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Making sense of SEND; the Standard for Exchange of Nonclinical Data

机译:送送礼; 非界性数据交换的标准

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Abstract The Standard for Exchange of Nonclinical Data (SEND) is currently the preferred submission format for nonclinical animal data by the US FDA and became a requirement on the 18th December 2016. Application of these data standards is the first step to being able to perform cross-study querying and is expected to open up opportunities for data mining and meta-analysis by the pharmaceutical industry. This paper reports on our experiences in developing a tool to allow recent SEND formatted studies to be explored alongside historical nonclinical data already gathered as part of the eTOX project. Combining SEND data with historical data will positively impact the power of any analysis performed and increase the likelihood of being able to detect rare effects. It describes the use of KNIME in generating dose group averages and incidences from individual animal level data captured in SEND. There are a number of options for opening and reading SEND files but the benefits of using KNIME are that it is a free, open source data mining framework which allows the data to be viewed in a holistic manner rather than one domain at a time. Additionally it incorporates several nodes useful for aggregating and visualising the data to more easily identify patterns and trends. Graphical abstract Display Omitted Highlights ? Differences in SEND submissions from multiple sources. ? Use of KNIME to read and aggregate SEND. ? Exploring SEND alongside legacy data gathered in the eTOX project.
机译:摘要非临床数据交换标准(发送)是美国FDA的非临床动物数据的首选提交格式,并成为2016年12月18日的要求。这些数据标准的应用是能够执行交叉的第一步-Study Querying,预计将为制药行业开辟数据挖掘和荟萃分析的机会。本文报告了我们开发工具,以允许最近发送格式化研究的工具,以便与已收集的历史非界限数据一起探索的历史非纯粹项目。结合发送数据与历史数据将积极影响任何分析的功率,并增加能够检测稀有效果的可能性。它描述了在发送的单个动物级数据中生成剂量组平均值和发短信中的使用。打开和读取发送文件有许多选项,但使用KNIME的好处是它是一个自由的开源数据挖掘框架,它允许一次以整体方式查看数据而不是一个域。此外,它还包含几个有用的节点,可用于聚合和可视化数据,以更容易地识别模式和趋势。图形抽象显示省略了亮点?从多个来源发送提交的差异。还使用KNIME读取和聚合发送。还探索在Etox项目中收集的遗留数据伴随着发送。

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