The evolvement of digital technologies in the past years has been transformative in the field of clinical trials in therapeutic areas, being CNS (Central Nervous System) in highlight. The introduction of digital endpoints has transformed how, for example, neurodegenerative symptoms are quantified and tracked and contributed to the growth of CNS decentralized clinical trials (DCTs). Within CNS DCTs, remote patient monitoring (via sensors or trackers) is increasingly common.
The total number of DCTs has increased more than fivefold worldwide, from 250 trials in 2012 to 1,291 in 2021. According to GlobalData’s Clinical Trial Database, the most researched therapeutic area for DCTs is CNS (26% of trials), followed by metabolic disorders (11%).
The Challenges faced in CNS Clinical Trials
Neurodegenerative diseases like Alzheimer’s disease (AD), Huntington’s disease (HD), and Parkinson’s disease (PD), cause progressive degeneration of neurons in the central or peripheral nervous systems, leading to functional decline that considerably affects a patient’s activities of daily living (ADL) and quality of life.
The challenges traversed in CNS clinical research include the lack of sensitivity in standard assessments (questionnaires and interviews), cognitive testing, and mobility assessments, which limit their use as outcome measurements in clinical trials. For example, Gupta et al. (2023) highlights the lack of objective, sensitive, and accessible outcome measures for amyotrophic lateral sclerosis (ALS) clinical research. Hanke et al. (2023) indicated that outcome measures for AD clinical trials lack the ability to detect gradual changes.
CNS DCTs Opportunities
Digital endpoints for neurodegenerative diseases
Digital endpoints in clinical trials are measured with the use of remote monitoring technologies (RMTs) either passively (e.g., gait measures) or interactively (e.g., surveys). In contrast with traditional assessments, RMTs are unobtrusive, objective, and able to collect real-world data continuously. Subtle changes in instrumental activities of daily living (IADLs) can predict disease progression, and while current cognitive assessments may not pick up on them, RMTs can potentially measure these changes.
In their neurodegenerative disease clinical trials study, Brem et al. (2023) concluded that using digital endpoints can significantly change the assessment and tracking of neurodegenerative symptoms. Digital endpoints pave the way for:
- objective, immediate, and continuous measurement
- a reduction in face-to-face visits
- improved accessibility for underserved populations
- improved stratification
- personalized interventions
- artificial intelligence (AI)-supported decisions.
Study findings from Hantke et al. (2023) suggest that continuous, home-based digital biomarkers (measures of daily function and cognition assessed unobtrusively) may serve as behavioral proxies and enhance trial efficiency.
Remote assessments of cognition, speech, and motor functioning
A recent research of a mobile app study protocol for the remote assessment of cognition, speech/language, and motor functioning in frontotemporal dementia (FTD) found it to be feasible and acceptable for remote clinical research. The smartphone-based platform for remote, self-administered data gathering allows DCTs and enhance participant access to research.
Remote monitoring of CNS biomarkers
Recent studies on mild cognitive impairment (MCI), Lawson et al. (2023) found that digital tech is an objective method of capturing IADL-related behaviors. A literature review by ZhuParris et al. (2023) found that machine learning (ML) techniques can process mobile health (mHealth) data coming from continuously monitoring patients’ symptoms to derive precise biomarkers of disease activity.
Functional independence through habitual physical activity
Mc Ardle et al. (2023) studied the use of digital technology in quantifying habitual physical activity (HPA) in people with dementia and MCI. Digital technologies like accelerometers can measure HPA objectively, including nuanced measures relating to volume, intensity, pattern, and variability. Compared to the control group, participants with dementia had lower volumes, intensities, and variability with different daytime patterns of HPA, while people with MCI demonstrated different patterns of HPA.
Monitoring disease progression of ALS
Studies on the monitoring of the disease progression of ALS, Gupta et al. (2023) demonstrated that at-home wearables and ML not only capture ALS disease progression but also outperform the gold standard (clinician-administered questionnaire ALS Functional Rating Scale-Revised). The researchers concluded that at-home wearables and ML provide an ecologically valid and scalable measure for ALS trials.
Multiple sclerosis DCTs
Garjani et al. (2023) studied DCTs in multiple sclerosis (MS) research and concluded that DCTs can potentially enhance the statistical power of randomized controlled trials (RCTs) while producing more generalizable and less biased results. Further, Garjani et al. (2023) indicated that MS DCTs can run more efficiently than conventional RCTs due to the recruitment of larger samples, flexible and frequent assessments of outcome measures, and gathering real-world data.
Participant Satisfaction
An international research on patient perspectives on digital technology for MND sought to capture participants’ attitudes toward remote monitoring. Most participants had a positive attitude toward digital technology in care and clinical trial settings, indicating that they would be happy to self-monitor from home (69%) and be remotely monitored by a multidisciplinary care team (75%). More than half (65%) reported being willing to participate remotely in clinical trials.
Beswick et al. (2022) conducted a review to assess the potential of technology to evaluate motor function and disease progression in patients with MND for clinical research. They found it to be a promising area of MND research and that feedback from participants on using tech was generally positive.
Working towards a new PD clinical research model, Jensen-Roberts (2022) conducted a decentralized, remote natural history study to assess participant satisfaction and interest in future DCTs. Most participants (97%) were satisfied with the overall study.
Opportunities for Enhancement
Patient-centric research
Patient-centric measures and at-home patient monitoring allows the measurement of novel endpoints for clinical trials. Holdom et al. (2023) explored wrist-based actigraphy, a non-invasive technique to assess activity and rest over time, to measure functional decline and disease progression of motor neuron disease (MND). The study revealed that wrist-based actigraphy outcomes are more variable than those from the hip. It recommended that if wrist-worn devices are chosen for at-home monitoring of patients, outcomes, and analysis should be carefully designed.
Standardization and validation
On digital endpoints for assessing IADLs in MCI, Lawson et al. (2023) found that measuring multiple IADL-related digital endpoints can offer more value than measuring discrete IADL outcomes alone. The authors recommend developing core metrics relevant to IADL-related behaviors aligned with clinically meaningful outcomes to facilitate standardization and validation of digital technologies in clinical research.
How MILO DCT Can Improve Your Experience in Clinical Trials
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MILO provides tailored services such as, a comprehensive app with multiple functions that facilitate both patient and doctors lives; televisits; a website with highly informative content, all integrated. MILO’s team purpose is to bring feasible, quality, and user-friendly technology to the healthcare landscape and enhance your experience in Clinical Trials.
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Conclusion
Innovation in digital technologies and integration of digital endpoints in clinical trial design have helped to address past clinical research challenges, including the lack of objective, sensitive, and feasible outcome measures. Digital endpoints have revolutionized how neurodegenerative symptoms are quantified and tracked, contributing to the growth of CNS DCTs. As CNS disorders have unique challenges, researchers continue to explore how digital tech can be applied to improve trial efficiency.