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.