Automation and Digital Manufacturing for Cell and Gene Therapies ‒ Why Paper Is the Enemy of Scale

Current Challenges

Recent approvals¹  from the US Food and Drug Administration (FDA) and Medicines and Healthcare products Regulatory Agency (MHRA) for potentially curative therapies in difficult to treat blood cancers, such as leukemias, lymphomas and most recently multiple myeloma, offer some hope to patients looking to benefit from these lifesaving therapies. Yet <2%² of the patients who could benefit from these therapies have gotten access – due to significant scale-up challenges faced by developers bringing these treatments to market.

Many of these challenges can be traced back to process challenges like paper-based quality assurance/quality control (QA/QC) and the failure to establish the chemistry, manufacturing and controls (CMC) process for advanced therapy medicinal products (ATMPs) early enough. For those that have succeeded in making it to market, the cost of manufacturing and QC are so high that these potentially curative therapies³ are expensive and therefore often only offered as a last line therapy to refractory patients who have failed all other treatments.

Defining a CMC process for ATMPs is significantly more complicated than that for small molecules or biologics, as the production of living cell-based products is inherently variable in nature and the manufacturing process must be able to accommodate this variability. At its most extreme, we have patient specific (autologous) ATMPs, where each batch is unique to an individual patient. For example, chimeric antigen receptor T (CAR T)-cell therapies are produced using the patient's own cells, which are genetically modified and cultured ex vivo in an often 14–21-day process.

Experts⁴ agree that CMC should start as soon a potential therapy has been identified in preclinical activity in the lab. Detailed records of the chemical and biological processes used to produce the therapy must be recorded. This record-keeping must be able to scale as the therapy moves through the subsequent development, clinical trials, and manufacturing phases. With ATMPs, however, this is frequently a manual process, with paper-based records being created and stored. There are several knock-on effects of this. Manual record-keeping is laborious and error-prone, the storage of the records is costly, and the subsequent QA and QC processes can only be provided by specialists who have access to the physical records acting as a bottleneck to scale. These paper-based processes also increase the challenges of process characterization, comparability, tech transfer and gaining regulatory approval. Iovance, Novartis and Bristol Myers Squibb are all examples of companies that have faced challenges in translating their preclinical/clinical processes to commercial scale.

The manufacturing requirements of ATMPs are also extremely difficult to scale out from the lab. For autologous ATMPs, each manufacturing run creates a single treatment for an individual patient. This means it is only currently possible to scale out the manufacturing horizontally, by adding in new manufacturing units through manual interventions by a highly qualified workforce requiring significant investment in facilities and human resources. The more manual the manufacturing process is, the harder this scaling becomes and the more costly the Cost of Goods (COGs) are for the resulting treatments. In addition to this, the patient specificity of these treatments means that cross-contamination or incorrect administration would have very severe consequences on the health of the patient creating a zero-defect requirement in manufacturing. This makes the regulations for manufacture, chain of custody (CoC) and chain of identity (CoI) both critical and potentially costly to implement. It also means that, unlike traditional pharmacological treatments, each autologous therapeutic dose must be subject to individual QA and QC checks acting as a bottleneck to scaled production.

Finally, the logistical challenges of personalized autologous therapies being manufactured in a central manufacturing facility presents significant challenges for ATMP manufacturing. These challenges call into question the logic of trying to retrofit old paper-based, centralized manufacturing models and warrant us thinking about newer digital platforms that may allow for manufacturing closer to the patient. As we say at Ori, paper is the enemy of scale.

Visioning the solution with digital 

If we look to other highly regulated industries such as finance, banking, general manufacturing, and mass transit systems, a cloud-first digital transformation has already proven to be of significant positive impact to cost, quality, and scale, whilst remaining compliant with regulatory requirements.

