Advanced Therapies, Archaic Hardware: the Perils of Paper

The phrase “death by a thousand paper cuts” can be aptly applied to advanced therapeutics manufacturing.

Makers of the first wave of cell therapies leveraged existing processes to reach patients as quickly as possible. And that meant following a path based on manufacturing approaches that are efficient for scaling up large batches of small molecules or monoclonal antibodies, rather than applying bespoke processes to individual patient-derived cells for each therapeutic dose.

Multiple autologous cell therapies are now on the market, but there remain many opportunities in other therapeutic areas. But there are obstacles to reaching patients in need; namely, the high costs, long timelines, and large manufacturing facilities needed to make cell therapies.

One lesser discussed limitation is the use of paper-based records. A 1,000-page batch record isn’t so daunting when it represents millions of therapeutic mAb doses, but it’s a different story when the same type of paper record is required for each dose of an autologous cell-based therapy. After completing a commercial clinical dose, the batch record must be stored in a secure, fireproof cabinet until a document management company collects and stores it for years.

Paper batch records present significant obstacles to obtaining critical data insights, which are essential for accelerating process development and enhancing quality assurance in manufacturing. The inherent inefficiencies and lack of real-time data access delay decision-making and hinder the ability to quickly identify and rectify process deviations. Moreover, the manual nature of paper records increases the risk of errors and complicates the task of ensuring compliance and traceability across multiple production cycles and facilities.

A combination of digitization and integrated hardware is key to cutting the paper out of cell therapy manufacturing. Digitized data can easily be aggregated and used to refine processes. It can be integrated across different steps of the process, accessed across geographically disparate sites, and – crucially – shared with partners. Collaboration remains a critical part of cell therapy development, particularly for reducing the time it takes to make a dose and get it back to patients. Cloud-based research and development platforms will play a critical role in industrializing advanced therapy manufacturing.

During the early stages of development, drugmakers often don’t recognize the scope of challenges that paper represents for scale-up. What may work for tens of patients in an early-stage clinical trial is an untenable obstacle for a field aiming to treat tens of thousands of patients per year in the near term. It is common to hear early-stage developers say they plan to transfer processes to digital in time, but most realize – too late – that this change is not a minor consideration. It is a process transformation – and most of the challenges are difficult to predict.

Attempting to squeeze digitization into more mature workflows tends to add rather than remove complexity; building it in from the beginning is crucial to ensuring a smooth, sustainable scalability.

Moving away from paper also means automating and integrating connectivity into manufacturing technologies. In many fields, the Industry 4.0 trend of smarter machines improves efficiency and productivity in several ways; for example, making it clear when preventative maintenance is required. When a batch takes weeks to produce and where a single failure can mean life or death for the patient, equipment uptime is critical.

Especially for autologous cell therapies, complex supply chains are required to ship patient biological material from hospitals to manufacturing sites and back. In a paper-based system, manufacturing can be a black box, meaning doctors do not have the necessary information to make key decisions on patient care in the moment. Given that clinicians are managing patients in critical care, having access to data on the product and its estimated time of arrival, quality, and release time during the end-to-end manufacturing process can be invaluable. Hardware integration will be even more important as more patients need to be served at more distributed sites.

Smart manufacturing requires early investment in a different set of priorities and capabilities than today’s common approaches. For example, new closed and automated platforms need fewer human operators and less cleanroom floorspace, meaning drugmakers might not need large manufacturing facilities. On the other hand, robust internet connectivity becomes a much higher priority for maintaining and monitoring the Internet of Things-enabled device fleet.

Though many drugmakers wait to think about automation and smart manufacturing, those that adopt and initiate them early will see more significant impact. Early adoption lays the groundwork for resilient manufacturing and logistics models, robust and streamlined scale-up, and the flexibility to constantly learn and improve.