Virtual Clinical Trials (VCTs)

Digital, decentralized, virtual, global clinical trials are the future. Digital transformation of clinical trials will decrease cost, redundancy and improve efficiency.

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Introduction

Virtual Clinical Trials (VCTs) are an effective alternative to traditional clinical trials in that; they are:
  • Digital-first
  • Virtual Care Continuum
  • Healthcare IoT
  • eConsent
  • Decentralized
  • Global
  • Direct-to-Consumer
 

Figure 1: Virtual Clinical Trials: An Overview

 
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Traditional Clinical Trials - An expanding crisis

 
Traditional Clinical trials are in crisis due to a multitude of factors as discussed below:
  • Increasing Cost
  • Prolonged Time to completion
  • Decreased Accessibility
  • Reduced Diversity
  • Geographically restricted

Cost

  • According to a report presented to the U.S. Department of Health and Human Services, clinical Trials cost:[1]

Table 1: The average cost of clinical trials per phase/turn

Phase
Average costs (in $ Millions)
Range (in $ Millions)
1
4
2-6
2
13
10-16
3
20
12-28
4
20
5-35

Time

  • The average clinical trial lasts for 7.5 years. [2]
  • If included the duration of registration with the FDA, it takes about 10-15 years. [3]
  • Out of all the trials, only 14% of them are being successful. [4]
  • The average number of clinical trials conducted per year are: [4]
 

Table 2: The average number of the clinical trials conducted per annum, according to each phase

Phase
Average no. of trials per year
1
1.7
2
2.0
3
2.8
4
3.2

Accessibility & Recruitment

  • The average recruitment rate of participants is 0.5% per month. [5]
  • The average dropout rate of research volunteers is about 20%. [6]
  • 11% of research sites fail to enroll even a single patient. [7]
  • Many sites in the US conducting trials shut them down because of a lack of enrollment resources. [8]
  • 45% of first-time investigators quit the field after their first clinical trial. [9]
  • Patients who have just begun their initial cancer treatment are less inclined to volunteer for cancer research. [10]
  • In 2008, US government-sponsored clinical trial sites screened an average of 28 participants and enrolled 21 people only. [8]

Diversity

  • The diversity of clinical trials conducted in the US is limited to White Males.
  • White Americans represent the majority (82.9%) of participants in trials, while they make up 61.6% of the total US population. [11][12]
  • African Americans make up to 12% of the US population, but they only make up 5% of clinical trial participants.
  • Hispanics make up 16% of the population, they make up only 1% of clinical trial participants. [13]
  • While in underdeveloped countries, enough resources are not available to ensure the conductance of trials or availability of participants on their own.
  • The median female enrollment in government-funded US clinical trials was 46.7%. [14]
 

Table 3: Median female enrollment in each phase of clinical trials conducted by US-government

Phases of Clinical Trials
Median female enrollment
Phase 1
42.9%
Phase 1/2 to Phase 2
44.8%
Phase 2/3 to Phase 3
51.7%
Phase 4
51.1%

Site-based

  • From 2010 to January 12, 2022, the number of registered clinical studies has increased from 82,861 to 399,549 [15]
    • but the available sites to conduct trials remain low.
  • Sites carry a significant burden regarding [1]
    • Protocol training
    • Building Awareness
    • Screening and Selection
    • Patient Education and Informed Consent
    • Medication distribution and monitoring
    • Reporting outcomes
    • Tracking safety and adverse events
    • Case report forms and Data capture

‌Benefits and Attributes of Virtual Clinical Trials

Global

  • Can operate in multiple countries, states, continents, and across multiple time zones.