Many of the costs and scaling issues caused by the existing paper-based records in AMTPs could be alleviated by using integrated, cloud based, digital platforms including electronic batch manufacturing records (eBMR), manufacturing execution systems (MES), Lab Information Management Systems (LIMS), digital CoI/CoC solutions and other relevant digital systems. These systems can capture all the in-motion protocol unit operation, for example sensor and analytic readings, and the mechanical and environmental state of the system during the manufacturing run. Capturing this data in a fully digital, IIOT construct provides valuable insights for process characterization and effective root cause analysis, helping to reduce the process development cycle time and cost. Collating all the data captured during this phase seamlessly feeds into the tech transfer and the CMC evidence required for regulatory approval. During the manufacturing process, the captured data meets the needs of QA & QC, whilst allowing sign off by remote QC specialists. Furthermore, by virtue of being digitized, the QC process can be further streamlined by allowing process deviations to be detected so that manual QC can be targeted to these exceptional cases only (i.e., release by exception).

Once these data points are collected in a digitally native platform, opportunities are opened up to create links with other systems in the supply chain in a way that has not been possible until recently. These digital integrations allow better management of both up and downstream resources and therefore help to reduce manufacturing timescales and cost.

Creating a fully integrated, digital vein to the manufacturing platform and supply chain, would dramatically increase throughput and the potential for full automation. This would increase both the speed and accuracy of the manufacturing process, reduce the likelihood of CoC and CoI errors and open up the possibility of distributed manufacturing.

This data also has significant potential for providing deep insight into optimal biological processes earlier in the preclinical process discovery phase in order to reduce development times and improve visibility into sources of variability and opportunities for optimization. If this is combined with patient characterization data, these insights hold the promise of being able to predict the progress of protocols for individual patients and to provide recommended in-motion adjustments to improve the quality of the resulting therapy. These predictions may also help to better prepare resources and clinical sites post-manufacture, potentially getting treatments to patients earlier and saving more lives.

Innovative cell therapies, such as CAR T-cell therapy, and gene therapies will only be able to have a significant clinical impact if they prove to be financially viable for the manufacturers. If not, the unfortunate scenario would be that so few ATMPs reach the market at scale that therapy developers abandon this promising treatment modality entirely. These curative treatments are available now, we must not let patients down by letting them slip through our fingers because of these challenges.

References
 

1. Approved Cellular and Gene Therapy Products. FDA. https://www.fda.gov/vaccines-blood-biologics/cellular-gene-therapy-products/approved-cellular-and-gene-therapy-products. Published March 1, 2022. Accessed April 1, 2022.
2. Swetlitz I. Hospitals are saving lives with CAR-T. Getting paid is another story. STAT. https://www.statnews.com/2019/03/12/hospitals-arent-getting-paid-for-car-t/. Published March 12, 2019. Accessed April 1, 2022.
   
3. Melenhorst JJ, Chen GM, Wang M, et al. Decade-long leukaemia remissions with persistence of CD4+ CAR T cells. Nature. 2022;602(7897):503-509. doi: 10.1038/s41586-021-04390-6
   
4. Macdonald G. Dev. COGS crisis: Cell therapy sector must rethink CMC, says expert. Dark Horse Consulting. https://bioprocessintl.com/bioprocess-insider/therapeutic-class/cogs-crisis-cell-therapy-sector-must-rethink-cmc-says-expert/. Published August 6, 2019. Accessed April 1, 2022.

  
About the Author

Matt Todd is a pragmatic technologist with over twenty years of experience as an expert in the technology and data space, including ten years as co-founder of an application development company. He is currently Head of Architecture at Ori Biotech, a cell and gene therapy manufacturing technology company with offices in London and New Jersey which raised a $100M Series B in December 2021.

Having worked with a broad range of technologies and methodologies his focus is always on maximizing value and ROI by pushing for the adoption and enablement of situational best-fit solutions to deliver on strategic objectives.

Matt has deep knowledge of architecture and data at all levels of the business, combined with the operational experience of designing, building and operating mission-critical systems at scale in cloud-native environments. He gained a BSc in Artificial Intelligence and Computer Science at the University of Birmingham and remains an active member of the Birmingham technology scene.