Lhasa Limited, Granary Wharf House, 2 Canal Wharf, Leeds, LS11 5PS, United Kingdom.
Regul Toxicol Pharmacol. 2017 Dec;91:77-85. doi: 10.1016/j.yrtph.2017.10.012. Epub 2017 Oct 21.
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.
《非临床数据交换标准》(SEND)目前是美国 FDA 首选的非临床动物数据提交格式,并于 2016 年 12 月 18 日成为强制性要求。应用这些数据标准是能够进行跨研究查询的第一步,预计将为制药行业的数据挖掘和荟萃分析开辟机会。本文报告了我们在开发一种工具方面的经验,该工具可用于探索最近按照 SEND 格式进行的研究,同时还可以探索作为 eTOX 项目一部分已经收集的历史非临床数据。将 SEND 数据与历史数据相结合将对执行的任何分析的功效产生积极影响,并增加检测罕见效应的可能性。本文描述了如何在 SEND 中使用 KNIME 从捕获的单个动物水平数据生成剂量组平均值和发生率。有许多打开和读取 SEND 文件的选项,但使用 KNIME 的好处是它是一个免费的、开源的数据挖掘框架,允许以整体方式查看数据,而不是一次一个域。此外,它还包含了几个用于聚合和可视化数据的节点,以便更容易地识别模式和趋势。