Leading Strategic Transformation in Manufacturing, Quality and Supply Chain Operations with Veronique Kodjo, Ph.D., Ceva Santé Animale [Speaker Spotlight]

In this Speaker Spotlight, Veronique Kodjo explores how Ceva Santé Animale spearheads strategic transformation in manufacturing, quality, and supply chain operations by tackling industry shifts, enhancing governance and collaboration, anticipating future needs, and ensuring readiness for upcoming major products to sustain business continuity and meet customer demands.

This article provides insight into Veronique Kodjo's upcoming panel discussion, "Leading Strategic Transformation in Manufacturing, Quality and Supply Chain Operations," which will be featured at the European Biomanufacturing Summit. Additionally, this article will explore Veronique's intriguing journey into biomanufacturing and her role as EVP of Global Manufacturing, Supply Chain, and Quality at Ceva Santé Animale.

Introduce yourself and describe your role/responsibilities as the EVP of Global Manufacturing, Supply Chain, and Quality at Ceva Santé Animale.

As the EVP of Global Manufacturing, Supply Chain, and Quality at Ceva Santé Animale, I oversee the company’s operations across approximately 15 platforms in key regions, including Europe, the USA, Canada, Latin America, and China. At Ceva, we've seen substantial growth in the biotech sector, with 50% of our turnover now coming from BIO, particularly in vaccines, compared to traditional pharmaceuticals. This shift is closely related to our focus on animal health, which emphasizes prevention.

My role is crucial in steering global functions like Quality and EHS, ensuring that our manufacturing processes are efficient, compliant, and aligned with our ambitious growth targets. We’re now a top-five global player in animal health, with double-digit growth since our spin-off from Sanofi over 24 years ago. It’s been a brilliant journey, and Ceva is now ranked number five worldwide.

I’m also part of the Executive Committee at Ceva. In my previous role at Boehringer Ingelheim, I held similar responsibilities. I often say that as a plant manager, you deal with a crisis every two hours; in upper-level management, it's a crisis every day. At our level, we manage a crisis every week. This is our life—we're here to solve problems and fix issues.

Could you tell us more about your personal career journey in the biomanufacturing space?

Well, I can tell you it wasn’t my plan.

My background is in veterinary medicine, so my career began as a veterinarian, but I barely really practiced with pets or large animals. This actually connects a lot to biotech. The veterinary field emphasizes prevention, and the "One Health" concept is pivotal, which means prevention through vaccination is a key focus. In fact, animals use many more vaccines than we currently use in humans.

Initially, my work was more focused on research and development in bio, and later on fundraising. Then, I transitioned to marketing and sales in the human pharma sector—nothing to do with biology at all. I was working in traditional oncology, which, at the time, wasn’t as correlated with biotech as it is today.

However, my core fascination has always been with biology, probably because of my background. I started my studies in biology and life sciences, which have advanced dramatically in the last 30-50 years—it's amazing. This passion eventually led me back to animals when I had the opportunity to take on a leadership role in quality control, testing vaccines produced by the company. This experience brought me back into biology and the industry.

Over the years, I ascended through various manufacturing and leadership roles, focusing more on biotechnology. About ten years ago, I became the head of operations at Merial, the animal health division of Sanofi, before transitioning to Boehringer Ingelheim due to the swap. Then, I finally joined Ceva Animal Health five years ago.

When I joined, Ceva was not yet 50% biotech, but now it is, and we’re growing even further. Recently, Ceva acquired a biopharma company in the US called Scout Bio, based in Philadelphia, which pioneers gene therapy solutions for pets. This is significant because these treatments, once very expensive and exclusive to human medicine, are now becoming accessible in animal health. Pets, like humans, are living longer, and the same trends in human health are now visible in animal health—more treatments, more preventive care, and more diseases that weren’t seen before because animals didn’t live long enough to develop them.

With Scout Bio, Ceva is expanding its capabilities in this rapidly growing field. Scout Bio develops therapeutic proteins and AAV (Adeno-Associated Virus) gene therapies to treat major chronic health conditions in pets, such as kidney disease in cats, anaemia, and atopic dermatitis. They’ve made significant strides in integrating gene therapy techniques, initially used in human medicine, to create innovative treatments for pets. It’s really amazing, and we’re at a turning point now.

