Planning

Market Research for Medical Device Standalone Software and Consultancy Support

UNIVERSITY OF EDINBURGH

This public procurement record has 1 release in its history.

Planning

03 Mar 2025 at 00:00

OJEU - F1 - Prior Information Notice
Summary of the contracting process

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.

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Notice Information

Notice Title

Market Research for Medical Device Standalone Software and Consultancy Support

Notice Description

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.

Notice Details

Publication & Lifecycle

Open Contracting ID
ocds-r6ebe6-0000792006
Publication Source
Public Contracts Scotland
Latest Notice
https://www.publiccontractsscotland.gov.uk/search/show/search_view.aspx?ID=MAR524976
Current Stage
Planning
All Stages
Planning

Procurement Classification

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

Common Procurement Vocabulary (CPV)

CPV Divisions

48 - Software package and information systems

CPV Codes

48000000 - Software package and information systems

Notice Value(s)

Tender Value
Not specified
Lots Value
Not specified
Awards Value
Not specified
Contracts Value
Not specified

Notice Dates

Publication Date
3 Mar 202511 months ago
Submission Deadline
Not specified
Future Notice Date
1 Aug 2025Expired
Award Date
Not specified
Contract Period
Not specified - Not specified
Recurrence
Not specified

Notice Status

Tender Status
Planned
Lots Status
Planned
Awards Status
Not Specified
Contracts Status
Not Specified

Buyer & Supplier

Contracting Authority (Buyer)

Main Buyer
UNIVERSITY OF EDINBURGH
Contact Name
Iain Davies
Contact Email
idavies@ed.ac.uk
Contact Phone
+44 1316502759

Buyer Location

Locality
EDINBURGH
Postcode
EH1 1HT
Post Town
Edinburgh
Country
Scotland
Major Region (ITL 1)
TLM Scotland
Basic Region (ITL 2)
TLM1 East Central Scotland
Small Region (ITL 3)
TLM13 City of Edinburgh
Delivery Location
TLM75 City of Edinburgh
Local Authority
City of Edinburgh
Electoral Ward
City Centre
Westminster Constituency
Edinburgh East and Musselburgh

Further Information

Notice 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.

Open Contracting Data Standard (OCDS)

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