In January, Duygu Dikicioglu, PhD, associate professor in digital bioprocessing and biochemical engineering at University College London, co-published a paper on how the Industrial Internet of Things (IIoT) is being implemented in bioprocessing. Here, she talks to GEN about regulatory barriers, the benefits, and how sometimes exciting new developments remain under wraps.
Would you briefly describe the IIoT?
Dikicioglu: One way to describe the IIoT is implementing an embedded data-collection, modeling, and control strategy, retrieving process information while the process is ongoing, and then using that information to predict the future of the process. You can then adjust your future actions, either by reinforcing existing practice or taking corrective measures to reverse an undesirable outcome.
GEN has written about digital twins and real-time sensors, which seem to fit your definition. To what extent is IIoT already being implemented within the bioprocess industry?
Dikicioglu: Companies are at the stage of implementing the minimum required components of IoT, but not necessarily linking them together. Most examples of such IIoT elements we came across for our paper were implemented in patches to support either cell line or process development, rather than manufacturing.
Naturally, the field may be more advanced than what our research has shown. Our methodology employed open-access information but, realistically, you might expect that some of this information and technology advances haven’t been shared publicly. What is available certainly gives confidence that the mindset is there; the sector is moving in this direction, and there are quite a few exciting developments.
What was your motivation in doing this research?
Dikicioglu: I’m involved in the Institution of Chemical Engineers’ activities, and was invited to investigate IIoT for the digitalization section in their journal, The Chemical Engineer. We soon realized that, although chemical and biochemical engineering seem complementary industries, healthcare bioprocessing works entirely differently, and this is due to the nature of its regulation.
What is this regulatory issue?
Dikicioglu: Transforming your workflow to incorporate IIoT is a massive financial and resource commitment, and if you’ve spent millions of dollars, you need to know your product and process are GMP-compliant.
If you adopt a data-driven approach to ensuring the quality of your product and process, and implement necessary justifications when applying for approval, you need to know if they would be accepted. That’s a huge concern, which has come up in discussions we’ve had [with companies and subject experts] and, in my view, the regulators need to provide both reassurance and incentives.
You obviously see the IIoT as the future. What are the benefits for the bioprocessing industry?
Dikicioglu: IIoT gives a much better understanding of bioprocesses, helping companies better model and control their manufacturing steps. This includes comprehensive data recording and superior process understanding to help ensure product and process quality.
If an operation produces a successful product worth millions of dollars, IIoT can help detect unexpected operational outcomes and consequently understand what’s going wrong in real time to, if possible, salvage that process.
Moreover, the wealth of data generated by IIoT can help with consistent record keeping and streamline regulatory submissions. When implemented across the workflow, IIoT ensures all data remain internally consistent, complete, and in communicable format, reducing the risk of misinterpretations, which potentially lead to human error.
