Christopher Cole

Stuart Tindal, Sartorius, and David Chau, Thermo Fisher

connected with Stuart Tindal, portfolio manager, Intensified Downstream Systems, Sartorius; and David Chau, global technical product specialist, Thermo Fisher—both Bio-Process Systems Alliance committee leaders—discuss automation, single-use technology challenges, and smarter process control in bioprocessing.

Watch the 2-part video interview with Tindal and Chau:
Part 1: 

How Predictive Control Is Reshaping Continuous Bioprocessing

Stuart Tindal and David Chau on Sensors, Standards, and Shared Progress

PT: How Should Companies Think About Integrating Automation into Continuous Bioprocessing?

 Automation isn't optional anymore, it's an integral part of any continuous or advanced bioprocessing operation. The industry has moved decisively away from purely manual operations. As processes have become more data-driven and connectivity has increased, the need for robust control and automation has become paramount. It's no longer a nice-to-have; it's a must-have for maintaining consistency and productivity.

 The foundation must be process understanding. Before you can automate anything, you need to know what you're trying to make continuous. You must consider what the inputs and outputs are, what parameters matter, how you'll measure them through sensors or equipment. People entering continuous bioprocessing right now can feel overwhelmed, whether they're building a process from scratch or retrofitting an existing one. Going back to the fundamentals of your process is often the most valuable first step.

How Do Single-Use Technologies Fit in with the Demands of Continuous Manufacturing?

 It's a real tension. Single-use technology has earned its place in the industry with faster turnaround times, flexibility, speed at the R&D and pilot scale. But those same benefits can become concerns when you're talking about commercial-scale continuous manufacturing, where processes run for weeks or even months. Single-use was designed to be limited. As an industry, vendors and end users must come together to honestly assess the limitations and innovate around them.

 It comes down to the materials of construction. When something is designed for a single day of use and you're asking it to perform for weeks, critical failure points emerge. Are the sensors drifting over time? Are the actuators, the pumps and valves moving plastic components, going to withstand prolonged friction and wear? The work being done now is about understanding how far these materials can be pushed and what alternatives or design changes can support longer continuous runs.

What Does the Future of Process Control Look Like in Continuous Bioprocessing?

 We're moving beyond conventional PID controllers toward predictive and model-based control. In a continuous process, your operating window becomes more of a tunnel, you need to steer the process along that tunnel in real time, being adaptive and anticipatory. That requires a very fast control and response loop. For more complex or labile molecules with tighter critical quality attributes, advanced predictive control isn't a luxury, it's what enables you to maintain the process trajectory from start to finish.

 Continuous manufacturing generates enormous amounts of data, and the question becomes what we do with it. Model-based approaches make a lot of sense in this context; with enough data, you can build predictive models that guide processes rather than simply hold set points. The shift is from reactive control to genuinely steering and predicting where your process is headed. That's where the industry is going, and it's an exciting direction.

Articles

Automation is now foundational to continuous and advanced bioprocessing, driven by increased connectivity and data-centric operations requiring robust control to maintain consistency and productivity. Effective implementation starts with deep process understanding—defining critical inputs, outputs, and measurable parameters—especially when retrofitting legacy operations. Single-use systems offer flexibility and rapid changeover, yet commercial continuous runs expose durability limits in materials, sensors, pumps, and valves. Process control is shifting from PID to predictive, model-based strategies that use high-frequency feedback and large datasets to steer processes within tight operating windows.

Stuart Tindal, Sartorius, and David Chau, Thermo Fisher, discuss automation, single-use technology limits, and predictive control shaping continuous bioprocessing's future.

Q&A: How Continuous Bioprocessing Is Evolving With Smarter Automation

sat down with Bryan Poltilove, strategic advisor and independent board director focused on bioprocessing and advanced therapy manufacturing, to discuss how just-in-time, point-of-care manufacturing is revolutionizing biopharma without compromising quality.

Watch the 2-part video interview with Poltilove:
Part 1: 

Bryan Poltilove on Evolving Bioprocessing Manufacturing Paradigms

Point-of-Use Media Manufacturing Could Cut Bioprocessing's Carbon Footprint by Two Thirds

What's Changing in Bioprocessing and Advanced Therapy Manufacturing and What Is Staying the Same?

The fundamentals aren't going anywhere, validation and GMP manufacturing. Nobody's willing to take risks there, nor should they be. The industry standard is well established and well understood.

