What does it take to build an innovation culture in one of the world’s most careful—and consequential—industries? Biotech is often seen as conservative by necessity, with every process and product touching real lives.

This episode dives straight into the balancing act of pushing boundaries with new technologies while rigorously protecting quality and patient safety—a challenge every scientist, engineer, and leader knows firsthand.

In this episode from the Smart Biotech Scientist Podcast, David Brühlmann meets Irina Ramos, a chemical engineer by training who’s navigated everything from bench research to global regulatory filings, who played a key role in the worldwide rollout of AstraZeneca’s COVID vaccine.

Key Topics Discussed

• Why conservatism persists in biotech and how it shapes the adoption of new technologies and automation.
• How Irina Ramos’s career path—from chemical engineering to large-scale biologics manufacturing—informs leadership and innovation in CMC.
• How CMC leaders shift from scientific contributors to cross-functional innovators through goal alignment, risk ownership, and communication frameworks.
• How innovation cultures can be built inside conservative biotech organizations through problem-driven approaches, strategic roadmaps, and leadership support.
• What mindset and interpersonal skills scientists need to drive meaningful innovation while maintaining trust, competence, and balanced optimism.
• How stakeholder coordination, communication structures, and project management practices influence the success of cross-functional biotech initiatives.
• When continuous manufacturing is advantageous in bioprocessing, and how misconceptions, facility constraints, and analytical technologies influence adoption.
• How the field of continuous biomanufacturing is evolving—including digitalization, predictive models, hybrid systems, and real-time release strategies—and how organizations choose between hybrid and end-to-end continuous approaches.

Episode Highlights

• Why conservatism is vital in biotech—and how to balance it with innovation [00:00]
• The vision for “lights out” manufacturing and if bioprocess facilities could run with minimal human intervention [02:50]
• Irina Ramos’s career story and the lessons her “happy accidents” teach junior scientists [03:53]
• Mindset shifts: Transitioning from scientist to innovation leader in CMC development [06:29]
• Building an innovation culture in a conservative, highly regulated industry [08:07]
• Essential mindsets for scientists to thrive and innovate in biotech environments [11:22]
• Coordination strategies for effective communication across stakeholders, departments, and geographies [13:52]
• The misconceptions of continuous manufacturing and what actually drives its adoption [17:09]
• What’s hot in continuous biomanufacturing: trends, global perspectives, and how real-time analytics can change process control [21:12]
• Guiding principles for choosing between hybrid or end-to-end continuous processes [23:46]
• Practical tips on implementing control strategies and real-time monitoring in manufacturing [25:01]

In Their Words

The conservative aspect of our industry is necessary. We shouldn't fight it; we should embrace it. We work with products that have a direct impact on people’s lives, so there’s no way around it. We shouldn’t just fight for a less conservative aspect of the discussions. We should, however, leverage new ways of working and new technologies — maybe automation and maybe digitalization — with the appropriate checks and balances, and following ICH Q guidance, but adapted to the new solutions that will solve these new problems.

Episode Transcript: From Batch to Continuous: Building Innovation Culture in Conservative Biotech Environments - Part 1

David Brühlmann [00:00:39]:
Have you ever wondered how innovation leaders balance risk-taking with regulatory compliance? Or how to navigate the transition from batch to continuous processing without disrupting your existing operations? Welcome to the Smart Biotech Scientist Podcast. Today we are diving deep with Irina Ramos, who is a downstream processing powerhouse and has led CMC programs from bench to regulatory filing. And yes, she helped transfer the AstraZeneca COVID-19 vaccine globally. Irina’s bringing the unfiltered truth about building an innovation culture in conservative environments. So grab your coffee — this episode is packed with plenty of insights.

Welcome, Irina. It’s great to have you on today.

Irina Ramos [00:02:40]:
Thank you, David. Happy to be here.

David Brühlmann [00:02:42]:
It’s a pleasure. Irina, share something that you believe about bioprocess development that most people disagree with.

Irina Ramos [00:02:50]:
I think it’s the vision for the future. Some of us might disagree on when we’ll be ready to accomplish that vision. Some people might disagree that, in the next 10 to 20 years, we will have lights-out manufacturing — which means we wouldn’t need people to walk in, gown up, and perform the tasks we do today. I do believe we can achieve that. I think we can envision a manufacturing facility that is smaller and doesn’t need people inside except to solve problems. And if everything runs at steady state, we don’t need the lights on.

