Post-treatment follow-up of patients is not new. Traditional follow-up studies may last two to five years, while long-term follow-up (LTFU) studies can last from 15 years to a lifetime.

Cell and gene therapy (CGT) studies have particularly extensive follow-up requirements. In April this year the FDA issued a mandate requiring LTFU of patients who have undergone CAR-T cell therapy in response to emergent safety issues such as secondary malignancies.

With strategic planning and innovation, sponsors can optimise their LTFU studies to be flexible and cost-effective, overcoming challenges while capturing valuable data insights.

LTFU studies must demonstrate safety, efficacy and health economics for regulators and payers. These study requirements pose challenges such as patient retention over much longer periods, and extensive data collection and management. Sponsors must respond to these challenges and be prepared to adapt to further changes. Using novel data collection routes such as patient registries, tokenisation and integrating real-world data (RWD) can prove advantageous in LTFU. While patient safety will always be the primary driver, commercial imperatives are also a significant factor. The reimbursement mechanisms for new therapies like CGT are largely outcomes based, with the payer and developer sharing the risk. Data that demonstrates positive outcomes enables developers and clinicians to justify novel treatment plans.

Choosing the right study design is crucial in addressing these challenges. In traditional follow-up studies, which are relatively simple compared to LTFU, one protocol covers the treatment and follow-up stages. A single informed consent form (ICF), set of submissions, electronic data capture system (EDC), budget and team keep things streamlined. LTFU studies, particularly when unanticipated, can be much more complex. These studies may be implemented months, perhaps years, after the treatment phase has finished. Decoupled studies like these generally fall into one of two categories: single-feeder studies or multiple-feeder studies with RWD. Single-feeder studies involve patients who participated in the treatment study and are operationally challenging because they require two of everything: protocols, ICFs, submissions, EDCs, budgets and even teams. In the multiple-feeder model, patients from a programme of clinical trials (either closed or ongoing) and those treated in clinical practice are enrolled in the LTFU.

A more flexible approach, popular with CGT studies, is the basket LTFU study design. This allows multiple-feeder studies in a programme to funnel into a single LTFU study. It can be designed and implemented at any time, even after the feeder studies have closed. When properly planned, basket LTFU studies can be more efficient than multiple-feeder studies. Patient data is captured in a single LTFU protocol with a single ICF, budget, EDC, team and regulatory submission, making them more attractive operationally.

Basket LTFU studies require planning and a strategic approach across operations, infrastructure and stakeholder investment. This ensures each element is adequately resourced to meet any future changes. Basket study surveillance prioritises data integrity and streamlines data processing, thereby optimising efficiency, lowering costs and reducing site burden. A single extension team uses standardised data processing to mitigate risks of integration errors or variability. Data integrity is ensured within a single database. A single consolidated rollover master protocol is a key operational innovation used to ensure efficiency in the study design.

Models of this kind use scalable resourcing, giving them the flexibility to adapt to changing requirements. One global portfolio programme with a basket LTFU that ICON operationalised spanned 15 years. During the first few years the number of feeder studies increased by 600% and the number of sites by 400%. As novel therapies are developed, and new regulations put in place in response, basket models can adapt to new regulatory requirements. From a financial perspective, these studies use modular costing that allows a manageable budget allocation over the study’s lifetime.

Technological tools are being adapted and developed to support LTFU. Clinical trial tokenisation can complement or replace primary data collected by tracking study patients within real-world data sets. It uses encrypted tokens to isolate study cohorts in the data set, generating insights on long-term safety and effectiveness. AI is already being used to inform decision-making in clinical trial design and operation and can be applied to follow-up studies. When combined with RWD it can be used in multiple ways including to identify patient populations, refine endpoints, improve gene therapy engineering, predict safety outcomes and optimise protocols by providing insights into protocol complexity.

As the number of CGT trials increases, there will be a corresponding increase in LTFU studies. Sponsors need to plan for LTFU from the early phases, adopt innovative methods and be prepared to adapt to regulatory changes.

Harpreet Gill is VP, Real World Solutions, Project Management at ICON