What is changing is how and where manufacturing happens. We're seeing a significant shift toward point-of-care and place-of-care models, more distributed approaches to manufacturing, and supply chains that are becoming increasingly flexible in how reagents and other products are delivered to the industry. Cost has always mattered, but now environmental sustainability and supply chain resilience are becoming equally important drivers of that change.

It's a genuine paradigm change, a change in mentality and approach, not just a tweak to existing processes. The best analogy I can offer is the auto industry in the 1980s moving from large, inventory-heavy operations to just-in-time manufacturing. Biopharma is undergoing something very similar right now.

The key challenge is achieving that flexibility without compromising on the things that cannot be compromised. Reproducibility, availability, quality standards, those are non-negotiable. The goal is to find technologies and supply chain approaches that reduce inventory, make logistics more seamless, and give manufacturers more operational flexibility, all while keeping the product and the regulatory standards fully protected.

Where Are You Seeing this Play Out Most Concretely?

Cell therapy is probably the clearest example. We're seeing modular clean rooms, new cell processing technologies, and unit operations that can realistically be executed in a hospital setting. It's a remarkable development when you think about where cell therapy manufacturing stood even a decade ago.

I'm currently working with Nucleus Biologics, which has a particularly innovative approach to media manufacturing. The model is almost like a Nespresso or Keurig concept for cell culture media. Rather than producing a large, centralized batch and distributing it broadly, you're enabling on-demand, point-of-use manufacturing of the media itself. Their Krakatoa technology is built around that idea, storing powders on-site and only requiring water on-demand, rather than shipping and storing large volumes of liquid media.

What's the Practical Significance of that Powder-Based, On-Demand Approach?

The potential is substantial. Shipping requirements drop considerably because you're moving powder rather than liquid, and storage needs on-site shrink accordingly. Beyond the logistics, you gain the ability to manufacture exactly when and what you need, no excess, no waste.

What makes it compelling is that it combines the best of both existing formats: the ease of use and flexibility of liquid media with the logistical and cost advantages of powder. Bringing those two things together in a single workflow is genuinely innovative.

How Significant Is the Environmental Sustainability of this Shift?

It's increasingly central to how the industry evaluates these decisions. Best-in-class sustainability thinking now looks at total environmental impact from sourcing all the way through disposal, not just what comes out of a single step in the process.

Based on figures I've seen, moving to a distributed, point-of-use model for cell culture products can reduce end-to-end carbon footprint by roughly two-thirds compared to traditional centralized manufacturing. There's enormous promise here, or the industry and for the world more broadly.

It's just getting off the ground. A prototype system has been deployed in academic and industrial labs across multiple continents, used hundreds if not thousands of times, and has demonstrated strong reproducibility, consistency, and reliability at that scale. The commercial launch is happening now. Scaling that performance up to full bioprocessing scale is the next step, and I have every reason to believe the results will follow the same trajectory.

Validation and GMP rigor remain non-negotiable in bioprocessing, but manufacturing paradigms are shifting toward distributed, point-of-care/place-of-care models that prioritize flexibility, resilience, and sustainability alongside cost. This represents a just-in-time mindset change analogous to automotive manufacturing’s 1980s evolution, requiring inventory reduction without sacrificing reproducibility or quality. Cell therapy is the clearest near-term proving ground, enabled by modular clean rooms and hospital-executable unit operations. Powder-based, on-demand media manufacturing could materially reduce logistics burden, waste, and end-to-end carbon footprint.

Bryan Poltilove discusses how distributed, point-of-care manufacturing is reshaping biopharma supply chains and cutting carbon footprints.

Q&A: Bryan Poltilove on the Future of Bioprocessing

, co-hosts Chris Cole and Richard Jaenisch explore the emerging role of digital twins in pharmaceutical container systems with guests Mihaela Simianu, president of Concordia MCS and scientific advisor to SmartSkin Technologies, and Austin Caudle, vice president at SmartSkin Technologies.

To view the full fascinating, practical, engaging conversation, click here!

The discussion centers on how “smart” pharmaceutical container replicas—equipped with sensors and data-capture capabilities—can help manufacturers better understand how vials, syringes, cartridges, and other container closure systems interact with manufacturing equipment throughout the product lifecycle. Simianu explains that while today’s technology is not yet a fully virtualized digital twin, these physical smart replicas provide critical real-time data about seal forces, equipment interactions, and operational stresses that can impact product quality and patient safety.

