Simplifying CGT: A Necessary Precursor to Integrating AI and Automation

Josh Ludwig, Global Commercial Director, ScaleReady

Over the past decade, the landscape of cell and gene therapy (CGT) has experienced transformative growth. Artificial intelligence (AI) and automation will be necessary next steps for CGT manufacturing to reach its full potential. However, in order for these new technologies to play that role, it’s crucial first to understand them in the context of the particulars of these therapies.

At its core, cell therapy involves administering live cells to a patient to treat or prevent a disease. This can be as straightforward as replacing damaged cells with healthy ones. Gene therapy, conversely, involves the delivery of genetic material into a patient’s cells to correct, replace or insert modified material, such as chimeric antigen receptors (CARs), to enhance the targeting powers of T cells against cancer cells.

The manufacturing process for these therapies is incredibly complex. Unlike traditional small molecule drugs, CGTs involve live cells, which are unique and difficult to handle. The steps for production include cell extraction, activation, genetic modification, expansion, purification, formulation and finally patient administration. And while AI and automation are hailed as a panacea for handling such complexity, the reality is that existing processes can be simplified well before implementing these new technologies, making the eventual transitions streamlined and efficient.

Making CGT manufacturing simple

The CGT domain, with its promise of transformative treatments for a multitude of conditions, is among the most dynamic and intricate in the biopharmaceutical arena. But as we stand at this promising frontier, there’s a pressing need to enshrine a foundational tenet: the emphasis on simplicity before the integration of AI and automation.

Given the inherently complex nature of CGT manufacturing, simplicity may sound counterintuitive. The explanation lies in understanding the specific demands of CGT production. Every patient and every cell are unique. Simple, modular, and adaptable systems allow for customisation and flexibility in a landscape where one-size-fits-all solutions often fall short.

Another is the connection between AI and automation. Many in the CGT field expect AI to identify process improvements, and automation to help implement them. But while the combination heralds a future of increased efficiency and scale, their premature integration – without first simplifying unnecessarily complex processes – can introduce challenges that diminish and limit their potential advantages. Simplifying processes is not just desired but imperative, due to cost implications, time delays, the need for standardisation and concerns over safety and efficacy.

Incorporating AI and automation into an already intricate process actually amplifies complexities. These increased complexities demand more resources, both in terms of technology and manpower, to manage and rectify. As these costs escalate, they invariably are passed on, impacting the end price for patients. And complexity often translates to longer lead times, both in terms of setting up the automated systems and troubleshooting them. This can significantly lengthen the time it takes to get therapies from bench to bedside.

Before we can effectively leverage the full potential of automation, we must establish standardised processes. These can reduce variability, streamline operations and provide a consistent foundation upon which automation can be introduced. In addition, with therapies as crucial and transformative as CGTs, there’s no margin for error. Introducing automation into a non-standardised process can result in inconsistencies that might compromise the safety and efficacy of the final product.

Automation platforms that embrace simplicity are more easily validated for regulatory compliance. They can be integrated seamlessly into existing workflows, and because they’re more user-friendly, they can reduce training time and costs, and can be quickly adjusted or reconfigured as understanding of processes evolve.

Reversible scalability

While the biopharma industry often discusses the importance of scalability, in the context of CGT, this doesn’t only mean ramping up production to treat thousands of patients. It also means the capability to scale down to treat individual or small numbers of patients, particularly in the case of ultra-rare diseases or personalised therapies.

Adopting automation platforms that allow for both large-scale and small-scale production ensures that manufacturing processes remain consistent. It also means costs can be controlled, whether producing one therapy or many. And it enables greater accessibility to CGTs for both large patient populations and to niche groups, ensuring that no patient is left behind.

Reverse scalability is also critical for making the most of the insights gleaned from AI. Today, enabling technology like Wilson Wolf’s G-Rex allows CGT developers to easily scale down and back up again. This makes it simpler to change processes when needed, for example to address issues that arise in clinical trials.

Without this ability, developers must either wastefully test modifications in large batches or switch between incongruous small and large platforms, resulting in repeat testing and validation. One of the biggest expectations for AI is that it will help parse which factors and processes are most important for cellular end product quality, and recommend certain changes. If this comes true, it means the ability to reversibly scale in order to test changes will become even more prevalent, perhaps even for late-stage and commercial therapies.

Preparing to implement AI and automation

For the CGT sector, the ultimate benchmark of success is patient impact. Our priority is, and should always remain, the rapid and safe delivery of therapies to patients at a cost that ensures broad accessibility. With this patient-first mentality, it becomes evident that we need to first simplify and standardise our processes before we integrate advanced technologies.

Once we achieve a level of simplicity and uniformity in our processes, the introduction of AI and automation can be truly transformative. They can expedite processes, minimise human-induced errors, and enable the manufacturing of therapies at scales previously deemed unfeasible. All of these benefits culminate in faster time-to-market and potentially reduced costs—direct advantages to the patient community.

The realm of cell and gene therapy manufacturing involves the interplay of biology, engineering and medicine. As the industry matures, adopting AI and automation will not merely be a choice but a pressing necessity. The advancement into these sophisticated technologies must deliver the promise of efficiency and consistency and ensure that these revolutionary treatments can be made available to all who need them.

In the world of CGT manufacturing, where the unmet need is glaring and the therapeutic potential is equally evident, it’s tempting to leap into the future, but the real promise lies in mastering the basics first. In this endeavour, simplicity and adaptability in our automation approaches are our allies, relying on technology like the G-Rex that can operate at any scale. As we navigate the complexities of living cells and genes, let us not forget the power of simplicity and the importance of scaling in every direction to truly realise the potential of cell and gene therapies.


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