Biomanufacturing is moving toward smarter, faster, and more automated ways to produce medicines, but there’s a big problem: the technology that measures and controls these processes hasn’t improved fast enough. Right now, many factories still rely on old methods like lab tests that take hours or days to give results. This makes it hard to fully automate production or use digital tools like ‘digital twins’—virtual copies of production lines that help predict and control quality. For example, if a factory’s digital twin only gets updates every two hours, it can’t react quickly enough to changes in the production process. Similarly, if a factory claims to be automated but still relies on manual lab samples, it isn’t truly autonomous. The industry agrees these old methods aren’t the future, but not enough has been done to upgrade the tools that gather real-time data. This gap isn’t due to lack of ambition—most experts want these improvements—but rather a lack of investment in the right places. Over the past decade, companies have focused more on software, data systems, and modeling tools, while the actual sensors and measurement devices that feed them with data have been overlooked. This means many factories are trying to control processes with outdated data, like driving a car while only seeing the road through a rearview mirror. One tool helping close this gap is a technology called *process Raman spectroscopy*. Unlike traditional lab tests, Raman spectroscopy can measure multiple important factors in a production line continuously, without stopping the process or taking samples. It works in real time, matching the speed of actual production rather than the slower pace of lab work. This allows factories to track and adjust processes as they happen, improving quality and efficiency. However, Raman spectroscopy isn’t a magic fix. It requires careful setup, including custom models that account for variations in production (like changes in cells or equipment differences) and integration with existing control systems, which weren’t originally designed for such fast, frequent data. There’s also the challenge of convincing operators, engineers, and regulators to trust decisions made from real-time data instead of traditional lab tests. To discuss these challenges, the *European Pharmaceutical Review* is hosting a webinar titled *’Optimising efficiency and yield through bioprocessing automation’*. This session will explore how Raman spectroscopy can help factories move toward fully automated, closed-loop control systems, the practical steps for implementing it, and how it can improve production yields. The real question isn’t whether the industry wants to modernize—it’s whether we’re building the right tools to make those plans possible. Without better measurement technology, even the most advanced ideas for Pharma 4.0—smart, automated medicine production—won’t be able to live up to their potential.