“Nature abhors a vacuum,” and health technology assessment (HTA) bodies and payers hate uncertainty. Unfortunately, when it comes to advanced therapy medicinal products (ATMPs), they must contend with considerable uncertainty. ATMPs, such as gene therapies, pose a challenge for assessors because they come at a high cost (commonly over $1 million) via a single administration and often are approved by regulators on limited or immature data. Yet, their value is realized over the long term and some are potentially curative.
Meanwhile, drug sponsors are hindered in their ability to produce the evidence that HTA bodies and payers want. ATMPs typically target rare diseases involving small numbers of patients. Clinical trials of these therapies are often open label studies (sometimes with no comparator or historical controls), are of short duration with limited follow up, and in some cases, are lacking in appropriate outcome measures.
Because assessors aim to evaluate these products on their magnitude and durability of effect and long-term benefit, there is a need to continue generating evidence once they are on the market. Many of these therapies are, therefore, re-evaluated three to five years after the initial assessment, a process that can be supported with data from digital technologies such as sensors and wearables. Interestingly, many of these technologies are the same solutions that the industry has recently embraced to alleviate disruptions and mitigate patient risk during the COVID-19 pandemic. In some cases it maybe that digital technologies may allow assessment of more relevant outcome measures that can be captured in a passive way.
Strategies for Limiting Budget Impact
Payers use a variety of mechanisms to limit the impact of ATMPs on their budgets, to include managed-entry/risk-sharing agreements that are either based on outcomes or characterized by financial mechanisms such as simple discounting or utilization caps.
In the UK, the National Institute for Health and Care Excellence (NICE) many years ago moved away from pay-for-performance contracts and instead utilises financial based agreements that essentially requires a discounts to offset the uncertainty over a product’s value. In the US where there is no national HTA agency, payers will cover a gene therapy if FDA approved. Many US payers report that if they have the opportunity they will negotiate a performance based agreement with payments made in instalments. This way they limit financial risk by spreading payment over time and by only paying for agreed outcomes. Increasingly, these performance-based arrangements focus on the impact of a therapy on a given patient, rather than across participants in a clinical study.
Solutions within the Digital Ecosystem
The increased use of smartphones and sensors in real-world settings – for example for measuring activity levels – has given Sponsors the impetus to adapt them to generating digital endpoints in clinical research. The industry was collecting data from electronic health records, wearables, sensors, and smartphone apps before the emergence of the global pandemic. However, the necessity of limiting patient visits to clinics during the health crisis has led sponsors, clinicians, and regulators to embrace their full potential.
The pandemic has even spurred the development of new technologies such as tele-ophthalmology to conduct online eye exams. And, inexpensive technologies are being introduced to measure quality of life endpoints (such as sleep and activity) that are both important measures for ATMP assessors and can provide data over many years.
The benefits of collecting data from digital devices include:
- More frequent and continuous monitoring – beyond the walls of the clinic
- Easy and simple data capture
- The possibility of more precise and accurate assessment than traditional observational assessments [1]. Digital sources provide both nuanced information and contextual insight.
- Cost effective when patients can use their own devices
- Reduced bias when patients use their own passive devices, as they don’t change their behavior for the study
- Development and assessment of more relevant outcome measures
- The ability to answer the efficacy question for individual patients
Advances in Digital Endpoints
As more digital technologies enter the market and are integrated into clinical research, we foresee a shift from digital endpoints being used as supplementary endpoints to their use as primary endpoints. Digital health technologies provide a robust, continuous data stream that enhances the quality, quantity, and frequency of data collection, providing meaningful insights on patient outcomes.
Many technologies, for example, capture digital endpoints that are of keen interest in diseases of the central nervous system as well as in rare diseases, two-thirds of which affect children. [2] For instance, devices and apps are available to measure gait with nuanced information on how people place their feet, their walking velocity, stride length, and step cadence. [3] These measures are more detailed than those of observed walk tests.
