Cross study analyses of SEND data: toxicity profile classification.

IF 3.4 3区 医学 Q2 TOXICOLOGY Toxicological Sciences Pub Date : 2024-08-01 DOI:10.1093/toxsci/kfae072
Mark A Carfagna, Cm Sabbir Ahmed, Susan Butler, Tamio Fukushima, William Houser, Nikolai Jensen, Brianna Paisley, Stephanie Leuenroth-Quinn, Kevin Snyder, Saurabh Vispute, Wenxian Wang, Md Yousuf Ali
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Abstract

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.

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SEND 数据的交叉研究分析:毒性特征分类。
创建 SEND 毒理学数据转换、统一和分析平台的目的,是为了利用多项研究数据,更好地识别与预期目标、物种和给药持续时间有关的独特发现。缺乏用于数据分析的标准化数字格式阻碍了体内毒理学研究的大规模分析。CDISC SEND 标准可对来自不同实验室的多项研究数据进行分析。这项工作介绍了对毒理学研究进行数据分析和自动交叉研究分析的方法。交叉研究分析可用于了解单一化合物在所有研究中的毒性概况,和/或评估针对同一药理靶点的多种化合物的靶上与靶下毒性。这项工作包括开发数据协调/转换策略,以便对数字和分类 SEND 数据进行跨研究分析。分析中使用了 BioCelerate 数据库中的四个去标识化 SEND 数据集。利用 SEND 域为肝、肾、男性生殖道、内分泌系统和造血系统等关键器官系统建立了毒性概况。还创建了一个跨研究分析仪表板,内置用户定义的评分系统,用于自定义分析,包括可视化评估器官系统级别的数据和深入分析单个动物数据。这种数据分析为科学家提供了使用 SEND 比较多项研究毒性概况的工具。报告介绍了针对相同药理靶点的两种不同化合物的交叉研究分析,分析结果表明了对肝、肾和造血系统的潜在靶点效应。
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来源期刊
Toxicological Sciences
Toxicological Sciences 医学-毒理学
CiteScore
7.70
自引率
7.90%
发文量
118
审稿时长
1.5 months
期刊介绍: The mission of Toxicological Sciences, the official journal of the Society of Toxicology, is to publish a broad spectrum of impactful research in the field of toxicology. The primary focus of Toxicological Sciences is on original research articles. The journal also provides expert insight via contemporary and systematic reviews, as well as forum articles and editorial content that addresses important topics in the field. The scope of Toxicological Sciences is focused on a broad spectrum of impactful toxicological research that will advance the multidisciplinary field of toxicology ranging from basic research to model development and application, and decision making. Submissions will include diverse technologies and approaches including, but not limited to: bioinformatics and computational biology, biochemistry, exposure science, histopathology, mass spectrometry, molecular biology, population-based sciences, tissue and cell-based systems, and whole-animal studies. Integrative approaches that combine realistic exposure scenarios with impactful analyses that move the field forward are encouraged.
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