Market Research for Medical Device Standalone Software and Consultancy Support

The University of Edinburgh is developing a Clinical Decision Support Tool for the diagnosis of acute heart attack in the Emergency Department. The research team involved has recently developed and published the research surrounding the machine learning algorithm (XGBoost)(https://www.nature.com/articles/s41591-023-02325-4). An example of the algorithm’s inputs and outputs for educational purposes only are available as a shiny app (https://decision-support.shinyapps.io/code-acs/). The University seeks to commission external solutions and services for the following tasks: 1. The creation of standalone software which will be fit for UKCA marking as a Class I Medical Device under the current legislation. 2. Consultancy support for the regulatory process, providing systems and expertise to ensure all relevant legislation has been complied with. This will include any steps required for self-certification and device registration. The objective of this exercise is to obtain up-to-date information and feedback from potential vendors in order to understand market capabilities. Interested suppliers are advised to contact the University via this notice if they are interested in knowing more about one, or both, of the requirements by Friday 21 March 2025.