The COVID-19 pandemic showed the world the importance of quickly developing a vaccine. Fast vaccine development, though, depends on various advanced technologies. For example, Jennifer Reid, PhD, a senior scientist in vaccine development at Sanofi, and her colleagues, including one from Mettler Toledo, wrote: “Accelerated vaccine bioprocess development requires the integration of intelligent digital technologies and networks to better understand, control, and predict fermentation processes in real-time.”
In particular, Reid and her colleagues focused on automating the control of metabolites in fermenters. To accomplish this, Reid’s team combined a mid-infrared probe, process analytical technologies (PATs), and process information management systems (PIMS). To collect data on metabolites, the scientists reported: “Mid-infrared spectroscopy with an attenuated total reflectance probe in-line, and simple linear regression using the Beer-Lambert Law, were developed to quantitate key metabolites (glucose and glutamate) from spectral data that measured complex media during fermentation.”
Optimizing nutrient levels
Connecting the spectroscopic data to a PIMS allowed the scientists to optimize the levels of nutrients in a fermenter. As the scientists elaborated, the probe-PIMS combination allowed “continuous control of feed pumps with proportional-integral-derivative controllers that maintained nutrient levels throughout fed-batch stirred-tank fermenter processes.” By continuously collecting data on the metabolites, the scientists developed feedback loops to control the feed pumps to the fermenter.
The added control of nutrient levels produced big gains. “This improved process control of nutrient levels by 20-fold and the drug substance yield by an order of magnitude,” Reid’s team noted. “Furthermore, the method is adaptable to other systems and enables soft sensing, such as the consumption rate of metabolites.”
As shown in this work, quickly developing a manufacturing process for a new vaccine requires the use of various intelligent digital technologies. As Reid and her colleagues concluded: “This study facilitated the transition from off-line to in-line monitoring and control with the networking of devices to a PIMS that could enable end-to-end automation of metabolite control.”
