Over the past few years, the decentralization of clinical trials has gained much attention. Unlike traditional clinical research, decentralized trials use different technologies (i.e., wearable medical devices) and approaches (i.e., telemedicine) to recruit and retain participants and minimize barriers to participation by utilizing a more patient-centric perspective.
Digital transformation has become necessary for patient engagement and recruitment. It is directly linked to the rising costs of launching a new drug and the overall length of clinical trials, making them time and cost-consuming.
However, there seems to be little adoption. Clinical trials are taking baby steps when it comes to embracing modernization due to lagging global standards, and this is the main issue that must be addressed as soon as possible.
Importance of Implementing Decentralized Clinical Trials Technologies
According to global data analysis research, the decentralized trial technologies (DLT), digital therapeutics, and much more must are opportunities to improve patient health.
A number of digital technologies can help the realization of the clinical trial management process, including:
Wearables and sensors — Participating in research can be expensive or even difficult for patients who live far from a study site or if they have scheduling or mobility issues. Wearables and sensors eliminate or minimize the need to visit the site. These devices can process higher volumes of patient data received through them. Additionally, they can improve protocols, recruitment and retention, and clinical study design.
Digital therapeutics — These are therapeutic interventions controlled by software programs that can prevent, manage, and treat a broad spectrum of physical, behavioural, and mental conditions. In the form of a smartphone app, they can serve patients as medication reminders and facilitate participant feedback collections in electronic clinical assessment.
Software as a medical device (SaMD) — This software is intended to analyze and display medical information about a patient and is not part of a hardware medical device. As such, it can be used in DCTs for screening, prescreening, clinical diagnosis, and more.
Artificial intelligence (AI)/ Machine learning (ML) — Artificial intelligence is the building or programming of machines that can function as if they were humans. In machine learning, computers are trained with data to perform a given task and produce accurate results. When it comes to clinical trials, both can predict recruitment and retention rates, which treatments might be most effective for certain patients, analyze and implement participant feedback, target patient populations more effectively, gather insights by filtering unstructured data from various patient records, and more.
However, clinical trial management teams must understand and negotiate numerous technical and ethical issues to incorporate these technologies into their processes and ask patients to trust them.
Are Patients and Clinicians Embracing Digitalization at the Same Pace?
Patients have long been reluctant to embrace digital technologies as part of clinical trials. They have been uncertain about the trustworthiness of these components and if they are used ethically. Fortunately, the situation is changing for the better. Consumer-oriented digital health products and services, such as wearable technologies, smartphone apps, and social media-based disease support groups, have started to change patients’ expectations of the healthcare industry.
A survey conducted by Deloitte in 2018 showed that 92% of 650 patients said the healthcare and life sciences industry should prioritize improving patient experiences (through innovative technologies), compared to 71% in 2017.
Wearable technologies demonstrate that patients are embracing digital technologies. This is what the numbers say:
According to statista.com, the number of connected wearables worldwide has risen from 325 million in 2016 to 722 million in 2019, and a billion devices are expected to be in use by 2022.
com also states that the Apple App Store offered almost 54,000 medical and healthcare apps in 2021.
Imaging and EMR data generated by a single patient in a year can amount to 80 megabytes, not including other health data from wearable devices.
Digital therapeutics, wearables, and other biosensors allow patients to take care of their wellness and health in a way they have never been able to do before. They offer benefits such as:
Convenience — Remote technologies enable patients to communicate with investigators at clinical sites, reducing or eliminating the need to travel there regularly.
More insights — Patients can access more data and use it to improve their overall health and wellness. This way, wearable tech helps them take a proactive approach to healthcare instead of a reactive one.
Patient engagement — Wearable tech encourages people to monitor their health more closely. The device’s real-time data allows users to stay on top of their health condition.
Trackable awareness — With user-friendly dashboards, digital tools give insight into how patients perform with measurements and units.
Accurate diagnosing — Doctors can gain a deeper understanding of a patient’s issues by monitoring data from wearable devices over time. This data allows them to make more accurate diagnoses than they might have made without it.
Despite all the advantages of using digital technologies and DCTs, it will take time until patients and clinicians fully accept them. Scientists and clinicians must evaluate which healthcare technologies should be trusted and integrated. However, to address and eliminate these uncertainties in the application and technology, clinical professionals and patients must work together to develop global industry standards.
Global Technical Standards as Guidance
One might question the importance of global technical standards and their role. They ensure seamless global connectivity, and once established, there would be no doubt whether that technology is validated, whether it will protect a patient’s privacy, and whether it will be compatible with clinical trial databases. However, it will take some time until it becomes a reality.
Therefore some clinicians turn to policy and regulatory bodies for guidance regarding integrating digital health tools into clinical trials. Others turn to global standards development organizations (SDOs) that bring together experts to develop solutions cooperatively.
Standards are essential for addressing many ethical concerns regarding patient data governance, securing data from the device to the cloud, and protecting patient privacy. All stakeholders – clinical professionals, technologists, contract research organizations, and patients – must be involved in building consensus and developing global standards.
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