Related Experiment Video
Updated: Jun 24, 2025
16:02
Demonstration of the Sequence Alignment to Predict Across Species Susceptibility Tool for Rapid Assessment of Protein Conservation
Published on: February 10, 2023
2.7K
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.
Summary
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.
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.
