Five Digital Transformation Steps for Cell and Gene Therapies

Innovative cell and gene therapies can potentially treat and cure some of the most debilitating diseases known to humankind.¹ But moving preclinical candidates through development, manufacturing and regulatory approval presents some distinct difficulties compared to traditional drug development. Finding suitable genetic constructs, validating them in appropriate models, and shepherding them through clinical trials are all bottlenecks for cell and gene therapy developers.

The complexity of cell and gene therapies has necessitated the use of computational science and large amounts of digital data to reach the next milestone in pre-clinical and clinical development. While the most ambitious and accomplished minds are currently working in the cell and gene therapy space, many don’t have the computational training to navigate this complex digital expanse. In addition, the computational requirements have become a confounding barrier in cell and gene therapy discovery, development and manufacturing. Progress is severely limited by patchworks of difficult-to-manage custom code, siloed application and infrastructure components, and antiquated processes.

Tools from other biopharmaceuticals aren’t simply translatable to the cell and gene therapy world. Instead, a sea change in how we work and develop these therapeutics is essential. The required digital transformation is more than just “lifting and shifting” your old IT infrastructure to the cloud. We must remodel how we discover, work and communicate. We can only accomplish this with a robust digital transformation strategy and execution plan.

Below, we outline five steps to start you and your organization on the journey to implementing new, modern cell and gene therapy development methods.

Step 1: Create a digital transformation roadmap specific to your organization's needs

A successful commercial-scale cell and gene therapy development model starts with a digitally connected cohesive platform that allows for data traceability and integrity across all points of contact from the research laboratory, manufacturing, QC and supply chain to patient administration. But every team along this pre-clinical and clinical continuum will have specific (often non-overlapping) needs.

Therefore, it’s essential to determine the exact needs of various stakeholders and honestly prioritize the “nice-to-haves” versus “need-to-haves.” Based on these agreed-upon criteria, you can move on to the evaluation phase, where your team considers the relevant platforms to meet these needs.

Making such a wholesale change can seem overwhelming, but the most successful organizations don’t do everything at once. They take a modular approach to choosing a platform that allows for flexibility and agility in the ever-shifting landscape of therapeutic development.  There are many resources available for roadmap development, including, but not limited to, Miro, Monday and Roadmunk.

Step 2:  Implement a sophisticated data platform from research through commercialization

Guidelines for manufacturing cell-based therapies are changing as quickly as the science itself.  Manual, disconnected systems and workflows introduce inefficiencies in cell and gene therapy development. There needs to be more sustainable practices for achieving compliance against this rapidly evolving regulatory landscape.

If we look at other highly regulated industries digital transformation has already proven to significantly lower cost, improve quality and enable scalability while remaining compliant with regulatory requirements.²

In cell and gene therapy development programs, the goal is not to scale up the manufacturing of a single product to accommodate thousands of patients, but to scale out the manufacturing of small batches personalized for thousands of patients.³ Therefore, it’s essential to eliminate data silos and build a collaborative data platform to capture relevant documents and notes and provide a complete audit trail of changes to specifications and target control limits to mitigate risk and decrease the chance of clinical failure. This can be accomplished in various pre-clinical, clinical and manufacturing settings with all-in-one electronic notebooks, electronic batch manufacturing records (eBMR), and lab information management systems (LIMS) software.

These systems help companies move beyond data lakes and build federated data systems to enable a more accurate “bird’s-eye view” of operations across multiple data sources. Federated data allows end-to-end visibility of your supply chain, alert-driven event management, analytics and collaboration across teams, delivering more efficient and resilient cell and gene therapy development processes.

Step 3: Adopt intuitive and user optimized workflows so any team member can glean insights from informatics

Databases aren't just about collecting data.  It's also about generating insights and understanding what you can do with the data. With the explosion of available biological data from next-generation sequencing, it’s critical to incorporate bioinformatics and machine learning tools as core components of all cell and gene therapy development. This helps organizations better understand their internal processes and the patients they serve.

But these data analysis workflows must be accessible so that any team member, not just bioinformaticians, can make sense of the data in their experiment or operations.  The adoption of intuitive and user-optimized workflows allows streamlining the process of data to insights and every team member can keep up the pace.