This also stems from collaborations with universities that work on human pharma, and we’re just now entering that space with the same technology, even in vaccine manufacturing. Whatever you see in human pharma—same technologies, same GMPs, everything—it’s the same in animal health. There’s actually no difference.

This is why I’m very happy to have joined Ceva five years ago. I believe Ceva is a very entrepreneurial company, and with the acquisition of Scout Bio, we’re going to make a significant impact. There’s huge potential in this billion-dollar market, and as a pet owner myself (I have two cats), I’m very happy they can live long lives and benefit from these advancements when they become available.

Can you provide examples of how data-driven decision-making has improved outcomes in your transformation projects?

I think it's crucial, particularly in the vaccine and biomanufacturing space. Why? Because biology is inherently variable. When you produce a vaccine, for instance, you're dealing with logarithms—it's not about getting one or two points more or less; it's about achieving significant differences, sometimes in the hundreds of thousands, depending on the output. This is why data-driven decision-making is instrumental in industry practices.

One example comes from an early career project when I was training to become a Six Sigma Black Belt, which I eventually achieved. I led an initiative that significantly reduced the cost of goods for a vaccine by optimizing certain parameters. By meticulously analysing production data, we identified inefficiencies and implemented strategic changes that reduced waste and improved equipment performance, all without compromising quality. Data-driven decisions are also about enhancing quality. When people face an issue, they often jump to conclusions. For example, if there's a variation in vaccine production, one might think, "What's happening? Is this a normal variation in my process, which is inherently variable, or is there an actual issue?" You need data and statistical analysis to determine this.

That's why most companies are now gathering data into Data Lakes and other repositories. With this data, you can make informed decisions about your processes. Even in process development, artificial intelligence, and machine learning algorithms can now help optimize and develop new products. I find what we can do with AI incredibly exciting—sometimes, I’m at a loss for words. Of course, AI has its limitations, and you need to be careful when using tools like ChatGPT, which has its pros and cons. However, when you train a machine to understand and execute tasks, it becomes much faster and more efficient, although human oversight is still essential.

We're really entering a new era, especially in the biotech area, where data-driven decision-making is key. While intuition can sometimes be helpful, particularly in diagnostics (as veterinarians often have to make quick decisions without verbal feedback from animals), data provides the full picture.

I remember the visibility of that Black Belt project to the executive committee. I spent a lot of time being trained in the US, and it was a great experience. We were isolated, running Black Belt projects based entirely on data, which was a significant mindset shift for the company. Without proper data-driven analysis, you might jump to a solution, but the problem will likely resurface. You can’t afford that—it would turn a weekly crisis into a daily, or even hourly, crisis for the plant manager.

I’m known for being a fast decision-maker. I don’t need every piece of data to make a decision, but I do need enough—just enough, but not too much—to make an informed choice. Yes, decisions can sometimes be wrong, but fortunately, that doesn’t happen too often.

How do you balance the need for innovation with the requirement for compliance and risk management in biomanufacturing?

That's a difficult question because, in the pharmaceutical industry, it's heavily about compliance and risk management—or rather, avoiding risk altogether. In biomanufacturing, though, I see it as twofold: it's about challenging the status quo and sometimes leveraging fresh perspectives. By integrating professionals from outside the pharma industry, such as those from the food industry—which is also highly regulated—we can learn a lot.

This can foster a culture of questioning and continuous improvement. Often, when someone new to operational excellence joins the team, they might ask, "Can we do it differently? Can we change this?" The typical response is, "No, quality won't allow it," or "We can't because of regulations, GMP, or other risks." But in some cases, that's not true. There is room for improvement, even within strict compliance frameworks. You can still be fully compliant and find ways to do things slightly differently.

This approach encourages innovative thinking while maintaining rigorous risk management practices. Risk management is essential, but it's not about eliminating all risks. It's crucial to understand and proactively navigate the regulatory landscape, ensuring that new developments in fields like artificial intelligence are both impactful and compliant. This often requires lobbying and dialogue with regulatory authorities.

