The role of automation in pharma manufacturing

Jan. 9, 2023
To thrive in Pharma 4.0, companies will not just need to add automation, but also integrate digitization by looking at data, connectivity and AI

In today’s world, automation is all around us. The pharmaceutical industry is no exception, with automation now playing an increasingly pivotal role in the supply chain, from device development to fill-and-finish processes. 

Automation has been steadily developing, with a clear acceleration in recent years. At the peak of the pandemic, labor shortages were a significant factor in causing the widespread disruption felt throughout pharma supply chains. Exposure to these challenges led to many companies intensifying their focus on the adoption of technology. 

According to research from the Association for Packaging and Processing Technologies, 75% of pharma companies said they intend to increase their level of automation in the year ahead. Further analysis from consulting firm McKinsey & Company points to the scale of automation adoption, with up to 50% of current work activities in pharmaceutical and medical manufacturing to be automated.

But to thrive in Pharma 4.0, companies will not just need to add automation, but also integrate digitization looking at data, connectivity or artificial intelligence (AI).

Key considerations

When implementing any form of automation, improving operational efficiency is constantly top of mind. Reducing production risk is also a major consideration, given that an estimated 50% of process deviations in production are the direct result of human error. Transferring these activities to automatic handling under closely controlled parameters results in clear improvements in reliability and consistency. As a result, organizations benefit from improved quality assurance, greater operational agility, and the reduction of costly and time-consuming production stoppages.

Equipped with more efficient manufacturing capabilities, pharma companies are better positioned to respond to wider market trends such as the growing popularity of injectables and the emphasis on personalized medicines. These trends are leading to the proliferation of new devices and smaller batches while maintaining high-volume capability for blockbuster drugs.  

Modern manufacturing facilities must accommodate these shifts and consider minimal downtime. Additionally, machines must be able to accommodate a wide variety of formats as well as make rapid, seamless changeovers, underlining the need for flexibility and scalability. 

With automation and modularity at the core of a manufacturer’s strategy, they can be highly flexible and can enable production to scale while maintaining the same technology from clinical trials to high volumes. Additionally, manufacturers produce machines that enable pharma companies to process different device formats on the same line, thus optimizing costs for customers. 

Another example of how manufacturers can help customers mitigate risks and meet high quality requirements is by integrating robotics focused on visual inspection. Introducing robotic processes ensures superior fully automated inspection performance for high-value small batch treatments without human intervention.  

Humans are still important

All these examples show how manufacturers can effectively employ automation. Introducing these new processes will help drive change within pharmaceutical production and packaging processes, supporting pharma partners in the move towards ‘Industry 4.0’ where it is expected that human involvement will gradually play a more limited role. 

It is important to remember, however, that such capabilities do not exist in isolation. To find success in Pharma 4.0, companies need to do more than just automate — they also must integrate digitization looking at data, connectivity or AI.

For example, in the design and development phase of a device assembly line, Digital Twin technology can be used to create an identical virtual replica of the proposed assembly processes to predict risks, minimize errors, reduce delivery time and optimize ROI.  By integrating Deep Learning models into automatic inspection machines, manufacturers can offer increased defect detection while minimizing false reject rates. These efforts, coupled with a secure, cloud-based artificial intelligence platform, bring the potential for optimized costs and improved quality. 

Automation and digitization are clearly at the heart of this vision, but there is no doubt that the application of human expertise remains a critical factor in realizing the true potential technology can deliver.  

About the Author

Raffaele Pace | Engineering VP of Operations, Stevanato Group