How AIoT is Transforming Pharmaceutical Manufacturing

The Artificial Intelligence of Things (AIoT) is the combination of artificial intelligence (AI) technologies with the Internet of Things (IoT) infrastructure to achieve more efficient IoT operations, improve human-machine interactions and enhance data management and analytics.

It is a market sector that is growing fast. According to the recent report  The "Artificial Intelligence of Things: AIoT Market by Technology and Solutions 2020 - 2025" from ResearchAndMarkets.com, the global AIoT market will reach $65.9 billion by 2025, growing at a compound annual growth rate (CAGR) of 39.1%.

Gauging the Challenge

The potential for this new technological paradigm to reshape the pharmaceuticals sector is clear, as is the urgency that this should happen. Given the current market volatility in pharmaceuticals, manufacturers must be more agile than ever before to survive and thrive. The level of disruption has been difficult to navigate with future demand for product lines often unclear and difficult to predict. Data management strategy is often fragmented with data held in silos that are difficult to access. That’s often exacerbated by large volumes of mergers and acquisitions across the industry with manufacturers purchasing new sites and plants that can be cut off from the rest of the business.

The use of isolated pools of Excel spreadsheets and manual documents is rife, leading to issues with governance and workflows. Many processes are still carried out entirely on premise and it can be difficult for senior managers to get a real-time view of what the data is telling them. In a world where regulation holds sway and there is much process complexity, many executives are unwilling to change and adopt new processes. They are wedded to their existing systems and processes and sometimes ‘allergic’ to the very concept of the cloud.

It has become increasingly urgent that pharmaceuticals manufacturers are able to overcome these challenges though. The pandemic and the success of getting new vaccines approved and rolled out within a year of its emergence has reset the parameters and that has set a precedent that puts additional pressures on the industry. Leveraging AIoT gives them the opportunity to address these issues and start delivering enhanced operational efficiencies.

Today, AIoT is being used increasingly widely across the pharmaceuticals industry. Manufacturers are deploying elements of the AIoT stack on-premise to do batch analytics and for process historian applications. We are also seeing the technologies more widely used for cloud-based visualisations and dashboarding; digital workflows and governance; and data connectors in order to aggregate multiple data sources into a data lake, a foundation for applying Machine Learning at scale on large data sets. AIoT also plays a big role in enabling machine learning and experimentation to help drive R&D.

Scoping the benefits

While the technology is still emerging today, it has huge potential to drive ongoing benefits. By bringing data together, we can break silos across sites and between those working on information technology (IT) and operational technology (OT) who typically still work separately on different data sets. More broadly, AIoT offers pharmaceutical manufacturers the great benefit of making their data management and data processing efforts much more affordable.

By moving key capabilities to the cloud, AIoT becomes much more affordable not just for the largest plants but for the smallest sites too. It also allows these businesses to start to run analytics in real time rather than having to rely on historical data. When errors or inefficiencies are discovered, therefore, changes can rapidly be made, helping to ensure the safety, quality, and profitability of a plant. By improving real time visibility over the data, the latest AIoT tools also help give senior decision-makers governance over the process and insight into what is going on out in the field at the same time.

Scaling the barriers

Yet despite these multiple benefits, challenges do still remain to the broader roll-out and success of AIoT. There are still barriers to overcome.

The age-old resistance to change in what has traditionally been a conservative sector is part of this of course, even if the growing recognition of the need for change is counterbalancing this. There has to be a sense of velocity balance in play, nevertheless. Change is happening but it can’t and shouldn’t be expected to happen overnight. There are other challenges also. Pharmaceuticals remains a highly regulated sector and that needs to be borne in mind.

The need for data privacy security and protection of IP are also all key considerations that require careful management as AIoT is rolled out across the marketplace. At the same time, manufacturers also need to find ways to work more in collaboration with each other as we saw in the case of Covid-19. Within an ecosystem of ‘coopetition’, mechanisms will be required to decide what kinds of data can be brokered and share securely and to find ways of controlling and auditing what is being shared.   

The time is now

Ultimately, though, while the above issues need to be carefully considered and thought through, we are seeing a growing consensus behind the importance of moving to AIoT and a growing sense that pharmaceuticals manufacturers understand the need to make use of this exciting new technology model as they battle to beat off intense competition and find ways to accelerate time to market at the same time.

Looking even further into the future, the potential of AIoT becomes still clearer. The enhancements in data processing and analytics that AIoT supports brings with it an opportunity for higher-quality research and development. The technology could also be leveraged to further fuel the roll-out of self-optimising plants with the attendant opportunity of diverting resource and investment to higher value tasks like research and developing new products. There are also opportunities here to drive enhanced sustainability. The AIoT environment allows manufacturers to monitor batches in real time, thereby benefiting the environment by reducing waste.  

It is becoming increasingly clear that despite the challenges and barriers, AIoT will have a key role in shaping the future of the pharmaceuticals market and giving manufacturers across the sector the opportunity to build a production ready AI environment, where they can ensure the quality of the latest drugs, streamline the production process, and speed up time to market. Given the wide range of gains on offer, it is clear that the time is right for manufacturers to start looking at AIoT technologies and begin to consider how they can deploy such solutions both for their own benefit and that of the industry as a whole.