The long way from raw data to NAM-based information: Overview on data layers and processing steps.

IF 4.5 2区 医学 Q2 MEDICINE, RESEARCH & EXPERIMENTAL
Jonathan Blum, Markus Brüll, Jan G Hengstler, Daniel R Dietrich, Andreas J Gruber, Michele Dipalo, Udo Kraushaar, Iris Mangas, Andrea Terron, Ellen Fritsche, Philip Marx-Stoelting, Barry Hardy, Andreas Schepky, Sylvia Escher, Thomas Hartung, Robert Landsiedel, Alex Odermatt, Magdalini Sachana, Katharina Koch, Arif Dönmez, Stefan Masjosthusmann, Kathrin Bothe, Stefan Schildknecht, Mario Beilmann, Joost B Beltman, Suzanne Fitzpatrick, Aswin Mangerich, Markus Rehm, Silvia Tangianu, Franziska M Zickgraf, Hennicke Kamp, Gerhard Burger, Bob van de Water, Nicole Kleinstreuer, Andrew White, Marcel Leist
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引用次数: 0

Abstract

Toxicological test methods generate raw data and provide instructions on how to use these to determine a final outcome such as a classification of test compounds as hits or non-hits. The data processing pipeline provided in the test method description is often highly complex. Usually, multiple layers of data, ranging from a machine-generated output to the final hit definition, are considered. Transition between each of these layers often requires several data processing steps. As changes in any of these processing steps can impact the final output of new approach methods (NAMs), the processing pipeline is an essential part of a NAM description and should be included in reporting templates such as the ToxTemp. The same raw data, processed in different ways, may result in different final outcomes that may affect the readiness status and regulatory acceptance of the NAM, as an altered output can affect robustness, performance, and relevance. Data management, pro­cessing, and interpretation are therefore important elements of a comprehensive NAM definition. We aim to give an overview of the most important data levels to be considered during the devel­opment and application of a NAM. In addition, we illustrate data processing and evaluation steps between these data levels. As NAMs are increasingly standard components of the spectrum of toxi­cological test methods used for risk assessment, awareness of the significance of data processing steps in NAMs is crucial for building trust, ensuring acceptance, and fostering the reproducibility of NAM outcomes.

从原始数据到基于名称的信息的漫长道路:关于数据层和处理步骤的概述。
毒理学测试方法产生原始数据,并提供如何使用这些数据来确定最终结果的说明,例如将测试化合物分类为命中或未命中。测试方法描述中提供的数据处理管道通常是高度复杂的。通常,要考虑从机器生成的输出到最终命中定义的多层数据。这些层之间的转换通常需要几个数据处理步骤。由于这些处理步骤中的任何更改都可能影响新方法方法(NAMs)的最终输出,因此处理管道是NAM描述的重要组成部分,应该包含在诸如ToxTemp之类的报告模板中。同样的原始数据,以不同的方式处理,可能会产生不同的最终结果,这可能会影响不干体的准备状态和监管接受程度,因为改变的输出可能会影响健壮性、性能和相关性。因此,数据管理、处理和解释是全面的NAM定义的重要元素。我们的目的是概述在开发和应用不结盟运动期间需要考虑的最重要的数据级别。此外,我们还说明了这些数据级别之间的数据处理和评估步骤。由于NAMs日益成为用于风险评估的毒理学试验方法的标准组成部分,因此认识到NAMs中数据处理步骤的重要性对于建立信任、确保接受和促进NAMs结果的可重复性至关重要。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Altex-Alternatives To Animal Experimentation
Altex-Alternatives To Animal Experimentation MEDICINE, RESEARCH & EXPERIMENTAL-
CiteScore
7.70
自引率
8.90%
发文量
89
审稿时长
2 months
期刊介绍: ALTEX publishes original articles, short communications, reviews, as well as news and comments and meeting reports. Manuscripts submitted to ALTEX are evaluated by two expert reviewers. The evaluation takes into account the scientific merit of a manuscript and its contribution to animal welfare and the 3R principle.
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