David Brühlmann [00:03:31]:
I love this vision. It’s a great vision — I like it. Before we dive a bit further into today’s topic — we’re going to cover continuous processing, obviously, and a lot more — I’d love to go into your story. Can you please draw us into your journey and share what got you started in biotech, what were some interesting pit stops along the way, and what you’re doing today?

Irina Ramos [00:03:53]:
It’s a series of happy accidents. And I hope students and junior scientists are listening to this because sometimes, when they happen, we wonder if it’s a good thing or a bad thing — but it’s about how we embrace them.

My background is in Chemical Engineering. I’m originally from Portugal, and at the time, the biotech industry was not big there. There was no focus at the university to lead us into that industry. So the happy accident was an exchange student program that opened the door to the United States and exposed me to smaller-scale systems. I could look at cells, I could look at proteins, and I could interact with a microscope. I learned that I could apply chemical engineering principles to very small, microscopic things.

The interesting series of events is that when we enjoy working with the people we encounter in life, that becomes the driver for our choices. For me, it’s really about the people. I absolutely loved working with the professor I met in the U.S., Dr. Theresa Good, who invited me to apply for the PhD program — and 22 years later, I’m still here.

After the program, I got a job in industry at AstraZeneca — at the time, it was MedImmune — and we learned to work in a small-company environment with the resources of a large company. For over a decade, we grew with the AstraZeneca portfolio, and I learned what a chemical engineer could do from bench scale all the way to large scale. It was a great demonstration of how we can apply our background in the biotech industry.

David Brühlmann [00:05:42]:
Yeah, that’s great. I love the way you see it — it’s about people, and I totally agree. Obviously, we’re passionate about science, but ultimately, we work with people. That’s also part of my story — I love working with different, interesting people and learning from them.

So, Irina, you’ve obviously seen a lot of different companies and settings. You’ve led teams in early-stage development all the way through regulatory filings. I’d like to start by looking at that part of your work — what are the biggest mindset shifts you’ve seen successful CMC leaders make when they transition from scientist to innovation leader?

Irina Ramos [00:06:29]:
You are working with individuals who come from very different functions. Each function has its own role, responsibility, and of course, accountability. So in order to bring them all together, we all need to be aware of the goals for that project, for that program, and for the team.

There are two things. First, the goal setting has to be very clear. We all need to agree on the timeline, we all need to understand where the resources come from, and we need to give and take.

The second one is the risks — from the unknowns to the absolutely known and high-risk items. How do we all embrace the same risks? Traditionally, we call it a risk register. A risk register should not be divided into slices per function; it’s really to compile the risks so that the team understands we all embrace the same risks.

So in many ways, the secret — that is not so secret anymore — is: how do we build a team where we all understand, through good communication tools, what it will take to meet that timeline?

So often, you find that the stronger teams are the ones that share resources and knowledge — from leadership approval at the functional level to the overarching governance of the portfolio. So I think the key question is: how do you then build that trust, that we are all together for the same purpose?

David Brühlmann [00:07:52]:
We work in a conservative industry. Obviously, there is a lot of innovation going on, but still, biotech is quite conservative. So how do you build an innovation culture despite these constraints we have in our industry?

Irina Ramos [00:08:07]:
Everything starts with a problem — with a need. If that problem and need are a common denominator, then it’s much easier to convince others. You need a solution; you need to change; you need to seek that solution.

Often, you need to collaborate with vendors or other partners. If you don’t have that common understanding that the problem is real — and it’s no longer just a functional interest to improve — it’s harder to convince other stakeholders, because they don’t want to change. Things are working — why would we change?

It’s easier to innovate when you’re working on novel modalities, because the current platform doesn’t fit anymore. It’s also easier to innovate when you explain to leadership that you need to invest — and that such investment brings resources. That could be budget, people, or space. Maybe you even need a different facility to get that product out the door.

Because let’s be honest — in our industry, it’s the product and the discovery of that product that drive everything else. Manufacturing is a very important piece of the puzzle, but we need to make it work for that product to help patients.

So, new modalities, new constructs — I like to call them these “Frankenstein maps,” right? We no longer have the simple maps. The traditional 20-year-old platform doesn’t always work. So how do you translate that into innovation?

Innovation comes in different shapes and forms. Often, people like to think it’s a shiny piece of equipment that makes things work. Sometimes, innovation is in how we work — maybe we need to change processes to make things faster. We might need to automate documentation and template writing. We might need to innovate in the way we interact with regulatory agencies.

The vision has to be: what is the next platform? What does that look like? And does it apply across the portfolio, or do you have a dedicated platform per modality?

