How technology is reshaping clinical trials and the future of medicine

The COVID-19 pandemic has accelerated the need and application of digital technologies to help deliver health services, predict and track the spread of the virus, provide researchers with access to real-world evidence, and facilitate vaccine development. Today, many of these tools, along with other revolutionary technologies, are being applied to clinical trials, which are the cornerstone of the development and evaluation of new medical treatments, drugs and interventions. Digital applications, sensor-integrated devices, wearable technologies, and data acquisition platforms enable researchers to collect and analyze real-world data from clinical trial participants in real time. This transforms the way clinical trials and medical research are conducted, significantly improving their efficiency, accuracy and impact on healthcare outcomes.

Digital innovation also improves the selection and recruitment of clinical trial participants, makes clinical research more inclusive, reduces delays, facilitates remote participation, and enables new ways to collect and share data. These improvements in the clinical trial process can lead to advances in treatments and therapies, new, safer and more effective drugs, and better patient outcomes.

The benefits of digital health technologies in clinical trials

Traditionally, data were collected from clinical trial participants in a clinical setting, in handwritten or computer logs and at scheduled intervals. Digital devices and wearable sensors have revolutionized researchers’ ability to measure, collect and store biological, behavioral and physiological information, leading researchers to coin the term digital biomarkers. These digital biomarkers, which provide essential data to researchers, play an important role in determining the health status of each patient and in drug development.

Digital health technologies (DHT), such as wearable devices, are beneficial in clinical research due to their ability to collect more meaningful, objective, continuous, and real-time data that reflects participants’ real-world experiences. While traditional clinical trials were conducted in a single physical environment, DHTs have enabled decentralized clinical trials (DCT), in which some or all of the activities take place in other locations, including the participant’s home, in a laboratory local or in a health establishment. During DCTs, sensors capture information during a patient’s routine, providing researchers with insight into the effectiveness and safety of the treatment in daily life. Better collection of real-world data means more accurate measurements and a complete picture of a patient’s overall health. DHTs also strengthen the inclusiveness of clinical research, ensuring that underserved populations can participate in and benefit from medical advances. Additionally, they reduce reliance on patient self-reported information and capture variations and trends that may have been missed in scheduled measurements.

DHTs can be used to measure many biomarkers and conditions. For example, ambulatory blood pressure monitoring provides data to determine the effects of a new investigational drug. An actigraph, which measures an individual’s movement (activity), rest and sleep, helps monitor sleep patterns and facilitates the development of treatments for sleep disorders. Polysomnograms are used in sleep studies to measure brain activity signals to diagnose and monitor sleep disorders such as insomnia, narcolepsy cataplexy syndrome, obstructive sleep apnea, sleep disorders circadian rhythm sleep and parasomnias such as sleepwalking, night terrors and even sleep-related terrors. eating disorders.

DHTs offer many potential benefits in the innovation and development of medical products, including drugs. DHTs provide comprehensive data and information on symptom progression to improve clinical care and scientific understanding of various diseases such as Parkinson’s disease, dementia, Alzheimer’s disease, epilepsy and more. other nervous system disorders. These technologies provide invaluable assistance by facilitating early detection, monitoring disease progression and facilitating accurate diagnosis, thereby enabling rapid intervention and management of these complex neurological conditions.

Using artificial intelligence (AI) and machine learning (ML), statistical analysts can classify, sort, organize and store the massive amounts of data collected through DHTs, quickly and at scale. AI and ML help analysts mine huge volumes of data to identify patterns and predict outcomes. For example, statistical analysts can create models that interpret and evaluate data collected from DHTs to identify significant differences between an investigational new drug and an active placebo in terms of safety and effectiveness. Their unique ideas and predictions will lead to advances in medical research and therapies that are safer, more effective and evidence-based.

Indeed, researchers and data analysts face several challenges and limitations, such as data privacy issues, regulatory hurdles, legislative issues, communications compatibility, technological barriers, and disparities in access to digital technology. Despite the challenges, researchers see opportunities in DHTs to “improve healthcare delivery, remote patient monitoring, increase access to medical services, and reduce healthcare costs.” They also offer the potential to improve patient outcomes by enabling early detection and intervention for medical problems.

Medical advances and better patient outcomes

Advances in DHTs offer promising benefits in the development of drugs and treatments for undiagnosed diseases, including neurological disorders, which are often considered underfunded and understudied in the medical community. The use of DHT allows for better data collection on conditions such as epilepsy, multiple sclerosis, Alzheimer’s disease and Parkinson’s disease. Patients suffering from these and other neurological disorders face high healthcare costs and high disability rates worldwide. According to a 2023 study, “the use of digital tools, such as connected sensors, promises to make research more patient-centered and move clinical trials beyond simple ‘snapshots’ of disease status.” disease toward a more continuous measurement of these and other chronic disorders. Accumulating better real-world data using DHTs can “facilitate new study designs, improve the efficiency of clinical trials, and help address many of the challenges facing neurological research.”

In one analysis, researchers gathered previously inaccessible data such as “repetitive cognitive testing, speech characterization, or swallowing monitoring” via DHT. The hope is that this data can lead to new medical advances and treatments for these debilitating disorders. Japanese company Takeda is working to bring digital monitoring technologies to Parkinson’s patients. Takeda has created an integrated care solution called Care for One, in which Parkinson’s patients can use an app on their Apple Watch 1 to continuously monitor symptoms, capture movement and collect data. Patients can also enter additional medical information into the app and send complete data directly to their doctor’s computer.

The future of digital technology in healthcare

There is evidence that the use of DHTs will continue to expand globally. Forecast trends show that the digital health market is expected to grow at a compound annual growth rate (CAGR) of 18.6% between 2023 and 2030. DHTs make real-world data collection more accessible and efficient for health researchers. medicine. Technologies improve clinical trial recruitment, diversify participant demographics, improve retention and compliance, reduce costs, and improve data collection, management, quality, and analysis. Digital technologies also help analyze patient data, identify patterns, predict outcomes, and advance new perspectives in personalized medicine.

This evolution is essential to address the complexities of precision medicine, drug development and modern healthcare delivery. AI, ML and other emerging technologies will continue to accelerate the digitalization of clinical trials, leading to an increased data-driven approach to study design and implementation. As clinical trials and healthcare become increasingly digitalized and patient-centered, they will blend seamlessly to create a holistic journey that maximizes the benefits of medical advancement for the medical industry and patients.