Source: https://tendernation.io/opportunities/01a13cb4-c43a-72c7-888c-2c18c1436aff/cefas23-144-contract-for-pathsafe-pathogen-machine-learning

awarded GB direct award procedure Suitable for SMEs

# CEFAS23-144 Contract for PATHSAFE Pathogen machine learning

[Cefas](https://tendernation.io/buyers/cefas)

Open field

Estimated value

£50,000 to £60,000

Published

21 Dec 2023

Deadline

Closed

19 Dec 2023

## Who can bid

- Buyer says suitable for SMEs

    The buyer ticked “suitable for SMEs” on the notice. Anyone can still bid.
- Small contract value

    Valued under £135,018 including VAT, the lowest Procurement Act threshold for goods and services.

[More contracts for small businesses and VCSEs](https://tendernation.io/opportunities/for-small-businesses)

## About this tender

Background:

As part of the Pathogen Surveillance in Agriculture, Food and Environment (PATHSAFE) programme, Cefas are conducting pilot surveillance studies for key foodborne disease pathogens. Cefas have collected and analysed weekly river water samples over a time series of 2 x 3 month periods.

Additional analyses of these samples and data generated is required to generate a tool for predicting the risk of foodborne disease in river catchments and shellfish harvesting areas.

Requirement:

Cefas require specialised services to generate 16S rRNA sequence data from river water samples and the subsequent bioinformatic analyses of 16S rRNA and whole genome sequences via a customised pipeline. A machine-learning method is required to be developed for the rapid analysis and interpretation of 16S data, along with a

dashboard and customised web platform for visualisation of 16S and microbial genomic results.

DNA samples will be shipped from the UK to UAB by the Environment Agency at nocost to UAB. Whole genome sequence data will be provided to UAB by Cefas.

## CPV classification

Analysis services

Source

Contracts Finder (UK)

[View official notice](https://www.contractsfinder.service.gov.uk/notice/41a0428d-d535-4f9a-9c23-f40f9a2d4531)

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