An End-to-End Solution is Required To Run a Successful Digital Trial
The pharmaceutical industry spent approximately four times more on R&D in 2015 than in 1995, with no corresponding increase in the number of drugs approved by the FDA (1). These spiraling costs can be attributed to a transition away from the traditional “one size fits all” model, which has led to difficulty defining clinical endpoints and an inability to recruit or retain patients.
As a result, digital disruption in the form of new wearables, sensors and medical devices are emerging to enable pharmaceutical and medical device companies to generate new types of datasets. Moreover, artificial intelligence and machine learning can generate new insights and responsive digital biomarkers from these new datasets. All of these factors are coming together to enable a growing revolution that can combat declining R&D efficiency: the implementation of digital trials.
Digital trials, which are defined as the use of mHealth and mobile technology to capture insights outside of a traditional clinical setting, present solutions to the challenges being faced by the pharma industry, making them increasingly appealing to patients, healthcare providers and payers. The global movement towards digital clinical trials has been occurring over the past several years and it offers drug companies the opportunity to leverage the technical advances in this huge and growing mhealth market, estimated to be worth $163 billion by 2020 (1).
Benefits of digital trials
In a recent survey carried out by the Centre for Information and Study on Clinical Research Participation, 24 percent of participants cited “too many study visits” as the reason for deciding not to take part in a clinical trial, while “travel burden” was cited by 79 percent of those surveyed on the barriers for clinical research participation (1).
As a result, there has been increased awareness of the value of a mHealth in clinical trials to improve patient recruitment and retention. For example, hospital networks such as the UCLA Health , are using mHealth to monitor patients remotely, allowing patients and caregivers to manage their health from the comfort of their own homes, reducing the number of clinical visits (2)., It is estimated that more than 7.1 million patients are utilising remote monitoring and connected medical devices as a way to better educate themselves about their disease (3).
Despite their clear benefits to patients, in addition to their ability to generate new datasets, the use of mHealth and other digital technologies in clinical trials has been limited to a relatively small number of pilots due to a lack of framework for the planning and execution of these trials.
Navigating the complexities of digital trials
To successfully operationalise digital trials, careful consideration during clinical trial design should be focused on three main areas: patients, devices and data.
One of the leading challenges when implementing these devices is the patient’s inability or inconvenience in using the digital technology. To ensure success of digital trials, it is critical that devices and sensors can collect data that is clinically meaningful with minimal impact on patients as they go about their daily lives.
Apps and devices should be designed with the user experience in mind, and should add value to the patient experience, while part of the study. A “bring your own device” (BYOD) model is ideal, so that patients do not have to deal with multiple mobile devices.
To seamlessly incorporate digital technologies into clinical trials, device selection should be made with study objectives, trial design and patient population in mind from the start.
Both medical devices and other grade technologies can play a role in digital studies, as long as there is sufficient evidence to support the use in that specific patient population, since a device that works well in one population may not transfer well to another.
From a regulatory perspective, the device needs to be able to capture and transfer the required data in accordance with local privacy and security regulations. These aspects will be key when presenting the CSR to regulators.
When selecting a digital platform, the ability to analyse high-frequency data is important. Additionally, to generate meaningful insights, data scientists who are skilled experts in advanced analytics are needed to generate meaningful endpoints from the high volume of data coming from devices and sensors.
A recent Clinical Trials Transformation Initiative recommended that it may be prudent to carry out a short feasibility study prior to implementation of the technology, especially in larger studies, to allow for the de-risking of large trials (2).
Seek guidance to ensure success
To run a successful digital trial, a complete end-to-end solution is required. Carefully selected technology, combined with the right trial design and operational excellence, will increase the likelihood of success. ICON is an experienced partner who partner with Intel on their Intel® Pharma Analytics Platform, an edge-to-cloud AI digital platform. Together they can help you navigate these nuances to ensure the success of your digital trial.