--- title: "Market Research for Medical Device Standalone Software and Consultancy Support" ocid: "ocds-r6ebe6-0000792006" canonical_url: "https://d3tenders.com/contract/?ocid=ocds-r6ebe6-0000792006" markdown_url: "https://d3tenders.com/contract/ocds-r6ebe6-0000792006.md" json_url: "https://d3tenders.com/contract/ocds-r6ebe6-0000792006.json" source: "Public Contracts Scotland" current_stage: "Planning" buyer: "UNIVERSITY OF EDINBURGH" published: "2025-03-03" --- # Market Research for Medical Device Standalone Software and Consultancy Support Buyer: UNIVERSITY OF EDINBURGH Current stage: Planning OCID: ocds-r6ebe6-0000792006 [View canonical contract page](https://d3tenders.com/contract/?ocid=ocds-r6ebe6-0000792006) [Download OCDS JSON](https://d3tenders.com/contract/ocds-r6ebe6-0000792006.json) ## Summary The University of Edinburgh is in the planning stage for their procurement process titled "Market Research for Medical Device Standalone Software and Consultancy Support." This procurement falls under the Education industry category and is located in Edinburgh, Scotland (UKM75). Key details include the need for external solutions and services to create standalone software fit for UKCA marking as a Class I Medical Device and to provide consultancy support for regulatory compliance. The procurement process aims to gather up-to-date information and feedback from potential vendors, with interested suppliers encouraged to contact the University by 21 March 2025. The future notice date for this opportunity is set for 1 August 2025. This tender offers significant business growth opportunities, especially for firms skilled in medical device software development and regulatory consultancy. Businesses specialising in software engineering, medical device compliance, and legal advisory services related to UKCA marking and self-certification processes will find this project particularly suitable. The project will leverage cutting-edge machine learning algorithms, promising wide-reaching impacts in clinical decision support for acute heart attack diagnosis. Companies capable of providing robust, compliant software solutions and expert consultancy are well-positioned to compete for this contract and contribute to improving healthcare outcomes. ## Notice The University of Edinburgh is developing a Clinical Decision Support Tool for diagnosing 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 to understand market capabilities. ### Lot Information Lot 1 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. ## Key Details | Field | Value | | --- | --- | | Publication source | Public Contracts Scotland | | Latest notice | https://www.publiccontractsscotland.gov.uk/search/show/search_view.aspx?ID=MAR524976 | | Notice type | OJEU - F1 - Prior Information Notice | | Procurement type | Standard | | Procurement category | Goods | | Procurement method | Not Specified | | Procurement method details | Not specified | | Tender suitability | Not specified | | Awardee scale | Not specified | | All stages | Planning | ## Dates | Field | Value | | --- | --- | | Publication date | 3 Mar 2025 | | Submission deadline | Not specified | | Future notice date | 1 Aug 2025 | | Award date | Not specified | | Contract period | Not specified | | Recurrence | Not specified | ## Values | Field | Value | | --- | --- | | Tender value | Not specified | | Lots value | Not specified | | Awards value | Not specified | | Contracts value | Not specified | ## Status | Field | Value | | --- | --- | | Tender status | Planned | | Lots status | Planned | | Awards status | Not specified | | Contracts status | Not specified | ## Buyer | Field | Value | | --- | --- | | Main buyer | UNIVERSITY OF EDINBURGH | | Locality | EDINBURGH | | Post town | Edinburgh | | Postcode | EH1 1HT | | Country | Scotland | | ITL 1 | TLM Scotland | | ITL 2 | TLM1 East Central Scotland | | ITL 3 | TLM13 City of Edinburgh | | Local authority | City of Edinburgh | | Electoral ward | City Centre | | Westminster constituency | Edinburgh East and Musselburgh | | Delivery location | TLM75 City of Edinburgh | ## CPV Codes ### Divisions - 48 - Software package and information systems ### Codes - 48000000 - Software package and information systems ## Release History - 3 Mar 2025 at 00:00 - Planning - OJEU - F1 - Prior Information Notice - https://www.publiccontractsscotland.gov.uk/search/show/search_view.aspx?ID=MAR524976 ## Documents - https://www.publiccontractsscotland.gov.uk/search/show/search_view.aspx?ID=MAR524976 Market Research for Medical Device Standalone Software and Consultancy Support - The University of Edinburgh is developing a Clinical Decision Support Tool for diagnosing 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 to understand market capabilities. ## Notice URLs - http:// - http://www.ed.ac.uk - http://www.publiccontractsscotland.gov.uk/Search/Search_Switch.aspx?ID=792006 - https://api.publiccontractsscotland.gov.uk/v1/Notice?id=ocds-r6ebe6-0000792006 - https://decision-support.shinyapps.io/code-acs/ - https://www.nature.com/articles/s41591-023-02325-4 ## Provenance This Markdown file is an alternate public rendering of the D3 Tenders contract record. The canonical page is https://d3tenders.com/contract/?ocid=ocds-r6ebe6-0000792006. The underlying structured data is available as OCDS JSON at https://d3tenders.com/contract/ocds-r6ebe6-0000792006.json.