In the animal health industry, the regulatory environment may differ slightly from that of human pharma, but the rules remain the same—we must be compliant. However, if we have ideas for improvement, we can and should discuss them with the authorities. Innovation shouldn't be stifled by the assumption that regulations are inflexible. Continuous manufacturing, for example, may challenge the traditional batch production model, but with open dialogue, we can bring about change.

It's about having fresh eyes and asking, "Why don't we improve this?" People often believe they can't because "quality says no," but that's not always the case. Innovation often leads to better quality and safety, not just change for the sake of change.

Things need to evolve. Some old molecules from the past, for instance, could never be marketed today due to heightened risk concerns. Take the early smallpox vaccines—yes, there were risks, and sadly some people died, but many more were saved. It's always a balance. There's no such thing as zero risk, but we must manage and mitigate it effectively. Today, we tend to assume everything can be 100% secure, but that's not realistic.

"It's crucial to understand and proactively navigate the regulatory landscape, ensuring that new developments in fields like artificial intelligence are both impactful and compliant."

Can you share a specific example of how agile practices have allowed for iterative improvements during a transformation project?

I think not everyone understands what agility truly means. Some people associate it with physical fitness, thinking it’s about being flexible or mobile. But I remember one key aspect of agility: it's about securing value at every stage. I recall a project involving a complete reengineering of operational organization. We were totally transforming everything, and I’m passionate about organizational transformation and governance.

We had two options: prepare everything for a big bang change at the end or adopt agile practices to secure value at every stage of the project. We chose the latter. This meant identifying short-term wins through continuous feedback loops with the product team and future users—the people who would navigate the new organization and make it successful. By addressing pain points iteratively, we refined processes in a way that truly embodied agility: testing, learning from failures, and implementing timely improvements. This approach significantly enhanced team morale and product outcomes. Agility isn’t about chaos; it’s about rigor and discipline.

At Ceva, we’ve established a network of agile facilitators. These facilitators are trained in agile methodologies and play a crucial role in helping teams collaborate more effectively. It’s not their full-time job; they dedicate about 10% of their time to this role, working across different areas like external manufacturing, research and development, and commercial sectors. This cross-functional involvement adds tremendous value.

Iterative improvements are key because if you wait too long, you risk failure. Traditionally, in large ERP programs, you’d wait until the end to launch, and if it failed, you’d lose years and millions of dollars. Agility ensures that at every step, you’re generating something useful for the company. In the past, during organizational transformations, we didn’t wait for the full change; we addressed pain points as they arose, which added immediate value.

Agility is not about random actions. Training in scrum mastering and agile project management is essential if you want to move quickly in a project. Agile methodologies are valuable in many dimensions, and I’m a strong believer in their power to enhance collaboration and deliver short-term value, not just wait for a big bang at the end.

What targeted training programs have you implemented to upskill your workforce in evolving technologies?

That's an interesting question. I see it in two areas. First, during the COVID-19 pandemic, many countries, including the U.S. and some European regions, experienced the "Great Resignation." In some of our plants, particularly in Eastern Europe, turnover was high. Employees were leaving to work in other industries, like fast food. We had to address this issue, so we introduced a platform—Hapster, a spinoff of Safran—that converts the tacit knowledge of our experts into explicit, accessible content for employees, thereby enhancing collective expertise.

Although it may seem outdated, this method has roots in practices used during World War II, particularly in the U.S., where women were brought into factories to maintain production. The key is how you utilize the knowledge of your experts. Even when Standard Operating Procedures (SOPs) are documented, new employees may not fully understand them. This platform allows us to capture the best practices from our experts. Sometimes, two experts might have slightly different approaches, even if they agree on the general process. The goal of this training methodology is to capture the most relevant information and make it completely explicit.

This platform is digital, which is crucial for the younger generation. It’s available on apps, iPads, and tablets and includes videos that show exactly what needs to be done, focusing on best practices rather than just the overall operation.

