Completed Engineering Public Health & Healthcare

SmartPSC (Smart Pharma Supply Chain): Application of digital technologies to integrate pharma manufacturing supply chain and enhance efficiency, productivity, flexibility, resilience, and sustainability

In plain English

AI plain-English summary

A single disrupted medicine shipment can cascade into weeks of delays for patients, because pharmaceutical companies still rely on manual coordination across dozens of separate suppliers. SmartPSC aims to replace that fragmented system with a shared digital platform that lets data flow automatically between companies. Currently, a Qualified Person—the individual legally responsible for releasing each medicine batch—must manually assemble data from every supplier before signing off. This process is slow, error-prone, and creates waste. As medicines become more complex and the population ages, the strain on this patchwork system will only grow. The project tackles two concrete problems: first, designing a standardised format for companies to share supply-chain data in real time; second, linking that data so a Qualified Person can make release decisions quickly and safely. If successful, SmartPSC will create a template for future pharmaceutical supply chains. The immediate impact would be fewer shortages, less waste, and faster access to medicines. Over time, machine learning could take over routine decisions, freeing experts to focus on safety-critical questions. The research is applied and industry-led, with direct implications for how the UK manufactures and distributes medicines.

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In order to meet National and International medicines demand, both small and large pharmaceutical companies need to use multiple suppliers. It takes significant effort to coordinate these separate companies and create an integrated plan that safely ensures patients get the medicines they need. Any changes to the plan take time and effort to manage and this creates waste. To add to the complexity, in order to sign off a batch of medicines, a Qualified Person ( QP, the person who assures patient safety for a given company) must see all of this data in order legally to release the medicines into the supply chain. The challenge of assembling this data can add delay. As the requirements of patients change, with an older population along with other constraints such as increasing complexity of medicines, more of the supply chain will migrate towards mixed-company models, putting stress on pricing and the ability of companies to deliver on their promises. The industry can't just 'throw more people at it' forever to solve the problem. Data science can enable people to streamline the movement of information and look at these problems differently. Once the passage of data has been solved it will even be possible to migrate some of the decisions to electronic systems by using Machine Learning (ML) and Artificial Intelligence (AI) solutions. This would allow QPs to focus on important questions. SmartPSC aims to apply these technologies to reduce waste, increase speed and improve access to medicines. Creating a template by which this can robustly be done will be complex, as it will mean connecting ways of working and systems that have not standardly been connected as well as overcoming data security challenges. This project aims to create the foundation for delivering this integrated supply chain vision by leveraging expertise and capabilities across a group of small and large companies within the UK pharma supply chain (SC) to deliver two work packages: 1\. Designing and implementing a way to get everyone to share their information in a quickly usable format, so it can move seamlessly and securely between companies so that we can build a real-time multi-company view of the supply chain. 2\. Link data from multiple companies so a QP can quickly and safely make decisions. By delivering on this scope, we will be able to template future supply chains.

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Original classification

Collaborative R&D

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