Taking a digital approach to advance cell and gene therapy
Global estimates for the cell and gene therapy (CGT) market show rapid growth at a compound annual growth rate (CAGR) of 22.42 percent from 2022 to 2030 with expectations to reach USD 93.78B by 2030.
The sector is seeing thousands of drug candidates currently under clinical and pre-clinical development and an increasing number of commercial approvals, including 10 new CGT approved in 2022.
Manufacturing productivity across the sector is low, however, and is constrained by manufacturing immaturity in both automation and digital technologies. To support the successful delivery of an increasing number of therapies to patients, it is critical to leverage digital tools and experiences across development phases and among the various stakeholders. Examples of this digital harmonisation might include the use of tailored digital platforms to enable different stakeholders to better communicate and share information as well as track the journey of a therapy, or the use of advanced analytics and digital tools such as artificial intelligence and machine learning to aid the manufacturing process.
Yet leveraging digital capabilities is perceived as a complex endeavour that requires different skills than are commonly available in the industry and digitalisation of a wide range of activities across the value chain of CGTs. Therefore, the perception is that digitalisation is too expensive and time-consuming to pursue.
The CGT industry, however, is moving in the right direction with the formation of various working groups and initiatives aiming to provide tools, solutions, and roadmaps for digital transformations in the biotechnology space. For example, the BioPhorum IT group for CGTs has created tools to identify who needs to be involved in the supply of different types of CGTs and what they do at a high level with particular focus on how IT systems can support the process.
Collaborating to drive change
To gain further insight on what has hindered adoption up to now, as well as to understand the main data and digital challenges facing the industry going forward, PA Consulting and the Cell and Gene Therapy Catapult jointly hosted a workshop at Phacilitate’s Advanced Therapy Week 2023 on “Building a common digital approach to unleash the CGT sector”.
The workshop identified major barriers which affect the development, manufacturing, and delivery of cell and gene therapies. It spanned a broad range of areas such as patient recruitment, enrolment, and therapy delivery at the point of care, data collection and data analysis during the therapy development and manufacturing process, interaction between manufacturers, suppliers, logistics companies, and hospitals, and more. The discussion led to the identification of dozens more examples of practical challenges faced by different stakeholders in the industry. Yet from all those practical challenges, some common themes emerged and can be grouped into seven key categories.
When analysing these seven overarching challenges it becomes evident to those outside of the CGT industry, particularly to those with experience in digitalisation, that these are not new or too dissimilar to what other sectors have experienced. The conversations highlighted the importance of cross-pollination to avoid embarking on digital projects seeking solutions that already exist and may well be easily tailored to service the CGT space. Below, we have highlighted these seven challenge examples:
The size, shape, and nature of data within CGT is complex and includes large data sets, such as genetic sequences, cell populations, and functional assays. The collection, processing, and analysis of these data sets can be a costly undertaking for small organisations as specialised tools, significant computing power, and expertise are often required.
However, the data complexity challenge has been solved in other adjacent areas of the healthcare industry such as gene sequencing, where large scale, non-alphanumeric datasets are well understood thanks to established cloud computing methods. Applying the learnings from these areas would solve for this challenge in CGT.
Integration is challenging on many levels. For example, pre-clinical development involves multiple data sources, including data from process development, animal studies, in vitro assays, and others. These data sources come in different formats or use different data standards. In addition, the data collection practices can be quite manual, especially in early development phases in academic labs. Lack of automated data collection and lack of alignment on best practices are key challenges for integration.
However, cross-industry healthcare bodies like medical societies regularly integrate diverse datasets from across healthcare systems in multiple countries. These bodies have invested in standards development, and show that with the right tools and methods in place, integrating diverse data sources is possible, and is already being done in other spaces.
The CGT industry continues to capture significant amounts of data in inaccessible and disconnected forms – in bench logbooks, paper records, and on stand-alone machines. Compounding this, the data being captured is increasingly sensitive. Data is no longer purely anonymous biochemical research in early-stage lab work, it now includes highly detailed, protected patient data alongside commercially sensitive corporate information.
As the industry matures it must make provisions for the appropriate management and safe disposal of the data and records it holds.
The introduction of European GDPR legislation over a decade ago led to all large pharmaceutical organisations having to take a revised look at records management; where information was stored, how research data was held, and in what jurisdictions. A similar approach can be applied to CGT record management.
Organisations need to have the right set of digital skills and competence to appropriately select and use digital tools and approaches. This enables the development and deployment of processes to capture, store, and analyse data, as well as ensure data security.
Organisations in the CGT space are often strong in science and engineering but lack deep digital competence. We’ve seen examples within the broader biotech industry where “CIO skills” can be dropped into startup organisations quickly through external experts to support in the early stages of their growth journey.
Security is a multi-faceted challenge. There are concerns associated with the potential for leaking sensitive patient data. With autologous therapies, there can be multiple hand-off points, exposing multiple systems and stakeholders to this sensitive data – an end-to-end solution is only as secure as the weakest link. It is therefore important to have strong solutions around chain of identity and chain of custody, two critical records used to ensure and monitor product safety, spanning from creation of the therapeutic material, through to administration into a patient and any follow-up activities. Importantly, there needs to be an audit trail of data to ensure legitimacy and that the data has not been corrupted or manipulated.
Completeness, timeliness, and accuracy of attributable data is critical across the entire product lifecycle. Poor-quality data can lead to incorrect conclusions, decisions, and lack of regulatory compliance. Quality issues can arise due to factors such as human error, equipment failure, improper data handling, or insufficient collection of data.
For example, front line hospital systems have been forced to tackle data quality issues for decades. This is to manage individual care pathways effectively, ensure clinical safety incidents don’t occur, and create efficient operations across healthcare systems. The data quality routines such as up-front data entry controls, regular data cleansing activities, and shared data quality teams can all support improved quality management in the CGT industry.
The overall process may require working and interfacing with a variety of products or systems that may input or output data in a variety of formats, be intermittent in providing data, or not provide any data at all. Being able to cope with this variability is important for successful and efficient implementation.
With various therapy developers using different systems, this can lead to clinical adoption problems downstream. For instance, various companies using different supply chain solutions mean hospitals offering different therapies may have to be trained on multiple supply chain solutions, wasting valuable healthcare professional time and resources.
The recent global vaccination initiatives surrounding COVID-19 has shown how interoperability of systems is important. During times of crisis or urgency, traditional barriers of interoperability are broken down – whether through formal or informal routes to ensure that data can flow and action can be taken where it needs to be.
Realising the benefits of digitalisation
An industry-wide consensus on how to harmonise would go a long way in removing key barriers to digital innovation and adoption. Various industry trade bodies and academic groupings are already investigating ways to replace the requirement for the current costly, time-consuming tailored connections. As a sector, if we can ensure that there is no compromise on flexibility when it comes to deciding which are the best systems and or vendors to use for any given activity or unit operation, then we will see an increase in leadership buy-in as well as the true benefits of digitalisation from much earlier in the product development lifecycle.