The guests emphasize that container intelligence can play a significant role across development, clinical manufacturing, commercial scale-up, and tech transfer between manufacturing sites and CDMOs. By using sensor-enabled replicas to monitor equipment-container interactions, companies can reduce glass breakage, minimize downtime, optimize line setup, and better maintain container closure integrity throughout production and distribution.

A key theme throughout the conversation is risk reduction. Simianu and Caudle argue that integrating these tools early in development creates continuity as products move between facilities and scales, helping manufacturers preserve process understanding and reduce variability tied to changing equipment environments.

The episode also highlights broader industry trends toward data-driven manufacturing, predictive analytics, and digital transformation, positioning smart container technologies as foundational building blocks for the future of pharmaceutical digital twins and advanced manufacturing intelligence.

Videos

Mihaela Simianu and Austin Caudle join the show to discuss how digital container twins can improve pharma manufacturing, validation, and risk reduction.

Manufacturing Intelligence: Digital Twins Meet Pharma Containers

Manufacturing Intelligence Episode 3 - Digital Twins of Containers

George Kwiecinski, Global Key Solutions Corp

connected with George Kwiecinski, CEO and co-founder of Global Key Solutions Corp, to discuss FDA GMP inspection trends, supplier oversight gaps, and the rising regulatory scrutiny of AI in pharma compliance.

Watch the full video interview with George Kwiecinski:


George Kwiecinski on Why Now Is the Time to Reassess Your GMP Audit Strategy

PT: How Should Quality and Compliance Teams Prioritize Foreign Suppliers for Audit or Reinspection when Inspection Coverage Is Limited?

Kwiecinski: It comes down to resources and organizational capacity. Whether you're inspecting an internal facility or auditing a supplier, most organizations are working within real constraints. The question becomes: are you procuring the right tools and technology to make sound assessments? Are you selecting suppliers through a documented, demonstrable process? These aren't just best practices, they're expectations. With the QMSR changes affecting both medical devices and the FDA's ability to scrutinize internal audit documentation, this has become a hot-button issue. Organizations need to take a second look at how those processes are being handled and reprioritize accordingly. The good news is that tech stacks have improved significantly for most workflows, so there's really no excuse not to reassess.

What's Your Outlook on Compliance Risk in Global Supply Chains?

Honestly, I don't think the fundamental risk picture changes dramatically. The top citation areas will continue to revolve around the quality unit, drug efficacy and safety standards, and how those standards are being enforced across vendors. Those core pillars aren't going anywhere. What will shift is the context around them, especially as new technologies and practices become more common in the industry.

How can AI-powered Regulatory Intelligence Improve Oversight without Providing False Positives or Incomplete Data?

Yes, this is something we've been tracking closely. One trend that really made waves recently was that an AI citation appearing in an FDA warning letter. Essentially, a company had used AI to respond to the FDA and generate some of their documentation, and that usage was called out directly. Now, I think this kind of citation will become more frequent over time. It may not always be flagged explicitly, but AI use in regulatory processes is clearly on the FDA's radar.

We put together a white paper recently looking at how the FDA has used ‘AI’ as a keyword across its correspondence and documentation over the last 3-4 years. What we found was telling: there are now 5 distinct regulatory correspondences specifically referencing AI, and over 20 FDA guidance and documents that mention it, with the frequency increasing steadily over time. That trajectory tells us that AI is becoming a meaningful part of the agency's regulatory purview, and companies need to start thinking about what that means for them.

What Changes Do You Recommend to Strengthen Foreign Supplier Governance when API and Finished-dose Sourcing Is Heavily Concentrated Overseas?

The first step is just awareness, understanding that these changes are happening and that it's accelerating. From there, it's about looking at your own tech stack and honestly evaluating how your organization is managing AI-related risk. If your organization is using AI tools in any part of its regulatory or quality workflow, you need to be thoughtful about how those decisions are documented and defended.

As for whether companies should invest in new AI tools, I think that's a legitimate conversation to have, but the justification has to be grounded in business reality. If a tool can demonstrably save cost or drive profit, and you can implement it in a safe, controlled way, then pursuing it makes sense. What's going to matter most though, is the risk-based approach: how are you accounting for AI-assisted or AI-driven decisions within your processes? That's exactly the kind of thing that's subject to FDA scrutiny right now.

Global supplier oversight remains constrained by finite audit resources, elevating the importance of documented, defensible risk prioritization and fit-for-purpose technology. Persistent GMP citation drivers—quality unit effectiveness and enforcement of efficacy/safety standards across vendors—are expected to continue, but will be reframed by expanding use of AI in quality and regulatory workflows. FDA attention to AI is increasing, including explicit mention in warning-letter context and growing references across agency correspondences and guidances. Organizations should reassess audit strategies, strengthen governance of overseas sourcing, and formalize controls for AI-assisted decisions.