As another example, fitness trackers with geolocation capabilities can be used to monitor the impact of a disease on a person’s ability to function although this could be problematic from a data privacy perspective. Monitoring a person’s movement away from the home environment may serve as an important measure of quality of life for someone with impaired vision or a movement disorder.
Other devices and apps can track and measure falls/spasms, visual function, vital signs, temperature, voice analytics, and respiration – a list that will undoubtedly expand as innovation continues and the demand increases.
The caveat is that selected devices must be capable of producing robust data that meet the same requirements that payers apply to conventional assessments. For example, a common fitness tracker worn on the wrist may not work in assessing gait changes in patients with Duchenne Muscular Dystrophy. Rather, digital devices must be validated against a gold standard technology to generate endpoints that are meaningful. And, that robust device and endpoint validation will be required.
A Promising Example
Duchenne Muscular Dystrophy (DMD) is a rare disease with symptom onset in early childhood, usually around age two or three. [4] While currently there are limited treatment options, it is an area of very active clinical development. The primary outcome in clinical trials is a measure of progression based on movement detected using in clinic assessments such as the six-minute walk test, the North Star Ambulatory Assessment (NSAA) and/or the four-stair climb. [5]
The European Medicines Agency (EMA) has qualified stride velocity 95th centile as a secondary endpoint measured by a valid and suitable wearable device. This ambulatory endpoint which can be captured passively in the home was correlated with both the six-minute walk test and the NSAA [6]. The agency has indicated that the endpoint has the potential to provide data on a primary endpoint in clinical trials, although more robust data from more patients over a longer period is required.
There is the potential to validate other assessments that may be more meaningful to patients and parents and impactful of their over-arching quality of life e.g., upper body movement. Although recognized as an important characteristic for patients living with DMD it is challenging to assess upper body movement in a robust and reliable fashion, and could be the target for new objective digital tools. This would be an example of a new outcome measure that is potentially more clinically and payer relevant.
Conclusion
Robust assessments based on digital data are a means of reducing the uncertainty that HTA bodies and payers face in making decisions around advanced therapy medicinal products. Digital sensors can capture existing measures in a new way and/or collect new measures that were previously impossible. As the global pandemic has accelerated the use of digital technologies for data collection in clinical trials as well as fostered the development of new measures, we see their use as a solution to meeting the evidence needs of HTA bodies and payers on therapy’s long-term benefit.
Authors
Marie McCarthy, MSc, MBA
Senior Director, Product Innovation, ICON plc
Marie has over 20 years’ experience working in the area of medical devices and in-vitro diagnostics. At ICON her focus is on the use of wearables and sensors to generate digital endpoints in clinical trials. She provides insight into outcomes addressed by wearable technology and has designed and led a number of pilot projects focusing on the use of mHealth technologies in redesigning the clinical trial.
Bob Swann, MBA
Senior Principal, Global Pricing and Market Access, ICON
Bob has over 25 years’ experience in market access consultancy and industry. At ICON he is a project lead for global pricing and market access client engagements. His experience includes all access including pricing, reimbursement, HTA support, multiple therapy areas and product types including ATMPs.
References
[1] Coravos, A., Khozin, S. and Mandl, K.D. Developing and adopting safe and effective digital biomarkers to improve patient outcomes. npj Digit.Med. 2, 14 (2019). https://doi.org/10.1038/s41746-019-0090-4
[2] https://research.sanfordhealth.org/fields-of-research/pediatrics-and-rare-diseases
[3] https://www.clinicaltrials.gov/ct2/show/NCT03921697
[4] https://www.duchenne.com/about-duchenne
[5] https://www.duchenneuk.org/outcome-measures
[6] https://www.ema.europa.eu/en/documents/scientific-guideline/qualification-opinion-stride-velocity-95th-centile-secondary-endpoint-duchenne-muscular-dystrophy_en.pdf