Once you have people on board with your problem, you can bring those stakeholders together to discuss a technology roadmap — and how that plays a role in your product launch. It’s no longer just early-stage work that matters; you have to think all the way to the filing — for a BLA, for instance.

It doesn’t mean you have to have all the answers at the beginning, though. People are often skeptical about what that strategy looks like — there’s so much we don’t know. And that’s okay. What’s not okay is to not think about or not address what we don’t know.

So we need to build that technology roadmap — identifying the milestones when we absolutely need to know the answer, and which functions need to be involved by that time.

At the end of the day, it’s really about human psychology. We want to be heard. We want our function to be represented when it’s supposed to be. So how do we build that alignment and reporting across those milestones for each function?

David Brühlmann [00:11:05]:
You’re making an important point — it’s about the way we think. And this leads me to the next question. What mindsets would you suggest the scientists listening should adopt to thrive in this environment and also to drive innovation?

Irina Ramos [00:11:22]:
We always want to work with competent people. We want to trust them because we believe they know what they’re talking about — from their specific function or area.

We also want to work with positive people — but people who live in reality. So, I’m talking about being good at what you do. And to get there, it’s not only through school — you have to be smart in the way you interact with people, the way you listen to them, and really do so with the intention of the common good — not a personal or individual agenda.

Just because I saw or heard something at a conference or read a really nice paper — how do I translate that idea into solving the problem my organization actually needs solved? Because if they don’t see that need, they won’t support you.

So we need competent people; you build trust, and then you have conversations that build strategy.

The conservative aspect of our industry is necessary. We shouldn’t fight it — we should embrace it. We work with products that have a direct impact on people’s lives, so there’s no way around it. We shouldn’t just fight for a less conservative aspect of the discussions. We should, however, leverage new ways of working and new technologies — maybe automation, maybe digitalization — with the appropriate checks and balances, and following ICH Q guidance, but adapted to the new solutions that will solve these new problems.

I want to emphasize that — and we’ll talk more about AI, I’m sure. We don’t have computers to replace us. We still need competent, valuable scientists and engineers to contextualize how we are going to apply those solutions.

David Brühlmann [00:13:05]:
Whether you’re leading innovation projects, working in CMC development, or preparing an IND or BLA filing, you have to interact with all kinds of stakeholders — especially in bigger companies.

One of our listeners mentioned that coordinating between various stakeholders across different departments and locations is their biggest challenge when implementing innovative solutions. But I think that applies to all kinds of settings.

I’d love to get your perspective, Irina. From your experience, what strategies have you found most effective for communication, collaboration, and ultimately achieving the results you’re aiming for?

Irina Ramos [00:13:52]:
I’ve had experiences like that too — absolutely. From time zones to geography to culture — even the way people think methodically about something, or how they go about giving updates and explaining what they’re doing.

I found different ways, depending on my colleagues. Sometimes, you might want to leverage a one-on-one. Maybe you have a one-on-one every other week with someone who has very limited English — think about that. In that more focused environment, you’re supporting that colleague.

And if you’re leading a team, you’re not alone anymore — that colleague is not alone anymore. You’re representing and filling the gaps as that colleague communicates to the rest of the team, if necessary.

You need strong project management skills in a team. That means when you present an agenda, sometimes it’s not enough — especially for teams from different cultures — to just have a bullet list of what we’re going to discuss. Maybe you need to be clear about expectations for those topics.

So I actually did that — I wrote not only what updates we needed from each function, but also the expectation: not only the timing, but the linkage of that topic to other functions. So now they come more prepared. The action items are very clear, and so are the timelines.

So: clear expectations, organized agendas, and meeting minutes that truly reflect what was discussed.

But we also need to be prepared for ad hoc discussions. In a recent example, I found that if we’re a bit more senior in the organization and have seen good ways of doing things, we are responsible for coaching. You might say, “Have you thought about this?” — and you need to build trust for your ideas to be accepted. Maybe you just ask them to trust you: “Let’s try it this way; let’s see if it works.”

It’s complex — and it applies to project teams, and to innovation as well. Sometimes innovation brings an extra layer of complexity: do they have the capability at that site? Do they have what it takes — from space, to bandwidth, to people, to know-how?

And we shouldn’t assume. Don’t assume anything. You should ask. Be curious about what those individuals or other teams do in their business-as-usual environment. So when you need to push them — to accelerate them, to think outside the box — you already understand what kind of tools you need to use to stretch a little bit more.

David Brühlmann [00:16:34]:
What I’m hearing comes down to clear communication, number two — trying to understand what their needs are, who they are — and then also having clear expectations, and making sure that things happen according to the agreed timeline.

