Exploring the new manufacturing paradigm for commercial success
In order for cell therapy manufacturing to be successful after clinical development and into commercialisation, it is beneficial to operate based on a systematic development paradigm that addresses key drivers for commercially viable manufacturing; quality, cost of goods, scalability, and sustainability.
Automation can help achieve maximum potential for many of these elements.
When quality is at stake
Automation can improve quality in at least two ways. The first is by significantly reducing the risk of human errors. Any time a step in the manufacturing process (a specific unit operation) can be automated, the risk of errors due to simple mistakes in data recording, calculations, or precisely performing a tedious sequence of manual steps in the process is reduced. The second is by reducing variability in the process. Despite excellent training and experience, human labor is by nature variable; different individuals may perform a task a slightly different way, and there may even be small variances in the way the same person performs a task from one day to the next. Reducing this variability through automation means more consistent processes.
When cost of goods is at stake
Automation can reduce COGs by reducing the cost of manual labor (by reducing both the number of hours and level of expertise needed), the cost of equipment and associated consumables if several unit operations can be handled by one piece of equipment, and the cost of overhead if automating certain steps can reduce the amount of time and physical space needed for manufacturing. Labor costs, in particular, can have a significant impact on COGS—automating a particular unit operation might save one hour of labor per product batch in traditional pharmaceuticals where the batch provides treatments for thousands of patients or more, but with PSCTs, each batch is one patient, so the hour of labor is saved over and over again for each patient treated and adds up quickly.
When scalability is at stake
Automation can address the scalability challenge in a couple of different ways. First, treating exponentially larger numbers of patients without automated processes would necessitate an exponentially larger staff. This presents the challenge of recruiting and maintaining trained staff and can limit the rate at which scale can be increased. In the extreme where process complexity is high, there may not be enough qualified labor in the local geographic area to meet demand. In this case, automation becomes essential. Second, automation usually includes closed-system design, which can substantially shrink the necessary physical footprint of the facility as scale increases, as well as simplify the type of facility needed (e.g. controlled non-classified space instead of ISO 7 cleanrooms), all contributing to a shorter timeframe and lower investment burden to reach the targeted scale.
When sustainability is at stake
Automation can improve sustainability if applied carefully. For example, automating the materials handling and logistics can help manage relationships with suppliers, particularly as scale increases towards commercial requirements. This helps to ensure supply chain and delivery sustainability by providing the developer and supplier with real-time data on demand and supply.
In terms of commercial sustainability, monitoring process consistency over time will be critical. Automation of process data collection can be extremely beneficial to efficiently track and identify trends in the data in order to ensure that product specifications are maintained over time. Additionally, this type of automation can reduce labour requirements significantly compared to extracting data manually from hundreds or thousands of batch records.
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Flowchart representing a typical cell therapy product process: Image from Eaker et al, 2013, 'Concise Review: Guidance in Developing Commercializable Autologous/Patient-Specific Cell Therapy Manufacturing', Nov; 2(11): 871-883
Lipsitz, et al, (2016), 'Quality cell therapy manufacturing by design', Nature Biotechnology 34, 393-400