant variability exists in SEND dataset creation due to flexible guidelines.
  • Extracting even common data points like animal age presents challenges.
  • A framework involving all stakeholders is proposed to address variability.

Conclusions:

  • Addressing SEND data variability is essential for effective data utilization.
  • Harmonizing SEND implementation will benefit stakeholders and enhance nonclinical research productivity.
  • Standardized data management facilitates routine analysis of archived SEND data.