Now, let’s shift our conversation to a topic that’s dear to your heart. Let’s talk about continuous manufacturing. For those who are still in the fed-batch world, let’s start out in a slightly controversial way: what is one misconception about continuous manufacturing that you hear most often — and how do you address it?

Irina Ramos [00:17:09]:
Too complex. Too expensive to implement. It’s going to take longer timelines to develop a continuous process — even before you scale it up. A lot of uncertainty, right? A lot of ambiguity.

It’s all valid. All of these concerns are valid — and they actually matter. And why do I call them misconceptions? Because it’s really company by company, facility by facility, and situation by situation.

Continuous manufacturing is not the solution for all products. Nor is there a single, one-size-fits-all solution for continuous processing. That’s why the community is growing — vendors are providing different solutions. And we don’t always call it “continuous.” Sometimes we call it intensified, or even automated manufacturing.

So how do we make sure that, for our portfolio and our existing facilities — both internal and external — we’re making the right choices? Because if you have to work with CMOs (Contract Manufacturing Organizations), you need to understand their ability to adapt to your products.

Then you need to make a decision: is it worth it? Can we have a forecast that we can actually trust? Often, these forecasts — for example, blockbuster forecasts — are not really met. They just give us an indication. But can we expand and apply that to the capacity we will need for that product?

So it all comes down to productivity for us in the bioprocess world. My background is downstream, but if my upstream colleagues don’t develop a highly productive upstream process in the bioreactor, downstream intensification doesn’t make sense.

You can think about traditional perfusion, steady-state perfusion, or dynamic perfusion. You can think about a couple of weeks’ duration or longer — duration doesn’t really matter. Productivity is the measure — how much mass per unit time per unit volume you’re able to produce. How much do you actually need?

Only after that does downstream make sense to intensify — to make it continuous. Even though some intensification tools in downstream could also be applied to fed-batch.

If we find a way to have a flexible facility — more like pieces of a puzzle — we can identify a stage-wise approach to implementation that makes sense for the product. For example, if you’ve aligned your upstream feeding strategy to achieve really high productivity — 5x, 10x improvement — then it makes sense to start thinking about downstream integration.

Where I’d like to highlight is the PAT part — Process Analytical Technology — all the analytical tools, sensors, and real-time or near real-time tools. If they’re being developed to facilitate or even enable continuous processing, why wouldn’t we use them in a fed-batch process?

So I actually think that, from an analytical perspective, we might have an even stronger push — from our customers — to get these technologies out the door. And I know the regulators want that, because at the end of the day, they want us to control our processes better.

So how can we entertain this vision — of what’s out there — and then make our own internal strategy that fits our portfolio needs for the next five to ten years?

The worst thing that can happen is if we set a strategy and keep it at steady state — “This works for now” — and no one is really thinking about the next three, five, or ten years in terms of portfolio evolution.

And then leadership comes with these very intriguing molecules — that may not be very productive, or that degrade very fast. And that’s where continuous can actually be your solution.

So I talked about productivity, and now I’m talking about product quality. Product quality could be another driver to implement continuous manufacturing — because then your intermediate is not sitting around for too long.

David Brühlmann [00:21:00]:
You’ve just come back from the Integrated Continuous Biomanufacturing (ICB) conference in Dubrovnik — I saw it on LinkedIn. What is the state of continuous manufacturing today like? What’s hot in this area?

Irina Ramos [00:21:12]:
The most interesting thing about the conference was that we focused on having more continents represented — leveraging the location in Europe. And we did that.

We also wanted to bring new people and institutions on board, so we offered pre-conference tutorials with three big names in this field who decided not to retire — and we’re very thankful for that. They’re still around, and they’re still incredibly valuable in providing context and mentorship.

So now, David, you can imagine — you have this wave of new people coming in, interested and curious. You have more organizations represented, presenting posters and oral talks. And at the end of the day, what you get is more diverse solutions to intensify and make the bioprocess continuous. That, in turn, enables many more “what if” conversations.

So, what’s hot right now? Well, we’re being bombarded — in a positive way — with new modalities and constructs that no longer fit the traditional platform. You need to find automated and smart ways to move the needle — to get closer to utilizing predictive models that reflect what’s happening in the process.

These models are predictive not only of real-time activities, but also of scalability. There are many technologies used in other industries that vendors are now bringing into bioprocessing — a field that’s admittedly late to the game in some respects — but we also bring unique challenges: closed systems, single-use components that need to last, and stringent GMP expectations.

