Source: https://tendernation.io/opportunities/01a13ca2-38d6-7177-a4d1-9112570b455e/identifying-high-carbon-footprint-medicines

awarded GB negotiated without publication procedure Suitable for SMEs

# Identifying High Carbon Footprint Medicines

[NHS England & NHS Improvement](https://tendernation.io/buyers/nhs-england-nhs-improvement)

Estimated value

£48,000 to £50,000

Published

9 Feb 2022

Deadline

Closed

14 Jan 2022

## Who can bid

- Buyer says suitable for SMEs

    The buyer ticked “suitable for SMEs” on the notice. Anyone can still bid.
- Buyer says suitable for VCSEs

    The buyer ticked “suitable for voluntary, community and social enterprises” on the notice.
- 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

### Need for the project

- The 2019 NHS Long Term Plan set sustainability commitments for the NHS, which are elaborated in the 'Delivering a Net Zero National Health Service' report.
- The 2020 'Delivering a Net Zero National Health Service' report committed the NHS to reaching net zero carbon emissions across the emissions that it directly controls by 2040 (with an 80% reduction by 2032) and for its full scope, including its supply chain, by 2045 (with an 80% reduction by 2039). Medicines account for 25% of NHS carbon emissions, 5 percentage points being direct emissions, e.g. from inhalers and anaesthetic gases, and 20% being from other medicines, including those emissions embedded in the medicines supply chain.
- Whilst several options exist, it is unclear which methodology is the most practical and usable for the NHS in assessing the carbon footprint of specific medicines, which is essential for determining the next steps in the NHS's strategy to reduce emissions from medicines, particularly those beyond direct emissions from inhalers and anaesthetics. Example of options considered to date:

â&#128;¢ Process mass intensity (PMI) is one methodology of assessing the environmental impact of chemical and pharmaceutical development processes. PMI uses the total mass of input materials required to produce a unit of the target chemical product. It has the advantage of being relatively easy to calculate, where the manufacturing process data is readily available, but has the limitation of being a proxy and still requires manufacturing information

â&#128;¢ Top down economic modelling of medicine supply chains assumes the same intensity of carbon emissions per unit of monetary value. This homogeneity assumption is a well-known limitation of input/output modelling.

- There is limited information available on emissions from active pharmaceutical ingredients (APIs) and the manufacture of them. It is important to note that the API is only one component that contributes to the emissions of medicine manufacturing - many other chemicals and processes could be used in medicine manufacture, which must also be included in the assessment of emissions per medicine.
- There are broader impacts of the production and manufacture of medicines on the environment. The focus of this methodology must be carbon emissions (CO2e), but broader environmental impacts should also be considered to avoid unintended environmental consequences.
- A number of factors must be taken into account when defining medicines related policy measures to reduce carbon emissions. It is critical that any change in policy results in no diminution in patient outcome (ideally an improvement in patient outcomes will be realised). Other factors such as financial impact or supply chain resilience must also be considered.

The objective of this project is therefore to understand the best approach to assess carbon emissions from specific medicines or groups of medicines (e.g. by class)

Read full description

## CPV classification

Health services

Source

Contracts Finder (UK)

[View official notice](https://www.contractsfinder.service.gov.uk/notice/c7768404-b9c7-4da9-9df8-1ed2d0455aa8)

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