Faced with the ongoing pandemic, biomanufacturers are working harder than ever on vaccine production; and, although there have always been issues to be solved by the intelligent deployment of technology, their level of importance has moved from a business need to a critical necessity.
In other industries, unplanned downtime is a major risk that can quickly lead to the lost of profits, data and product. If production stops in a biomanufacturing setting, the situation is even more precarious: loss of integrity during vaccine production, for instance, could necessitate the need to destroy the entire batch.
When it comes to key challenges in biotech, ensuring that all the equipment is always on … is paramount. Typically, batches are manufactured in runs of thousands of vials.
Taking each vial to a lab to test its quality would be an impossible task. This is when the regulations come in; The Medicines and Healthcare products Regulatory Agency (MHRA) requires that the quality of each product is built into the design of biotech manufacturing systems.
Each and every process in the manufacturing chain of a drug has to validated. Biomanufacturers must be able to show that they have the systems in place and the corresponding data to support the continuous monitoring of the product.
If they are unable to do so, under regulatory guidelines, that product can’t be released to the market. Depending on what the product is, that could mean the loss of millions of pounds and a devastating impact on the availability of medicines. It’s a case in point that highlights the need for smart manufacturing.
Richard Sharod
Edge computing is vital to the success of smart manufacturing facilities and it’s this innovative technology that’s pushing pharmaceutical manufacturers towards higher levels of implementation and use.
With the rapid deployment of the Internet of Things (IoT) across the manufacturing spectrum, sensors are being placed at almost every touch point of the production line. These sensors record an abundance of data; but, for the onsite operator to make use of this data, it has to be made available to them in real-time.
And this is only possible if the data is processed where it was collected — on the plant floor at machine level — at the edge. There is built-in latency associated with sending data to the cloud for analysis, which isn’t a problem when it isn’t related to a time-sensitive issue.
When that data pertains to machine health or the potential contamination of a batch, the onsite operator needs to be made aware immediately if/when a fault occurs. Being able to action data in real-time can be the difference between a whole batch being lost or the issue being solved quickly and production continuing.
Edge computing is commonplace in the healthcare industry; everything from smart watches to heart rate monitors all sit at the edge of the network and provide real-time data.
Implementing edge computing in the manufacture of pharmaceuticals offers the same benefits, including unrivalled insight into the current health of the machine, the ability to action data in real-time and the peace of mind that comes with “always on” availability.
Now more than ever, you could say that every industry and every human depends to a greater or lesser extent on the success of biomanufacturing. The deployment of edge computing in life sciences provides a simple, protected and autonomous way to ensure continuous production with no loss of data.