A very important topic is how to leverage expectations around documentation, data gathering, and monitoring — and do more real or near real-time analysis. Some people are skeptical, others are encouraged by the idea of real-time release.

So how do we bring all these ideas together? Eventually, they converge into what we’re all striving for: faster processing, higher productivity, smaller facilities, single-use or hybrid setups (stainless steel combined with single-use). Ultimately, your PAT framework supports better process control and drives digitalization across the entire manufacturing process.

David Brühlmann [00:23:28]:
How do you decide whether to go for a hybrid approach or a fully end-to-end continuous process? Because as you said, there are so many options now — and it can be quite overwhelming. Are there some simple guiding principles to help scientists choose the best approach?

Irina Ramos [00:23:46]:
I think there are. A stage-wise approach is always better — even if your final goal is fully end-to-end continuous.

Unless you’re building from scratch — a greenfield or even a brownfield facility — it’s important to leverage what you already have. But you also need a portfolio that can feed into that long-term plan, including scalability considerations.

Maybe you start with clinical manufacturing, and then, if those products are successful, they become the ones feeding your commercial facility. So you need that vision — that roadmap.

A hybrid approach, especially while vendors are still maturing their solutions, is extremely important. And we shouldn’t only rely on the big vendors — we should also engage with smaller companies that bring innovative solutions and prevent the industry from becoming monopolized. Competition is healthy in this field.

In the end, it’s really about what fits your organization — if you have a clear vision of the kind of portfolio you’re going to focusing on.

David Brühlmann [00:24:49]:
To what extent do scientists need to prioritize the control strategy or real-time monitoring? That seems crucial for continuous manufacturing. Are there some easy solutions to start with?

Irina Ramos [00:25:01]:
Think about what you already do in fed-batch — how do you control the process? Look for parallels.

Maybe you don’t need everything under the sun — and that helps demystify the perceived complexity of these implementations. Just because something would be nice to have doesn’t mean it’s a must-have to control the process effectively today.

So, leave the nice-to-haves for later. Focus first on the must-haves, which are linked to regulatory expectations.

Look at what you already do in fed-batch — identify what you absolutely need to continue doing for continuous — and then maybe add sensors that provide feedback loop control.

For example, you might monitor concentrations or pH. If you’re titrating inline, you’ll want that sensor connected to a simple feedback loop. In fed-batch, you might not need that as much.

So, you’re not reinventing the wheel — these tools already exist. You’re just transferring that knowledge to equipment that’s now closed, enabling closed-system operations. There are many examples like that — where you can leverage existing sensors and technologies to provide the necessary control and insight.

David Brühlmann [00:26:11]:
That’s it for part one. We’ve explored leadership mindset shifts, innovation, culture building, and the advantages of continuous manufacturing.

If these insights sparked something for you, please leave a review on Apple Podcasts or your favorite platform — it helps scientists like you discover these conversations.

Stay tuned for part two, where Irina reveals what the COVID vaccine taught us about what’s truly essential in process development — plus her take on AI in biomanufacturing.

See you next time.

All right, smart scientists — that’s all for today on the Smart Biotech Scientist Podcast.

Thank you for tuning in and joining us on your journey to bioprocess mastery. If you enjoyed this episode, please leave a review on Apple Podcasts or your favorite podcast platform. By doing so, you’ll help empower more scientists like you.

For additional bioprocessing tips, visit us at www.bruehlmann-consulting.com. Stay tuned for more inspiring biotech insights in our next episode. Until then — let’s continue to smarten up biotech!

Disclaimer: This transcript was generated with the assistance of artificial intelligence. While efforts have been made to ensure accuracy, it may contain errors, omissions, or misinterpretations. The text has been lightly edited and optimized for readability and flow. Please do not rely on it as a verbatim record.

Next Step

Book a free consultation to help you get started on any questions you may have about bioprocess development: https://bruehlmann-consulting.com/call

About Irina Ramos 

Irina Ramos has developed a career in downstream process development of Biologics, from the bench to team's leadership. Her work was applied directly in portfolio projects, leading CMC projects to regulatory filing milestones, and in innovating and implementing platform technologies, in particular related to continuous manufacturing.

In 15+ years of experience in downstream process development, Irina has worked in Early and Late stage process development, process scalability, CMC leadership, technology transfer and process validation. She led the technology transfer of the AstraZeneca COVID-19 vaccine process to an international partner.

Connect with Irina Ramos on LinkedIn.

He is also a biotech technology innovation coach, technology transfer leader, and host of the Smart Biotech Scientist podcast—the go-to podcast for biotech scientists who want to master biopharma CMC development and biomanufacturing.  

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