Can real-world evidence bring fresh thinking to the medical devices space? – Med-Tech Innovation
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The medical devices sector is characterised by constant innovation. As one device achieves regulatory approval, a new iteration is at the clinical trial stage, whilst yet another is being researched and developed. This rapid turnover in product line and improvements makes the traditional route of randomised controlled trials (RCTs) a costly one for device manufacturers. It also makes longer term post market surveillance difficult.
Whilst it’s a given that clinical trials play an essential role in developing the right treatments for the right patients, it is also a given that they are limited in scope. The controlled environments in which they take place make it difficult to replicate all the factors that could affect a successful, or less successful outcome. This means RTCs can only ever provide a partial view of how the medical device is predicted to perform within a mass market setting.
This is where Real World Evidence (RWE), collecting observational information outside of a clinical trial, could provide a more complete picture of how effectively a drug or medical device is treating patients with varying and individual needs. The information can be gathered from electronic medical records, medical claims data, medical registries, or the patients themselves, and by anonymising the data the patients’ privacy can be protected.
Registries can support the regulatory process
As more devices come into the market there have been renewed calls for regulatory reform. The Medical Devices report last year by the Regulatory Horizons Council, highlights the need for devices to be tracked over their whole product life cycle to increase safety assurance and support the ongoing needs of patients.
For this to be achievable, regulators are increasingly acknowledging that clinical trial research data alone is not the answer, and this is changing the parameters around regulatory decision making. An example being the 21st Century Cures Act in the USA, which mandated the need to explore the potential for RWE to inform regulatory decisions.
Nowadays, if the data has met certain criteria and conditions, then the RWE it has been drawn from can constitute valid scientific evidence. Registries are recognised as having the data collection and analysis infrastructure to support different types of trial designs such as RCTs and observational studies.
RWE provides a wealth of additional insight on how the device or medicine can be used for other purposes or groups not monitored in the original clinical trial and therefore not part of the original regulatory decision.
Given the costs of R&D, and the human cost of health if something goes wrong, it’s beneficial to all, from manufacturers to patients, that insight is captured from as large a pool as possible. If robust processes are in place, registries, and other sources of RWE could be a gamechanger in the medical devices sector. As it would enable more effective post market monitoring bringing greater reassurance for patients, regulators, clinicians, medtech and pharmaceutical companies.
Take the National Joint Registry (NJR), for example. It holds over three million records and is the largest registry of its kind anywhere in the world. Since submissions are mandatory it has the coverage and scale that gives the medical community confidence in the evidence to know what will and what will not work in the real-world. The NJR captures granular characteristics of implants. It’s these different aspects of the data that lend it power to analysing and comparing outcomes. Having this granularity of information makes it much easier to understand treatments in more depth and assess what can cause variations in patient outcomes.
Improving clinical and regulatory decision making
The Regulatory Horizons Council Medical Devices report makes mention of the need to detect adverse events occurring either rarely or a long time after the device is fitted, and the ability to track and trace patients in the event of a recall. Registries can help facilitate this, one such example being the National Vascular Registry (NVR) collection of data on an implantable device designed to prevent abdominal aortic aneurysms.
The RWE collected at scale via registries such as the NVR could greatly assist in plotting the long-term outcomes of procedures against a larger coverage of the population than is possible within a traditional clinical trial setting.
Having a good feedback system in place within registries is also hugely beneficial. Learnings extrapolated from the real-world data can then be fed back to the hospitals and clinicians to improve clinical practice and patient outcomes.
A vital role in the creation of new treatment pathways
Using RWE could be a critical driver in helping regulators, MedTech and pharmaceutical companies and clinicians better identify trends and patterns in patient outcomes that will ultimately lead to better real-world answers (RWA).
Registries can help play a vital role in the design and creation of new critical treatment pathways by measuring the effectiveness of drug, therapy, and implant interventions against a larger cohort of patients than is possible in clinical trials.
Drawing upon a larger, more accurate and comprehensive real-word evidence base, alongside results from RTCs would enable healthcare professionals to determine with increased confidence, what works best, under what conditions and for who. For example, what type of heart valve performs best at scale on men over the age of 50 with additional underlying health conditions, compared to those over 50 who are otherwise in good health.
To safeguard scientific validity however, the collection of quality RWE is essential. The reliability and relevancy of the information must not be compromised, or it will risk undermining the value of RWE. That’s why having recognised mechanisms and processes in place like those in a registry will be increasingly important going forward.
RWE enables patient centric care
Advances in machine learning and AI will continue to enhance the medical community’s ability to make effective use of RWE at speed. Up until now there have not been the technical tools to collect quality data at scale. However, advances in data analytics and artificial intelligence have now made it possible for more accurate and reliable insights to be gained from RWE sources.
This new ability to extrapolate data from multiple real-world sources will allow clinicians to take a more personalised approach to patient care.
The application of AI and machine learning techniques against these large volumes of data can filter out the ‘noise’ inherent in such analysis and help pinpoint what treatments are producing the best outcomes. And there has never been a greater need to seek out cost-effective patient treatments and outcomes. The health sector was already bowing under the growing economic pressures associated with an increasing prevalence of age-related disease, which has been further exacerbated by the inflationary costs of medical care.