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Automating Manufacturing Is Critical for Advancing Cell and Gene Therapies

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The heavily regulated and complex biopharmaceutical industry has been slow to change and adopt automated practices. A shift toward automation is a vital step forward to making breakthrough therapies more scalable and viable to help save patients’ lives. While the hurdles must be carefully considered, it is now time to accelerate digital transformation to enable the application of smart technologies, and specifically, to advance the cell and gene therapy industry.

Motivated by pandemic-driven changes in human resources and consumer behaviors, many companies in multiple sectors and regions were forced to accelerate their adoption of automated and other digital technologies. Many of these changes are here to stay.

In biopharma, automation and digital technologies are increasingly being incorporated throughout the entire drug development process, from the discovery of disease mechanisms to the industrial manufacture of regulatory approved therapies. Many laboratories are switching from paper records to electronic laboratory notebooks (ELNs) and digital laboratory information management systems (LIMS). This is the case in most biopharma labs as well as smaller, academic research institutions.

Many therapeutics begin in academic research laboratories, where basic research is performed to better understand disease pathways and identify novel targets for potential treatment. Transitioning a therapy from an academic lab to commercial scale can be particularly challenging for cell and gene therapies as academic teams may not focus on the scalability of production methods for industrial manufacturing.

Additionally, the requirements for transitioning from small-scale to large-scale manufacturing facilities can be stringent, especially when Good Manufacturing Practice (GMP) regulations must be met. To make the production methods originally devised at the research bench useable at scale, they may need to be radically altered, for example, by altering a batch production process into an automated continuous one.

Fortunately, the scale required for autologous cell therapies is not large. But not all cell therapies will be required only in small, single lots. The priority placed on developing allogeneic cell therapies, which are sourced from donors who are unrelated to the patient, means that large-scale production methods will also be needed, to produce large volumes of these therapies for multiple patients.

While genomic therapies, like traditional small molecule drugs, often include synthesis steps, they also often employ living cells in their manufacture and are relatively large, akin to the production and size of biologic drugs. These and other similarities may account for why pre-existing technologies and methods have largely been transplanted from the other two major drug modalities to discover and produce genomic medicines.

However, these transplanted technologies and methods are not always all that well suited to genomic medicines. Technologies and methods stemming from disparate processes and workflows can make it more difficult to incorporate digital transformation and automation, resulting in “islands of automation”. Clearly, there is a need for dedicated solutions designed specifically for gene and cell therapies.

These solutions can take many forms, including a digital approach. By focusing on key pain points expressed by their partners in the cell and gene therapy industry, cell therapy experts have determined that there are generally two kinds of solutions needed. One needs to address key bottlenecks within the various processes in the drug discovery and drug-making journey, and the other needs to address more overarching issues within the broader workflow. This includes solutions designed to better integrate various steps in the drug discovery, development and manufacturing processes, as well as enable more end-to-end visibility and control.

As more biopharma companies and academic institutions digitally transform their operations and infrastructure, automation, including that driven by artificial intelligence, can deliver much-anticipated improvements in terms of reducing hands-on time, resource utilization, and even risk, while at the same time increasing process and product consistency, scalability, and regulatory compliance.

Although hurdles remain, such as the continued need for bespoke solutions for this relatively new drug modality, the future is bright as the COVID-19 vaccines herald the advent of the genomic medicines age – one where we hope to see realized the promise of cell and gene therapies to deliver long-term remission and even cures for patients with some of the most difficult-to-treat diseases.