Industry 4.0 is a global effort to bring the latest digital technologies to manufacturing facilities across industries. It is intended to reduce costs, improve quality, and a host of other “good” things. It grew out of European efforts in the early 2010s to update their factories, and is often referred to as “bioprocessing 4.0” within the biomanufacturing world. However, biotech manufacturers have been fairly slow to implement many of its technologies, and its benefits remain a little unclear.
One area bioprocessing 4.0 is showing promise within biologics production is process analytics. Collecting data during cycles, as opposed to just after batch completion, or only after steps within batch production, could return faster quality indicators. However, unlike many industrial products, biomanufacturing needs new measurement tools, not just sensors and computers like other industries, due to the very sensitive nature of the product.
Taking advantage of photonic products used to monitor and manage fiber optic networks in telecommunications networks, Raman spectroscopy is one technology that can measure product features using lasers and infrared wavelengths. CHO cells emit biophotons during bioprocessing that can be measured by Raman spectrometers without interfering with production. While these devices add to the capex needed to buildout a facility, they can reduce opex through labor savings and more precise quality measurements during both upstream and downstream processing.
Beyond Raman spectroscopy, many other IoT (Internet of Things) sensors are built for higher volume manufacturing environments with less sensitivity. Chemical manufacturers and oil refineries use these devices to a large extent, but these same IoT sensors can’t be placed in a bioreactor without impacting the cell culture. Outside of basic environmental monitoring outside the bioreactor, customizing industrial sensors for biomanufacturing would be very expensive for the device suppliers, and leave them with limited volumes over which to cover their fixed development costs. As a result, the devices are not used as widely in biomanufacturing.
Sensors and spectrometers are needed on the hardware side, on the software side many consultants are promoting “AI” and analytic tools to help automate biomanufacturing. While this data can be useful in places, it is more widely used, and easier to adopt, in less regulated industries. Biomanufacturing process analytics can take advantage of additional data points, but development of Process Analytics Technology must be coordinated with the FDA. This is unlike algorithms that can find usage patterns among logs of website visitors, a common application for AI.
While bioprocessing/industry 4.0 could deliver some benefits for biomanufacturing, particularly on the hardware side in difficult-to-measure mammalian cell cultures, it seems like it’s still a long way from being widely accepted in this heavily regulated sector of the economy.