Reimagining the Future of Biopharma Manufacturing through Digital and Analytical Advances

In a highly regulated industry where the end product quality can be severely impacted by incomplete or erroneous information, biopharmaceutical companies have been trying to eliminate errors by adopting several ‘right-the-first-time’ initiatives. In fact, quality and compliance are largely intertwined in biopharmaceutical manufacturing processes, starting from the research & development (R&D) stage up till the actual steps involved in large-scale commercial manufacturing. As a consequence, biopharmaceutical companies ought to have an in-depth understanding of all information that needs to be captured at each process stage; utilizing them to design efficient and capable processes that are supported by process control tools that ensure quality is built into every step in the manufacturing process. To achieve this, biopharmaceutical firms are increasingly turning towards advanced technologies like Robotic Process Automation (RPA) and Artificial Intelligence (AI) to achieve zero process deviations while also unlocking productivity and efficiency gains that are redefining the future of biopharma manufacturing operations.

Challenges in extracting gains from biopharma plant operations

While the COVID-19 pandemic brought about massive disruption across the pharmaceutical industry, it also highlighted the fact that pharma companies are still lagging behind other industries in adopting technologically enhanced systems and capabilities. With a single biotech batch record comprising of as many as 45,000 manual entries, it comes as no surprise then that most delays in batch releases are due quality concerns arising out of missing batch information. Moreover, with biopharmaceutical companies tapping into new markets and ramping up their products portfolio, they are more exposed to supply chain disruptions than ever before. Relying on human planning for supply-chain planning and scheduling is therefore no longer an option, requiring companies to embrace AI tools to accurately predict demand, plan and manage inventory levels and leverage existing manufacturing infrastructure to extract more productivity. For the biopharma sector then, the challenge is to maintain high quality standards, slash drug development lead times and extract further manufacturing efficiencies; all in a bid to bring down manufacturing costs and provide more affordable treatment options for patients across the globe.

Why Continuous manufacturing automation is the need of the hour

Unlike traditional batch manufacturing that is reliant on substantial human intervention to manage and control the flow of biopharmaceutical manufacturing operations, continuous manufacturing involves the heavy use of automation technologies, equipment and tools to eliminate contamination, reduce production times and reduce process inefficiencies. By utilizing new-age technologies like Machine Learning (ML), Optical Character Recognition (OCR) and AI among a few others, biopharma companies can detect aberrations in real time and implement corrective actions to maintain robust quality control standards with continuous biopharmaceutical manufacturing. Leading biopharma players have in fact developed expertise in converting fed-batch to continuous manufacturing and are disrupting the cost of manufacturing complex monoclonal antibodies (mAbs) and even complex biologics. Some companies have developed proprietary continuous manufacturing platforms that can run as either integrated continuous or upstream and downstream discontinuous, deeming them capable of fulfilling varied product requirements. Moreover, since all units in the manufacturing process work in an uninterrupted mode, biopharma companies can produce drugs at a single manufacturing location with a significantly smaller footprint while also having the added flexibility to scale operations as per market demand.

Improving accuracy, quality and reliability with process analytical technology

In order to constantly improve processes and achieve more consistent quality levels, it is imperative to accurately capture manufacturing related data and use it to control process conditions instantaneously. Developing and implementing Process Analytical Technology (PAT) solutions that track critical process parameters, measure input material attributes and check quality parameters is thus extremely vital to continuous manufacturing operations. Not only do they implement diagnostic methods that detect anomalies during the manufacturing operation, but also involve the use of qualitative models that can scientifically assess all parameters to suggest process design changes. As a result, a clutch of biopharma companies are embracing network-wide digital transformation initiatives and leveraging the power of AI as well as big data analytics to record information and act upon it through automated strategies. The combination of continuous manufacturing operations and PAT tools can effectively address pain points such as abnormal deviation rates, low manufacturing productivity and yields; without the need to deploy additional human capital or make further infrastructure investments.

As biopharmaceutical companies rise up to the challenge of meeting the global demand for affordable healthcare solutions, it is imperative that they embrace digital and analytical advances to improve quality standards while bringing down the cost of producing biologics. In fact, adopting advanced continuous manufacturing platforms, integrating PAT tools and experimenting with the latest technologies will be essential to future-proof their operations.