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Related Concept Videos

Pharmacovigilance01:19

Pharmacovigilance

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Post-marketing surveillance is a critical component of pharmaceutical regulation, often uncovering unanticipated adverse drug reactions (ADRs) once a drug is widely used over an extended period.
This process, termed pharmacovigilance, aims to detect, evaluate, and minimize harmful effects related to medication use. The data collection for pharmacovigilance depends on spontaneous reporting systems, where healthcare professionals or patients voluntarily report suspected ADRs.
In some cases, there...
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Demonstration of the Sequence Alignment to Predict Across Species Susceptibility Tool for Rapid Assessment of Protein Conservation
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Cross study analyses of SEND data: toxicity profile classification.

Mark A Carfagna1, Cm Sabbir Ahmed2,3, Susan Butler2,3

  • 1Eli Lilly & Company, Indianapolis, IN 46285, United States.

Toxicological Sciences : an Official Journal of the Society of Toxicology
|June 9, 2024
PubMed
Summary
This summary is machine-generated.

A new platform standardizes toxicology data, enabling cross-study analysis to identify compound-specific toxicity profiles and potential on-target effects. This improves understanding of drug safety across multiple in vivo studies.

Keywords:
SENDcomputational toxicologycross-study analysistoxicity profile

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Area of Science:

  • Toxicology
  • Data Science
  • Pharmacology

Background:

  • Large-scale analysis of in vivo toxicology studies was impeded by the lack of standardized digital data formats.
  • The CDISC SEND standard facilitates multi-laboratory data analysis, but requires harmonization and transformation strategies.

Purpose of the Study:

  • To develop a platform for toxicology data transformation, harmonization, and analysis to improve identification of unique findings.
  • To enable automated cross-study analysis for understanding compound toxicity profiles and evaluating on-target vs. off-target effects.

Main Methods:

  • Developed data harmonization and transformation strategies for numerical and categorical SEND data.
  • Utilized four de-identified SEND datasets from the BioCelerate database for analysis.
  • Created a cross-study analysis dashboard with visualizations and a user-defined scoring system.

Main Results:

  • Established toxicity profiles for key organ systems (liver, kidney, male reproductive tract, endocrine, hematopoietic) using SEND domains.
  • Demonstrated cross-study analysis of two compounds targeting the same pathway.
  • Analyses indicated potential on-target toxicities in liver, kidney, and hematopoietic systems.

Conclusions:

  • The developed platform provides tools for scientists to compare toxicity profiles across multiple studies using SEND.
  • Automated cross-study analysis enhances the understanding of compound-specific toxicity and on-target effects.