Digital

  • VCTs are digital-first
    • Mobile Health (mHealth)
    • Use new forms of data from the healthcare internet of things (IoT)
  • By the virtue of being digital, VCTs are
    • Global (transverse borders)
    • Universal (accommodates diversity)
    • Site-less (from clinical sites to virtual sites)
    • Able to grow value proposition across research
  • Real-time
    • Can accommodate real-time data collection
    • Can accommodate real-time data analysis
  • Accommodate existing and emerging technologies
    • Virtual/Augment (Mixed) Reality Application
    • Wireless standards like 5G, wi-fi 6

Virtual Care Continuum

  • Virtual Care or telehealth is at the centre of VCTs
  • This includes but is not limited to :
    • Virtual clinical trial visits
    • Virtual physician visits
    • Virtual nursing visits
    • Virtual allied health visits
      • Therapies: Physical, occupational & speech
      • Cognitive evaluations and therapies
  • Remote patient monitoring
    • Health IoT
  • Mobile Health (mHealth) Applications

Decentralized

  • Global recruitment
  • Better trial to participant matching
  • Improved recruitment
    • Increased participation
    • Increased diversity of participants
    • Detect and explain phenotypic variance physiologically and pathologically
  • Geographically Redistributed
    • Removed physical location barriers
    • Imaging sourced locally, interpreted centrally
    • Diagnostics sourced locally, interpreted centrally
  • Removed language barriers
    • The trial can be offered with a global participation
    • Locally sources clinical staff with specific sub-specialty requirements
  • Mitigates the dependency on an intermediary e.g
    • Human intervention generated data (mobile phlebotomist) is shifted to all patient-generated collected data via app/device.

Direct to Consumer (DTC)

  • Direct recruitment of patients
  • Removes intermediary hurdles in recruitment

Convergence of Emerging Technologies in VCTs

  • Virtual Clinical Trials enable the convergence of emerging technologies as
    • Healthcare IoT
    • Artificial Intelligence
    • Mixed Reality applications
    • New Therapy Targets

Healthcare Internet of Things (hIoT)

  • Use newer devices for remote patient monitoring
  • These newer devices also enable new endpoints as discussed below
  • These devices come in various form factors (Figure 1)
  • These devices can measure a multitude of physiological parameters (Figure 2)

Figure 2: Multitude of physiological parameters measured in Healthcare IoT (hIoT) ecosystem

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Figure 3: Different types of form factors in Healthcare IoT (hIoT)

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Digital Biomarkers

  • New Digital Endpoints
    • Health IoT generated
    • Patient-reported outcomes
  • Digital Endpoints converge with other imaging and genetic biomarkers to create new Digital biomarkers
  • They are specified by their novel methods of measurement and their insight into detecting diseases at an early level
  • Crucial in Neurological and psychiatry disorders to bring new forms of digital therapies
  • Once clinical validated can serve as a new form of measures [16]
  • We discuss biomarkers in the chapter
  • We discuss therapeutics in the chapter

Artificial Intelligence

  • With the increasing amount of data, AI will be necessitated to provide real-time intelligence
  • AI can help in VCTs in the following ways:
    • Trial Design-Unstructured data from earlier experiments will be interpreted.
    • Trial start-up-Patient information, databases, and lab data are used to match patients with trials.
    • Trial conduct-Validate medicine consumptions, track missed appointments and provide non-adherence notifications.
    • Study closeouts-Improved insights by filling standard data. [17]

Mixed Reality

  • Augmented Reality (AR) is bringing the virtual world into the physical world with cameras, lidar sensors, and eventually holograms.
  • While Virtual Reality (VR) is transporting physical presence into a virtual environment.
  • Mixed Reality (MR) is a combination of Augmented and Virtual reality, acting in concert to bridge the gap between them. [18]
  • New forms of Data collection can be enabled by Mixed reality; e.g.
    • Dementia risk assessment [19]
  • New forms of therapies can be enabled via Mixed reality, and now FDA approved e.g.
    • Acute and chronic pain management [20]
  • MR also provides new forms of immersive education
    • Neurology education is evolving as well with systems like Virtual reality-based neurological examination teaching tool (VRNET) are being developed and tested. [21]
    • Medical education in the metaverse needs a coalition of medical schools and professional societies to create an authentic, trustworthy source of modern medical education and patient education.
  • This trend will likely continue with further expansion of virtual care as technologies like wearables, augmented intelligence become increasingly part of the social fabric.

