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The proliferation of Artificial Intelligence (AI) in our lives has set about a true revolution in how we collect, organize and use data. Pharma supply chains are no exception, with imaginative use of AI offering innovative solutions to the sector’s complex challenges. According to GlobalData, the worldwide data and analytics market is projected to grow to US$190 billion by 2028, with the pharmaceutical sector contributing 1.1% and the healthcare sector contributing 3.8%[i].
Much of this is driven by the automation of manual activities. For instance, in manufacturing, AI can streamline batch record reviews by quickly processing large volumes of data, identifying errors, and ensuring compliance with regulatory standards, all of which traditionally requires significant human time and effort. In supply chain management, AI can play a crucial role in monitoring risks and anomalies.
AI has also been leveraged to provide predictive insights that are valuable for planning and scheduling. By analyzing historical data and current trends, AI can forecast demand, optimize inventory levels and suggest the best times for production activities. These insights enable pharmaceutical companies and their contract service providers to make faster, more informed decisions, to allocate resources more effectively, and to improve overall operational efficiency. As AI technology continues to develop, its applications are predicted to expand exponentially, offering even more innovative solutions.
The increasing use of AI in the pharma supply chain
Dermot Somers is Director of Strategic Sourcing at Sharp, which has been providing commercial packaging services to pharmaceutical companies for more than 70 years. Somers explains that since the 2021 supply chain disruptions, AI has been increasingly integrated into a range of software tools for data analytics, tailored alerts and risk management.
“We owe it to our pharma clients to have a strong focus on risk management,” he says. “We are using AI to proactively identify a wide range of potential supply chain disruptions. Customized alerts are automatically sent to our sourcing team for their review, which will trigger action plans when appropriate. Our first test case was the US East Coast port strike last year[ii]. The minute that the unions announced plans to strike, I received digital alerts and we were able to initiate our action plan the next day, to prepare for potential disruption and communicate that plan to our clients.
“Thankfully, those port strikes were averted; however, we were way out in front of it. We were able to connect with suppliers immediately to establish appropriate contingency plans ensuring there would be no impact to our clients, even if the strike had gone on for months. From a supply chain risk perspective, AI offered us the visibility we needed to react faster than traditional tools would have and thereby continue to support our clients with timely and consistent delivery.”
AI alerts – real-time business critical information from collation of news reports and other data – is one way to stay ahead of the game when it comes to avoiding disruptions. However, AI within the pharma supply chain must be used carefully.
Keeping humans in the loop
John Hoey is Sharp’s Director of Enterprise Applications. While AI is progressing at a rapid pace, he reminds us that the pharma industry is highly regulated and that the FDA issued their guidance on the use of AI in January 2025. Hoey stresses the importance of transparency and compliance within existing regulations, especially regarding AI algorithms and bias. He says that in Good Practices (GxP)-accountable areas, AI is more of an evolution than a revolution, requiring education and strong understanding of its impact on processes.
Having added that note of caution, Hoey says that he is seeing certain use cases that can really make a difference, particularly where tasks are repetitive and common. In these applications, AI can help to release skilled professionals from monotonous and time consuming tasks to instead concentrate on strategic initiatives and solutions that will provide more value to our clients.
“What is exciting is the potential that AI has to augment and assist us operationally,” he says, “I would say the productivity and operational efficiency we gain as we develop with technology is exciting – for instance, the data accuracy that we can achieve with AI-powered automation such as intelligent document processing. With data analytics, we can gather a lot of information from various functional areas in our business in order to understand our operations like we’ve never really been able to before.”
However, Hoey adds that change management and the need for staffing expertise in AI is a significant challenge when applying some of these technologies. Implementing AI successfully requires some human adaptation and recognition that people need to adjust to integrating AI into their working practices. Offering workforce training and education about AI’s capabilities, concepts, and limitations will improve outcomes for everyone. Part of that training should include how to effectively manage intelligent systems to ensure responsible deployment, ethical decision-making and to mitigate potential risks. At the same time, businesses will need to hire AI and technology experts and be prepared for the next generation of workers who will expect technological integration.
However, when it comes to areas that are strictly regulated, Hoey says the key is to maintain human oversight and ensure a human element is designed into the decision-making process.
“The pharmaceutical industry must keep patient safety and drug quality top of mind, and we must continue to operate within that regulatory framework,” he explains. “That can be a challenge though. I think it can be mitigated to some extent; you can apply AI processes in GxP areas, but only by ensuring that there’s a ‘human in the loop’ who’s makes final critical decisions.”
How impactful is AI?
Somers and Hoey both acknowledge that as a contract packager, Sharp’s role is to be proactive, continuously improve services, and seek operational efficiencies. As well as the supply chain risk monitoring mentioned previously, Sharp is also developing plans to use AI as a predictive tool to assist with more detailed planning and scheduling, and using AI to enhance or replace some of its manual and repetitive processes to gain efficiencies where possible, including:
- batch record review
- materials incoming/receiving processes
- protocol and validation related documentation
- process monitoring and control for processing equipment
- examining suppliers’ risk models including cyber security, financial health and stability, and ESG performance
AI has the potential to improve the resiliency and efficiency of the entire procurement and order fulfillment process, says Somers, expediting medicine delivery through technological efficiencies and potentially reducing time-to-market, all while maintaining strict pharmaceutical standards.
“I see advancements that are possible here, in helping our clients deliver their drug product to the market faster,” says Somers. “AI is potentially going to address resource issues as well as enhance expertise, ultimately achieving shorter lead times to get medicines to the patients who need them and improve forecasting, planning and inventory management. There’s a lot of potential benefits.”
Hoey agrees, concluding: “It’s an exciting time – a shift into a new digital paradigm. We understand it’s a journey, but I’m genuinely excited to be part of how AI is evolving, particularly in the context of GXP accountability. Ultimately, we can deploy this technology to help improve patients’ lives, which is something we are all working toward achieving together.”
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[i] GlobalData: Big Data in Pharma, October 2024
[ii]