George Kwiecinski, Global Key Solutions Corp, breaks down GMP inspection risks, global supply chain compliance, and AI's growing role in FDA regulatory scrutiny.

Q&A: George Kwiecinski on How AI Is Reshaping FDA Regulatory Compliance

connected with Todd Vaughn, fellow, Aseptic & Sterile Products, and Christa Myers, senior fellow, Aseptic and Sterile Products, both at CRB Group, to discuss the growing role of robotics and automation in sterile pharmaceutical manufacturing and what it means for the industry's future.

Watch the 2-part video interview with Vaughn and Meyers:
Part 1: 

Robotics in the Aseptic Core: Rising Urgency, Rising Expectations

Todd Vaughn and Christa Myers on What Robotics Mean for Pharma Manufacturing

PT: Why Is Robotics in the Aseptic Core Such a Hot Topic?

 Robotics in aseptic manufacturing isn't new; equipment using robotics has existed for the last 10 to 15 years in this part of our industry. What's changed is the regulatory posture. Regulators are dramatically more interested in it now than they have been in the past, and they're pushing the industry to move further away from personnel manipulations associated with the process: How do we minimize human interaction all the way back from traditional fill lines, to now having greater separation between operators and the final patient?

 And it's a fantastic opportunity. One area I'm particularly excited about is environmental monitoring—the handling of plates and monitors inside the aseptic environment. That should have been the first thing we automated. We could have done it 20 years ago. Every time an operator sticks a hand in a glove to change a plate, you have to stop the fill line, which means stopping production entirely. Robotic replacement is going to drive meaningful efficiency back into the line.

What Trade-offs Does the Industry Need to Prepare for?

 The upfront work becomes significantly more challenging. When you remove personnel from the process, you have to identify every single thing that could possibly go wrong and figure out how to replicate what an engineer or operator would do across an entire batch operation. You're essentially encoding human judgment into automated systems, and that's not a small task.

 We've always been able to plan for interventions. Now we have to plan for unplanned interventions. It means thinking much deeper about your process and doing that work much earlier in the design phase. On top of that, the price tags on these fill lines are going up, and so are the lead times. Robustness has to be built in from the very beginning.

How Does this Shift Affect the Workforce?

 The operator knowledge base is likely to change significantly. In some cases, operators may actually need a greater understanding of operations than before. And the shift isn't limited to the aseptic core. We're going to need more people in component prep, parts prep, and sterile operations to facilitate cleaning and sterilization of rapid transfer ports and other components feeding into automated fill lines. There's a real workforce shift coming, and companies need to get ahead of it.

 Regulatory expectations are evolving too. The days of a site being grandfathered in are over. Continuous improvement is what's expected now. Operators and administration staff need to be tracking trends, and when regulators show up, you need to know your data and know where your highest risks are and how you're mitigating them.

Where Does the Industry Stand on the Adoption Curve?

 We're right on the edge between novel use and expected use. The first fully automated lines are coming off manufacturing floors now and will be installed at operating companies soon. That's going to drive more regulatory commentary, and as those next-generation lines follow, probably a year behind, regulatory expectations will shift again. Lines that are 10 or 15 years old could become suspect, much like what happened during the transition from restricted access barrier systems to isolators.

 One concern I have is for smaller companies. Larger organizations have the capital to push these designs forward, but smaller manufacturers are going to face real challenges keeping up. Our industry needs to figure out how to bring those companies along by finding solutions that are well-funded and accessible. Those companies are just as valuable to patients, and in many cases they're the seed that larger companies eventually acquire. We can't leave them behind.

Regulatory scrutiny is accelerating adoption of robotics in aseptic manufacturing, shifting expectations toward minimizing human interventions and increasing separation between operators and product. Automation offers major efficiency gains, particularly for environmental monitoring plate changes that currently force line stoppages. Trade-offs include higher capital costs, longer lead times, and substantially more front-end engineering to codify human judgment and manage unplanned interventions. Workforce needs will pivot toward higher technical competency and expanded sterile support roles. The sector is nearing a tipping point where automation becomes standard, challenging legacy lines and smaller manufacturers.

Todd Vaughn and Christa Myers of CRB discuss how robotics are reshaping aseptic pharmaceutical manufacturing, improving efficiency, repeatability, and compliance while demanding new operator skills and capital investment.