Patient Journey in Digital Clinical Trials

  • Digital transformation decrease latency in trial operations
  • The whole process can be digitized as discussed shown in Figure 4
 

Figure 4: The patient journey in Clinical Trials

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Examples of Recent Virtual Clinical Trials

Apple watch and Afib study

  • Apple watch monitors functional cardiovascular status using separate and integrated sensory outputs.
  • It successfully records:
    • Activity and steps
    • Distance and flights climbed
    • Heart rate, rhythm, and heart rate recovery
    • Photoplethysmography (PPG) outputs to measure volumetric variations of blood circulation
    • Oxygen consumption (V02) during various activities
  • The purpose of the Afib research was to see if the Apple Heart Study Watch app could detect arrhythmias like atrial fibrillation.
  • The survey comprised 419,093 people over the age of 22 who had an Apple Watch Series 1 or later with OS version 4.0 coupled with an iPhone 5S or later. [22]
  • The study design was set to be an interventional, prospective, unmasked, single-arm, screening trial.
  • The following endpoints were identified: [22]
    • 0.52 per cent of users had an irregular pulse (low flow). These individuals were given an ECG patch to wear for seven days, and 34 per cent of them were eventually diagnosed with AF.
    • The Positive Predictive Value for Notification was 0.84. (84% of notifications also had an ECG showing AF). Only 57% of individuals who got notices contacted their provider within 90 days.
    • Furthermore, irregular pulse alerts were more common in persons over the age of 65 (3.2%) and in men (0.7% in men vs 0.26% in women).
  • The apple watch uses photoplethysmography (PPG) which measures changes in blood flow which suggest irregular rhythms. [23]

mSToPS Study

Johnson & Johnson (J & J) conducted the trial mSToPS (mHealth Screening To Prevent Stroke) using the self-applied electrocardiogram (ECG) patch in July 2018 which showed that: [24]
  • A wearable patch can improve AFib identification in asymptomatic patients.
  • AFib affects 30 million individuals in the United States.
  • Up to 30% of AFib instances go undiagnosed until they cause life-threatening consequences.
  • AFib increases the risk of stroke by 5 times.
  • In the United States, a stroke occurs every 40 seconds.
  • While no significant difference was found in AFib related emergency visits and hospitalization.

Apple watch and SHAKE’ABLES

  • SHAKE’ABLES is the ongoing research trial using an Apple watch to track and record the symptoms of parkinsonism.
  • According to scientists, it’s better at detecting tremors and shakes. [25]

