At the recent PharmaTech Integrates conference, industry experts explored the pressing challenges facing pharmaceutical manufacturing and the role of technology in driving transformative change. XpertRule’s Iain Crosley rounds up the major insights.
The pharmaceutical industry stands at a critical juncture. With digital technologies such as AI already providing value, the time for incremental change is over. The urgency to fast-track adoption is greater than ever, and now, the focus must shift to delivering real, measurable improvements in patient outcomes and manufacturing efficiency.
Dave Tudor, CPI Managing Director – Pharma, HealthTech & Quality, set the tone in his opening remarks at PharmaTech Integrates 2024, stressing that the industry’s future hinges on decisions made in the coming years. With radical change required and the window for action narrowing, Tudor urged companies to not only adapt but to “scale up and scale out” to keep pace with mounting global pressures.
As I explained in my previous article, The Right Dose of AI in Pharma, the race is on to deliver life-saving treatments at scale. With a growing world population and aging societies, the need for more affordable and accessible medicines has never been greater. At the same time, the pharmaceutical industry faces mounting scrutiny for a carbon footprint that exceeds that of the automotive sector. That might be surprising but pharma manufacturing is energy-intensive and relies on hazardous chemicals, overproduction to meet demand and single-use plastics.
Of course, it’s important to celebrate the industry’s successes, such as the rapid development of the COVID-19 vaccine, which showcased the UK’s strength in collaboration, cutting-edge research and rapid action during a crisis. However, the industry cannot rely on crisis-driven innovation alone. Indeed, many would argue the impacts of climate change and our aging population are no less of a crisis.
The lessons learned during the pandemic must be carried forward, especially the importance of people, partnerships and technology coming together. As GSK’s William Dawson put it; “We need joined-up thinking, joined-up actions, joined-up outcomes."
Three Ingredients to Accelerate Adoption
The consensus among speakers was clear: digital technologies, particularly AI, are no longer optional – they are essential, and the cost of inaction will only grow. AI holds tremendous potential to transform the industry, such as reducing the time to deliver pharma dossiers by an incredible 90%, but it’s not a cure-all for every ailment. The key to success lies in deploying it with purpose. Companies must shift from implementing technology for its own sake to focusing on where it can deliver tangible, measurable outcomes.
But for AI to truly make an impact, practical use cases must move beyond isolated experiments into full-scale real-world applications. Generative AI and large language models (LLMs), for example, offer exciting potential but need careful management to detect and remove biases or hallucinations and avoid biased or misleading results. One solution is to integrate citation mechanisms in Gen AI models, ensuring transparency by allowing users to trace information back to reliable sources.
Moreover, AI’s real power comes when it’s combined with other digital tools, rather than relying on a single solution. As Dave Tudor highlighted, the greatest impact comes from integrating technologies to maximize their collective impact, not exploring them in isolation.
The success of AI ultimately depends on people. A key takeaway was that a cultural shift is needed to ensure that stakeholders across the pharma industry not only adopt new technologies but actively engage with them.
People can be both the biggest barrier to and the greatest driver of change. The best tools in the world won’t deliver results if the workforce resists or misunderstands them. That’s why upskilling and comprehensive training are critical. AI systems must be approachable and workers should feel empowered to use them without fear of job losses. Several speakers noted the importance of keeping humans “in the loop” to make AI adoption more collaborative and less daunting.
As AI continues to evolve, human skill and experience become more, not less, important. It’s not just about automating tasks; it’s aligning human expertise with powerful technologies to drive better outcomes.
Partnerships were another key theme. It’s clear that no single organisation can solve the challenges facing pharma alone. Pharmaceutical companies, tech firms, research institutions and healthcare providers must work together to drive large-scale change.
Successful collaboration allows for shared knowledge and resources, yet requires careful management, particularly around intellectual property (IP) protection. While there are examples of collaborative national projects, speakers called for more case studies to be shared, helping to inspire broader adoption of AI and sustainability initiatives across the sector.
The Road Ahead
Digital technologies, including AI, have immense potential to improve patient outcomes, increase sustainability, reduce costs and deliver on the promise of personalized medicine. But big questions remain. Concerns raised by speakers and audience members included regulatory challenges and ethical implications. The use of AI in healthcare must be auditable, transparent and meet stringent safety standards to win widespread trust, with all parties committed to responsibility and fairness. The need for robust guardrails around AI models was also raised, with some questioning whether regulators are doing enough to keep pace with the rapid advancements in technology, particularly around data standards and security.
The day’s discussions underscored a crucial point: AI and other technologies must drive real-world outcomes, not just serve as flashy innovations. In most cases, companies will need to start small, proving the value of AI in targeted areas before scaling up, and collaborate. This is where organizations like the High Value Manufacturing Catapult network, particularly CPI and the Medicines Manufacturing Innovation Centre, play a pivotal role.
At the heart of all this innovation is the patient and faster, more precise diagnoses and treatments that are affordable and accessible. For me, the key takeaway was how much more can be achieved when companies work together.
As Dave Tudor remarked in his closing statement: “We are making progress but there is a real opportunity to pick up the pace. We can no longer say that the technology doesn’t exist - it does. The focus now must shift towards implementation.”
The healthcare challenges we face aren’t going away – they’re growing. But the tools to address them are within reach. Whether you’re a pharmaceutical supplier, integrator or manufacturer, now is the time to explore how AI can add value across the healthcare chain, from the lab to the pharmacy shelf. Let’s talk about how we can help you drive that transformation.
This article is part of our new series, Reality Check: What AI Really Means for Manufacturing, designed to inform, inspire and help you implement AI in your manufacturing operation.
Look out for our upcoming article where XpertRule’s Akeel Attar will explain why transparency and accountability are key to ensuring machine learning can be effectively integrated into real-world manufacturing environments.