True digital transformation involves empowering every person and team in your organization to drive innovation. As we know with the scientific process, innovation is a continuum that never stops, and organizations should adopt a mindset that enables them to continuously explore novel ways of solving problems. Democratization of analytical tools so that every person and team in your organization can drive meaningful transformation and make operations more efficient.

Step 4: Leverage deep learning to optimize cell and gene therapy commercial manufacturing

As former FDA Commissioner Scott Gottlieb noted, one of the most significant challenges of implementing cell and gene therapies is building scalable manufacturing processes.⁴ Despite substantial clinical and commercial successes, manufacturing vectors for cell and gene therapies remains challenging and has proven costly. 

We know that during the manufacturing process of gene therapies, the vector used to get the therapeutic into the cell of interest can introduce unintended consequences to overcome. For instance, viral constructs are often truncated within the transgene, leading to contaminated preparations of drug products. This reduces the overall quality, making gene therapies less effective, less safe and more expensive per dose.

Numerous constructs are developed and tested for efficacy without considering manufacturability or design flaws. Ultimately, this leads to increased time and cost associated with cell and gene therapy development and manufacturing.

Leveraging computational capabilities, namely deep learning algorithms, allows precise predictions about truncation and more efficient optimization of constructs. When combined with patient characterization data, these insights promise to improve the quality of personalized cell and gene therapeutics and enable the delivery of treatments to patients earlier.

Step 5:  Drive a culture shift across your team to create a sustainable transformation

One of the most essential yet often overlooked aspects of genuine, sustainable digital transformation is managing the transition process that needs to occur within organizations. A true transformation requires a self-motivated eagerness for change and a cultural shift in mindset.

To make this a reality, get buy-in from leadership and work with end users to understand their pain points. Learn about and communicate how this change will make their job easier. Some habits (even those that aren’t serving your teams) are hard to break, but demonstrating that less effort will be needed to get things done can be an excellent first step to driving the adoption of new technology. 

It’s essential to have resources with the commitment and time to help drive transformation and create sustainable change. For large companies with outdated legacy systems to overcome, it’s more than “lift and shift;” it’s reinventing. You’ll need to rely on your selected vendor and onboard external consultants during the transition. For small and mid-size biotech companies, external support may not be necessary. Dedicating a proportion of a full-time employee’s time and relying on platform vendor support will be sufficient to bridge that gap and help your team create long-lasting, meaningful change.

Conclusion

Cell and gene programs today require a multi-disciplined approach that involves numerous stakeholders. Digital transformation is a journey that needs to be incorporated as a core tenet of the organization with no end date. 

Creating a fully integrated, digital vein from the laboratory to the manufacturing platform and supply chain would dramatically reduce errors, decrease failure risk and increase both the speed and accuracy of cell and gene therapy products. The five steps mentioned above together with access to enabling platforms, will reduce restrictions on digital transformation and drive more breakthrough therapeutics to market.

References

1. Approved cellular and gene therapy products. FDA. Updated November 12, 2022. Accessed November 25, 2022. https://www.fda.gov/vaccines-blood-biologics/cellular-gene-therapy-products/approved-cellular-and-gene-therapy-products
2. Lessons from banking to improve risk and compliance and speed up digital transformations. McKinsey. Published June 20, 2021. Accessed November 12, 2022. https://www.mckinsey.com/capabilities/mckinsey-digital/our-insights/lessons-from-banking-to-improve-risk-and-compliance-and-speed-up-digital-transformations
3. Eaker S, Armant M, Brandwein H, et al. Concise review: guidance in developing commercializable autologous/patient-specific cell therapy manufacturing. Stem Cells Transl Med. 2013;2(11):871-883. doi: 10.5966/sctm.2013-0050
4. Gottlieb S. Remarks to the Alliance for Regenerative Medicine's annual boardmeeting. Published May 23, 2018.  Accessed November 12, 2022. https://www.fda.gov/news-events/speeches-fda-officials/remarks-alliance-regenerative-medicines-annual-board-meeting-05222018