Digital Twins & The CGT Value Chain: A Universe Of Possibilities
By Kerim Ozbilge and Frank Traina, EY
The promise of cell and gene therapy is now a reality. There are 23 FDA-approved cell and gene therapies (CGTs) to date and, globally, 3,633 therapies (including RNA) in development.1,2 With continued strong financing, EY teams project that, by 2027, the CGT global market will grow to an estimated $50 billion annually. But this growing success results in higher complexities for CGT organizations. As they scale their product portfolios, modalities, and global networks, their variabilities and operational risks will increase.
CGT manufacture, delivery, and cost represent a huge departure from traditional pharmaceutical models. These therapies have a bidirectional value chain involving nearly triple the number of steps, leaving zero room for error. Autologous therapies involve more than 40 coordinated digital and analog hand-offs between disparate teams of healthcare providers, manufacturers, third-party logistics companies, and payers, each with their own software tools, processes, and workflows. For these made-to-order therapies to be safe and affordable, reliability, agility, and interoperability among all members of the CGT ecosystem are key.
CGT companies are investing to develop future-ready capabilities and transforming to meet the specific needs and growing complexities of the end-to-end CGT value chain. Increasingly, they are establishing decentralized point-of-care manufacturing facilities (their own or externalized) to reduce logistics lead times and therapy costs and to be closer to patients so they can be better served. But global operational expansion requires higher visibility and control over chain of custody, product quality, and global regulatory compliance requirements. This is further taxing the limits of this nascent industry.
For CGT organizations to continue to scale their business and support their growth, the processes and technical capabilities developed during the clinical stages require an uplift. In response, organizations are investing to reevaluate their operating model, redesign their processes, and further digitize and automate operations for greater agility and efficiency without compromising quality control.
Fortunately, the CGT revolution is coinciding with Industry 4.0 and the myriad digital technologies from which healthcare, and CGTs in particular, can benefit. At the forefront are digital twins.
Digital twins combine numerous technologies, such as at-scale computing, modeling methods, and Internet of Things (IoT) connectivity, to create full-scale digital replicas of physical assets, such as cars, or real-world processes, such as factories or value chains and even humans. Digital twins are updated from real-time data and use simulation, machine learning, and reasoning to help decision-making.
In the last two decades, many industries involved in large-scale products, projects, or systems have benefited from digital twins, including the manufacturing, automotive, aviation, energy and utilities, logistics and retail, and healthcare industries.
Digital Twins For Better Health Outcomes
Physicians and researchers are using digital twins to predict health outcomes, improve care, track treatment effectiveness, and more. For example, it won’t be long before more patients don virtual reality headsets in consultations with their doctors or wear biometric or “smart” tattoos to take blood and tissue readings.
For the millions of patients battling difficult-to-treat diseases, such as cancer and inherited genetic disorders, digital twins can literally pave the way for life-prolonging or life-saving advanced therapies. CGT companies are investigating this technology’s utility in addressing key value-chain pain points, such as:
- Ecosystem interoperability
- Digital twins allow real-time, secure information exchange and improved collaboration across all the functions and partners in the value chain involved in time-sensitive decisions around patient care and treatment delivery, including physicians, hospitals and clinics, laboratories, and payers.
- Risk mitigation
- Embedded advanced analytics accelerate the prediction, identification, and assessment of risk events. Digital twins can keep a watch on critical variables, including quality and process attributes, transport temperatures, manufacturing schedules, and chain of custody, and recommend adjustments as situations change.
- In addition to real-time alerts, digital twins use advanced simulation and modeling to provide business insights and recommended actions, with mitigation plans balancing customer service and cost.
- Digital twins continuously learn and improve to better inform decision-making.
- Optimized manufacturing
- Digital twins powered by IoT sensors, process analytical technology, and advanced analytics reduce batch waste and increase quality and reliability in a distributed manufacturing point of care setup by closely monitoring critical quality and process attributes.
- As variability occurs in the value chain (e.g., demand variability, raw material availability), AI support mechanisms improve decision-making so that companies can better allocate limited manufacturing capacity.
- Post-infusion monitoring
- Patient progress can be tracked with ingestible sensors and real-time analytics that help determine their body’s reaction to the therapy, which is compared to data from similar patients. This information is then transferred to the patient’s digital twin, where different treatment strategies are explored prior to making any adjustments.
Planning Ahead
For CGTs, the importance of flexibility, risk tolerance, and rapid decision-making in the personalized cancer treatment journey cannot be overestimated. CGT companies should invest early in the right infrastructure and tools, build a skilled workforce and digital culture, and set up a digital twins operating model that can grow with their operations and drive efficiencies, reduce errors, and deliver better patient outcomes. While they may face challenges in defining the right architectural vision and strategy, they don’t have to do it alone.
References
- FDA, “Approved Cellular and Gene Therapy Products,” https://www.fda.gov/vaccines-blood-biologics/cellular-gene-therapy-products/approved-cellular-and-gene-therapy-products
- ASGCT and PharmaIntelligence, “Gene, Cell, & RNA Therapy Landscape: Q2 2022 Quarterly Data Report,” https://asgct.org/global/documents/asgct-pharma-intelligence-quarterly-report-draft-q.aspx
The views reflected in this article are the views of the authors and do not necessarily reflect the views of Ernst & Young LLP or other members of the global EY organization.
About The Authors:
Kerim Ozbilge is an EY partner in the Supply Chain Advisory Services practice with 23 years of advisory experience successfully driving organizations through their business transformation objectives for improving supply chain and operational efficiency, resiliency, and profitability. For the last 13 years, he has served life sciences clients, including cell & gene therapy companies, by helping them improve their business processes, implement supporting digital capabilities, and drive operational efficiencies across supply chain and technical operations functions.
Frank Traina is a managing director in the EY U.S. Health Sciences & Wellness sector. He has 20 years of experience working with emerging technologies. He teams with health sciences companies to promote information ecosystems for patients and their care providers, leveraging innovative data and capabilities.