Biopharma: The trials of scaling-up

The biopharmaceutical sector is now the fastest-growing part of the industry, estimated to reach $389 million by 2024, up from $237m in 2018. The ability of biologic drugs to treat previously untreatable diseases has fueled this growth, offering hope for a new era of truly effective precision, personalized medicine.

However, there remain significant roadblocks ahead. Remarkable technological advances have transformed biopharma manufacturing processes in recent years – yet the industry is still struggling to scale up production to the industrial levels that skyrocketing demand requires. To achieve the full potential of biopharmaceuticals, we still require further changes to manufacturing facilities, as well as investments in novel technologies to scale up manufacturing beyond small-batch production. At Pall, we have been working to solve customers’ critical challenges by addressing technology gaps that hinder their progress towards increasing manufacturing capacity.

Automation and process analytical technology (PAT) have now become key for drug production to ensure product quality and safety, as well as to overcome rising cost pressures, but it has taken a long time. Other manufacturing sectors like the automotive industry have led the way for decades and are continually investing in technologies to modernize and advance manufacturing processes. The biopharma industry, meanwhile, has been slower to embrace the transition and exploit the resulting efficiencies.

If we are to scale up to truly industrialized production, we need to learn from our counterparts in other sectors. What can the biopharma industry adopt from other more advanced industries? And what will we need to do differently to meet our own specific opportunities and challenges?

Lessons from the automotive industry
The automotive industry is widely recognized as one of the most technologically advanced manufacturing sectors. The Ford Motor Company is often credited as a pioneer in the second industrial revolution for its introduction of the car production assembly line in 1913. General Motors was instrumental in the development of the programmable logic controller (PLC) in 1968, the foundation of the third industrial revolution and automation as we know it today. After more than a hundred years of innovation, automation, robots and Industry 4.0 have been wholeheartedly embraced and are transforming manufacturing and machinery across the sector.

The automotive industry is driving quality and efficiency using technologies ranging from 3D printers to virtual reality and artificial intelligence (AI) – all of which are often central to car companies’ core manufacturing strategies. They too are realizing the full potential of Industry 4.0, by programming machines to communicate with one another, as well as human operators.

The pharmaceutical industry is beginning to move away from batch processing and adopt a continuous approach

This cyber-physical convergence is a powerful change in mindset which unlocks the power of both the data and the machines.
Although not as quick to adopt the latest technologies, the pharmaceutical industry is beginning to move away from batch processing and adopt a continuous approach. Automation is behind the change, which enables products to be developed without interruption and has been used by the pharmaceutical industry for some time, for example in oral solid dosage manufacturing. Continuous manufacturing can reduce processing times, batch variability and costs while improving overall quality. We are starting to see more applications in biopharmaceuticals, particularly in gene therapy manufacture. However, the shift to continuous manufacturing, particularly for biopharma, isn’t without challenges.

From batch to continuous manufacturing
There are clear benefits to a continuous approach, yet there remain numerous obstacles that need to be overcome. For biopharmaceuticals, batch manufacturing involves developing therapies in a stepwise approach. At the end of each step, material is collected into a single batch and can be held for testing before moving on the next stage of the process. This means the process is well-established and regulated at each stage.

At the start of the journey towards continuous bioprocessing, the industry was concerned about regulatory hurdles. Since the process runs continuously, testing batches was perceived as a challenge that could be an issue among regulators, including the Food and Drug Administration (FDA). In the end, it is important to remember that the process isn’t inherently different to batch processing; it requires the same steps and employs equal safeguards, quality checks and standards. However, in continuous these must be directly connected to the process, allowing process and quality data to be collected in real-time, eliminating the need for offline testing. While the transition to a continuous manufacturing process can be a significant endeavour – requiring investment in new equipment, training to manage it, and time to develop a new process – the benefits are substantial. This is especially true since the logical goal of the journey to continuous bioprocessing is real-time release, whereby a product is sampled, tested and ready for distribution once manufacturing is complete. Real-time release offers economic benefits with greater product and process understanding. However, data collection, management and analysis on this scale remains a challenge for many manufacturers.

The challenges of data collection
In this sector, humans are often still responsible for timely tasks including reviewing data, as well as writing and submitting reports. As analytical tools become more sophisticated and the amount of data produced at each stage of an experiment or bioprocess increases, data capture, analysis and storage solutions will be able to translate this data into useful information without human input. This shift will alter the makeup of the manufacturing team since operators will need to be able to manage and oversee continuous processes and the automated systems that run them. This will result in more roles that incorporate data analytics, process analytical technologies (PAT) and automation, on top of traditional bioengineering skills.

Worryingly, there is already a skills shortage developing due to the rapid pace of change that the industry is undergoing. The problem is not with the quality of students graduating from life science programs or the standard of their education, but the lack of practical industry experience, cross-functional exposure and understanding they have. Furthermore, a recent study from the University of Leicester and the University of Warwick, funded by the Nuffield Foundation, suggests that STEM graduates often choose not to, or are unable to, find work in industries like the life sciences.

To help equip graduates with the required skills to find work in the industry, Pall Corporation partnered with the Biofactory Competence Center (BCC) – established to create a bridge between academia and industry and train graduates and unemployed pharmaceutical workers on biopharma manufacturing skills - to offer one solution. Through the partnership, Pall provided the BCC facility in Switzerland with equipment for both single-use and continuous manufacturing processes to help course participants build real-world skills in biopharma. To-date, the BCC has trained nearly 1,500 people and graduates have an 80% chance of securing a full-time job on completion.

The potential for biopharma
Challenges aside, realizing potential gains from automation, analytics and Industry 4.0 would be of great benefit to biopharma and patients alike. While there are many automated technologies and analytics systems available, there are few specifically designed for the biopharma industry. Because of this, it isn’t viable to fully acquire the technology solutions developed and employed in other sectors; the biopharma industry must further develop the available automation, analytics and Industry 4.0 solutions.
This could mean taking a different approach to equipment design and deployment, looking at how we can simplify and improve existing technologies and determine the areas that are truly worth investment. On the data side, there is a need for specialist software, which builds on the significant advances seen in other industries but is tailored to the specific regulatory and performance requirements of biopharmaceutical manufacturing. The convergence of this next generation of analytical equipment and software is crucial for continuous bioprocessing and single-use approaches, which are finally becoming more commonplace.

We are in a critical moment in time. Biopharmaceuticals are now offering multiple therapies and treatment options for previously untreatable conditions, bringing hope to patients worldwide. But to overcome the challenges ahead, a concerted effort will be required from all parts of the industry. If we fail to mobilize and act, we will miss the opportunity to better serve patients. However, if we can find a way to use technologies to their full potential, we will be able to usher in a new era of healthcare that will benefit millions.