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| Source: | Contracts Finder |
| Notice Type: | Award notice |
| Buyer: | Public Health England |
| Main Category: | Goods |
| Procurement Method: | Negotiated procedure without prior publication (above threshold) |
| Tender Status: | Closed |
Pipeline status
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Application Deadline
5 November 2021
Closed
Estimated Value
£425,000
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| £425,000 |
| Release Date: | 13 April 2023 |
| Application Deadline: | 5 November 2021 |
| Contract Start Date: | 10 December 2021 |
| Contract End Date: | 9 December 2022 |
| Contract Duration: | 1.0 years |
| Procurement ID (OCID): | ocds-b5fd17-ea8e338c-a8b7-4106-be2c-9df1e2cc2fff |
| Notice Reference: | 486643ab-bae7-4ded-87ad-e777a5975c7c-635145 |
View Original Notice
Access the full notice on the official portal
Awarded to
| Award value: | £425,000 |
| Award decision date: | 10 December 2021 |
| Award status: | Active |
Award to Akoya Biosciences for the purchase of a multiplex fluorescence slide scanner with quantitative pathology imaging and analysis to be used in the Research Department, Porton. The provision of a Multiplex Fluorescence Scanner will enable UK HSA to produce quantitative multiplex image analysis, with elements of the application of artificial intelligence in pathology (advance image analysis, such as tissue classification, phenotyping or pattern recognition) to be applied to ongoing and future research projects focusing on high priority activities including COVID-19, Ebola, Zika, Crimean Congo Haemorrhagic Fever, Chikungunya, Zika virus infection, Q Fever, Anthrax, Melioidosis, Clostridium difficile-Associated Disease, Tuberculosis, Monkeypox, Influenza, Pertussis, Meningococcal disease, Group B Streptococcal disease, Legionnaires Disease, Healthcare Acquired Infections, Anti-Microbial Resistance, etc. Importantly, this workstation will enable quantitative multiplex image analysis, with elements of the application of artificial intelligence in pathology (advance image analysis), such as tissue classification, phenotyping or pattern recognition. Moreover, the automated tool with associated algorithms will be able to eliminate the autofluorescence generated in every tissue slide. The system will increase resilience as it would be able to scan conventional brightfield stained slides and will be able to produce digital H&E e-slides from fluorescence-stained slides, reducing the workload in the laboratory.