For more technical areas, like automation or biotech, we hired external experts and leveraged our internal experts to conduct hands-on training sessions. For example, when automating a production line or workshop, it's essential to involve operators and line managers from the beginning so they understand the process, stay motivated, and feel invested in the new technology.

We also recently hired manufacturing data scientists to ensure our training is based on relevant expertise. When it comes to artificial intelligence, we’re using tools like Microsoft Copilot 365 to train our employees on AI and how to apply it using specific use cases.

So, we're focusing on both future and current technologies. It’s crucial to secure the existing knowledge in technologies like running bioreactors or specific purification steps because losing key experts can put you in a very bad situation.

What future trends do you foresee in process efficiency optimization, and how is your organization preparing for them?

We’ve already touched on the importance of data analytics and artificial intelligence. I believe that using AI and machine learning for process optimization is really expanding. Normally, you'll be able to predict and optimize your production processes and quality control more effectively. We’re also investing in AI capabilities and partnering with technology firms to integrate analytics into our operations. As I mentioned earlier, we’re starting to upskill employees, but it's still in the preliminary stages.

Currently, we're more focused on raising awareness among employees about what machine learning is. If you ask someone over 25 about machine learning—how a machine can learn—they often don't understand it. The younger generation is more familiar with it because they use it frequently, but they don’t always grasp the underlying principles—they just use it like it’s an extension of themselves. So, we’re working on integrating these capabilities and partnering with firms to advance in this area.

Most companies, including us, are working on using AI in areas like CAPA (Corrective and Preventive Actions) in quality assurance. This trend is gaining traction across various fields, including research and development, where it’s already showing tremendous results. Another trend is continuous manufacturing, which is becoming more prevalent, especially in biopharma. We’re adapting regulatory strategies to shift from traditional batch norms to continuous processes.

Sustainability is another critical trend. You can’t ignore the need to reduce your carbon footprint and other environmental impacts. By adopting greener manufacturing processes and technologies, we aim to minimize waste, water consumption, and energy use. Our goal isn’t just to publish claims about becoming carbon neutral by 20xx for the sake of boosting our stock price. Instead, we’re genuinely committed to sustainability. We aim to equip our facilities to produce all the energy we consume.

For example, we’ve built a new platform in the southwest of France that's already operating, with solar panels and geothermal energy sources. We’re also building new headquarters that will also be carbon neutral. For us, sustainability is about making targeted investments to truly decrease our environmental footprint, not just buying green energy certificates while continuing to pollute.

When we talk about artificial intelligence and digital transformation, another emerging area is the use of digital twins. These allow us—and other companies—to replicate physical processes or systems digitally, enabling us to simulate and optimize processes before implementing them on the production floor. We’re still in the early stages of this, but I recently hired someone with experience in digital twins, so I’m hopeful we’ll be able to replicate this success. Digital twins are well-established in other industries, but they’re just beginning to gain traction in biotech, where they offer great potential for simulation and process optimization.

Another trend is workforce evolution. Fewer people are interested in traditional roles, so we need to rethink what the future landscape will look like. For example, "black factories"—factories that are fully automated and run without lights because they don’t require human operators—are becoming a reality. I’m not entirely sure how I feel about this because I’m a people-oriented person who enjoys interacting with others, but whether we like it or not, this trend is here to stay. Automated factories also help reduce energy consumption, so there are clear benefits.

Lastly, I’m pleased to see more diversity in biomanufacturing. While I don’t want to focus too much only on gender balance, I’ve noticed more women taking on higher responsibility roles in this field, which is a positive development in what has traditionally been a male-dominated industry. It’s encouraging to see biomanufacturing becoming more inclusive and open to diverse perspectives.

We are grateful to Veronique Kodjo for her profound insights shared in this blog post. Her expert perspectives will greatly enhance our discussions at the European Biomanufacturing Summit. We look forward to her session, "Leading Strategic Transformation in Manufacturing, Quality, and Supply Chain," which will take place on September 10-11, 2024, in Berlin, Germany. Thank you, Veronique, for your collaboration and valuable input.