The CPHI Milan conference sessions, taking place October 6–8, 2026, represent a unique opportunity to gain insights from industry leaders shaping the future of the pharmaceutical industry and supply chain.
The Manufacturing 5.0 Track at CPHI Milan 2026 will explore how advances in technology, new approaches to manufacturing and changing partnership models are influencing how medicines are developed and produced. As sponsor of this year’s track, Thermo Fisher Scientific explores the practical challenges facing pharma and biotech companies and what it takes to translate innovation into successful execution. Here, Thermo Fisher’s Anil Kane, PhD, MBA, Global Head of Technical and Scientific Affairs, Pharma Services, shares his perspective.
1. “Manufacturing 5.0” captures a number of changes happening across pharmaceutical manufacturing. What does that evolution mean in practical terms for pharma and biotech companies trying to bring increasingly complex therapies to patients?
"We’re seeing several things happen at once. Therapies are becoming more complex, manufacturing technologies are advancing, and companies have access to more data and digital tools than ever before. At the same time, there’s tremendous pressure to move quickly without introducing additional risk.
The opportunity is in making all of those pieces work together. A new technology only creates value if it helps improve a decision, prevent a problem, or move a programme forward more reliably. For pharma and biotech companies, Manufacturing 5.0 is about bringing scientific expertise, technology, and execution together to make manufacturing more predictable and responsive."
2. Drug development and manufacturing increasingly depend on multiple interconnected activities, yet those activities are often managed across different teams, sites and partners. Where does that fragmentation create the greatest risk, and what can companies do to manage it?
"The risk often shows up at the handoffs. Each individual activity can be going well, but if information, decisions, or materials don’t move effectively from one team or partner to the next, that’s where you can lose time.
Those delays don’t necessarily stay contained. A decision made during development can affect tech transfer. A manufacturing delay can affect clinical supply. Something that looks like a relatively small issue in one part of the programme can have consequences further downstream.
That’s why coordination matters so much. The earlier teams understand those dependencies and make decisions with the next stage in mind, the better chance they have of protecting the overall programme rather than optimising one activity in isolation."
3. Tech transfer can be a pivotal point in a development program. What most often puts a successful transfer at risk, and what needs to happen earlier to prevent delays once a programme reaches that stage?
"One of the biggest misconceptions about tech transfer is that it begins when you’re ready to transfer the process. In reality, many of the things that determine whether a transfer goes smoothly happen much earlier.
How well do you understand the process? Are the analytical methods ready? Have you identified the critical parameters and potential scale-up challenges? And has the receiving team been involved early enough to understand not just what the process is, but why certain decisions were made?
Something that works well at development scale may behave differently when you move it into a larger manufacturing environment. Bringing the receiving site into the conversation earlier can help surface those considerations while there’s still time to address them, rather than discovering them when the manufacturing timeline is already in motion.
The more knowledge you can carry forward, the less you’re asking the receiving team to rediscover. That can make an enormous difference when you’re trying to move into manufacturing without losing momentum."
4. AI has quickly become a major industry focus. Where are you seeing it create meaningful value in pharmaceutical scale-up and manufacturing today, and where is there still a gap between its potential and practical application?
"There’s obviously a lot of excitement around AI, but we have to be disciplined about separating what’s possible from what’s useful.
The near-term opportunity is in places where we already have significant amounts of data and a clear problem to solve. One example is using data to identify patterns in process performance that can be difficult for an individual to spot across a large volume of information. That doesn’t make the decision for the scientist or engineer, but it can help them know where to look. There are similar opportunities to anticipate potential issues or help people get to the information they need more quickly.
Where we need to be careful is assuming that AI somehow replaces the underlying scientific and process knowledge. It doesn’t. The value comes from combining these tools with experienced people who understand the process and can interpret what the data are telling them. In a regulated manufacturing environment, that context matters."
5. Technical expertise and capacity are table stakes when selecting a CDMO. What else should pharma and biotech companies be looking for in a partner if their goal is to reduce execution risk and keep programmes moving?
"Capacity matters. Technical capability matters. But neither tells you how the relationship is actually going to work when the programme becomes difficult.
I would look closely at how a partner manages complexity. How do they communicate when something changes? How quickly can the right experts get involved? How are decisions made across teams and sites? And can they anticipate what a decision today could mean for the next stage of the programme?
You’re not just buying a manufacturing slot. You’re relying on that organisation to help you navigate problems that you may not be able to predict at the outset. That makes the way a partner executes and collaborates just as important as the capabilities listed on paper."
6. As attendees hear about AI, digitalisation, new modalities, and new manufacturing models throughout the Manufacturing 5.0 track, what do you hope they come away thinking differently about?
"I hope they come away thinking less about any one technology or trend and more about how all of these changes affect execution.
We can have better tools, more sophisticated processes, and more data, but ultimately we still have to turn a development programme into a medicine that can be manufactured reliably and reach patients.
For me, that’s the opportunity: How do we use innovation to make better decisions earlier, anticipate risk and make the path from development through manufacturing more predictable? If people leave with new ideas about how to do that, I think the conversation has been worthwhile."
