In an era where industries are increasingly driven by data and automation, the bioprocessing sector is embracing digital transformation to streamline workflows and improve productivity. However, blending the complex and highly regulated world of bioprocess with digitalization poses unique challenges. In this podcast, we talk to Dr. Simon Wieninger, Head of Portfolio and Applications at Eppendorf SE about how the journey toward digital integration requires well-defined goals, user-centered design, cross-industry learning, and, crucially, trust. Setting Clear Goals: Purpose-Driven Digitalization “Digitalization shouldn’t happen for digitalization’s sake,” Dr. Wieninger advises. While the temptation to adopt cutting-edge technology is high, each digital tool or system must serve a specific purpose. For bioprocessing organizations, establishing these objectives upfront is critical to ensure that digital investments yield meaningful results. Whether the aim is to boost productivity in production facilities, refine R&D processes, or improve operational efficiency in support functions like HR, having clearly defined goals anchors digital efforts in purpose. This intentional approach is especially significant for production and R&D sectors within bioprocessing. Here, digitalization can streamline processes such as real-time data monitoring, automated adjustments to culture environments, and improved reporting and compliance tracking. By aligning digital goals with broader business objectives, organizations can make more effective use of resources and ensure that digitalization contributes positively to organizational growth. Bridging Skill Gaps and Building Trust: Making Digital Tools Accessible A successful digital transformation relies on the people who will use these tools day-to-day. However, not everyone in bioprocessing has a background in software or programming. Simon points out that for digital tools to be effective, they must be intuitive and accessible to all team members, from scientists in the lab to technicians on the production floor. "We need to design solutions that everyone can use," he says, noting the importance of user-friendly interfaces that require minimal technical knowledge to operate. Part of building an accessible digital framework is understanding the varying comfort levels with technology within the workforce. Some employees may be tech-savvy, while others are less familiar with digital tools. Recognizing and accommodating these differences is crucial to creating a smooth transition. Moreover, as Simon explains, trust is fundamental—not only trust in digital tools but also in the partnerships with vendors and technology providers who support this transformation. Organizations should leverage the expertise of these partners, building collaborative relationships to create solutions that meet specific needs and ultimately make bioprocess workflows more efficient. Learning from Other Industries: Adopting Best Practices in Automation and Standards The bioprocess industry has much to learn from sectors like automotive, finance, and telecommunications, which have long relied on automation and standardized processes to boost efficiency. In automotive manufacturing, for instance, high levels of automation allow for the production of thousands of vehicles with minimal human intervention. Bioprocessing, by contrast, has historically been more manual and labor-intensive, particularly in R&D and small-batch production. According to Simon, one of the greatest opportunities for bioprocessing is to adopt industry standards that facilitate automation and improve interoperability across devices. One such example is the OPC (Open Platform Communications) standard, widely used in other sectors for seamless communication between devices. Applying such standards to bioprocessing could simplify data integration across lab instruments and production equipment, allowing researchers to capture and analyze critica...
