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Cross study analyses of SEND data: toxicity profile classification

delete2024-06-08
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OA
AI
M
Mark A. Carfagna *
C
Cm Sabbir Ahmed
S
Susan Butler
T
Tamio Fukushima
W
William Houser
N
Nikolai K. Jensen
B
Brianna Paisley
S
Stephanie Leuenroth-Quinn
K
Kevin Snyder
S
Saurabh Vispute
王文贤 cover
王文贤 (Wenxian Wang)
M
Md Yousuf Ali
DOI:10.1093/toxsci/kfae072delete
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Abstract

Abstract

En 中文
A SEND toxicology data transformation, harmonization, and analysis platform were created to improve the identification of unique findings related to the intended target, species, and duration of dosing using data from multiple studies. The lack of a standardized digital format for data analysis had impeded large-scale analysis of in vivo toxicology studies. The CDISC SEND standard enables the analysis of data from multiple studies performed by different laboratories. This work describes methods to analyze data and automate cross-study analysis of toxicology studies. Cross-study analysis can be used to understand a single compound's toxicity profile across all studies performed and/or to evaluate on-target versus off-target toxicity for multiple compounds intended for the same pharmacological target. This work involved development of data harmonization/transformation strategies to enable cross-study analysis of both numerical and categorical SEND data. Four de-identified SEND datasets from the BioCelerate database were used for the analyses. Toxicity profiles for key organ systems were developed for liver, kidney, male reproductive tract, endocrine system, and hematopoietic system using SEND domains. A cross-study analysis dashboard with a built-in user-defined scoring system was created for custom analyses, including visualizations to evaluate data at the organ system level and drill down into individual animal data. This data analysis provides the tools for scientists to compare toxicity profiles across multiple studies using SEND. A cross-study analysis of 2 different compounds intended for the same pharmacological target is described and the analyses indicate potential on-target effects to liver, kidney, and hematopoietic systems.
Keywords:
computational toxicology
SEND
cross-study analysis
toxicity profile
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Toxicological Sciences cover
Toxicological Sciences
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4.1
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