FDA and Digital Therapeutics

  • FDA is pushing the Digital Health Center of Excellence forward
    • Proposed multiple guidance documents
      • Good Machine Learning Practice for Medical Device Development: Guiding Principles
      • Artificial Intelligence and Machine Learning in Software as a Medical Device
  • The Food and Drug Administration (FDA) has initiated certification programs for the development of tools that can analyze Digital Health Technologies (DHTs) before their use in VCTs. [26]
    • DHT developers can also submit ideas to several Drug Development Tools (DDT) Qualification Programs.
    • Innovative Science and Technology Approach for New Drugs (ISTAND) Pilot Program for DHTs is one example of such a program.
  • The FDA has also issued a comprehensive set of suggestions for sponsors, investigators, and training guidelines to reduce the likelihood of digital technology troubleshooting.
  • More Recently:
    • FDA is embracing digital health technologies for remote data acquisition
    • Release draft guidance for Industry, Investigators, and Other Stakeholders
    • Released in December 2022 and accepted comments till 3/22/2022 [17]
    • To access draft guidance and place your comment. Follow the link
  • The following points were focused on in these guidelines
    • Availability of appropriate and reliable Digital Health Technology (DHT) to the trial participants.
    • The educational status, native language, age and technical aptitude should be taken into consideration to enable efficient use of DHT.
    • A submission document containing all the details of DHT should be provided by the sponsor to the agency beforehand for smooth implementation.
    • DHT should be “fit-for-purpose’’ and checked by examination to verify the validity of DHT.
    • Sponsors and agencies should constantly monitor the data and appropriate analysis methods should be applied.
  • The ways proving that FDA Guidance will be useful right away are:
    • It enlists all essential specifications about the registration and application of DHTs.
    • It provides detailed scenarios for a better understanding of the use of DHTs, ensuring good matching of DHTs with trials requirements.
    • It stresses the importance of informed consent, as it is often neglected in digital research.
    • It encompasses the need for cybersecurity for participants’ data and details and guides clinicians as well as sponsors in this perspective.
    • It ensures the implication of a digital framework in which the risks are outweighed by its benefits to favour innovation.
  • Further considerations to strengthen the future of digital research: [17][27]
    • Further details and complete understandings of risks are necessary before implementing DHTs to avoid serious adverse effects.
    • The new analysis methods should go through a total set of algorithms to ensure their resilience, bias, and reproducibility.
    • Only those software must be mandated who provide a set of Bill of Materials for clinical studies registry.
    • Protection strategies should be laid down to tackle cybersecurity/digital harms.
    • Measures should be taken to also include the unprivileged population; the persons who are unfamiliar with the use of digital devices as well as those with low socio-economic backgrounds.
    • Binding guidance for pharmaceutical companies and innovative stakeholders should also be presented to encourage smooth implementation.
    • Traditional site requirements should be adjusted. and regulatory meta-site (contact address, reference site) should also be established.
    • A patient-centric approach should be built that leverages telemedicine and mobile nursing to do routine evaluations.
    • Hospital systems should increase awareness and educate patients.
    • VCT should be targeted at the elderly population
 

Limitation of Virtual Clinical Trials

These factors may restrict the efficacy of VCT, if not taken under consideration.

Digital literacy

  • Most of the old aged people cannot communicate information through typing and other media on various digital platforms, as In England, a third of older persons have difficulties reading and comprehending basic health-related information. [10]
  • While to achieve global participation, many people in underdeveloped countries lack a clear understanding of the English Language and usage of digital devices.

Limited Therapeutics

  • Therapeutic benefits can be restricted in Phase 1 and Phase 2 drug studies when pharmacologic qualities and early side effects of the medicine have yet to be established in humans.

Virtual Clinical Trials in Neurology

Tremors - Apple watch and SHAKE’ABLES in Parkinson’s Disease

  • Every year, about 60,000 people in the United States are diagnosed with Parkinson's disease.
  • This condition affects an estimated 10 million people worldwide. [28]
  • Apple's movement disorder software algorithms are meant to provide data that is known to be associated with tremors.
  • The study, published in April 2020, assesses the feasibility of accelerometers in patients with Parkinsonism to quantify the tremors in extended and resting arm positions. [29]
  • 7 different types of Consumer Product Accelerometers (CPAs) were compared with Laboratory Graded Accelerometer (LGA).
  • The results determined how the CPAs can be optimally used to quantify the tremors in Clinical Trials as well as home measurements.
  • Moreover, resting arm position was declared better than extended arm position as it was associated with low variability in amplitudes.
  • From a clinical perspective, It’ll identify changes in tremor amplitude for therapeutic purposes, as pharmaceutical treatments may cause changes in amplitude rather than frequency.
  • It may be used to differentiate between Drug-Induced Parkinsonism and Parkinson’s Disease.

Apple watch (EpiWatch) and Epileptic Seizures

  • Epilepsy affects almost 50 million individuals worldwide, making it one of the most prevalent neurological illnesses. [30]
  • Researchers at Johns Hopkins University were researching to aid patients suffering from neurological disorders by gathering data on their seizures via their timepieces, especially their Apple Watches, called EpiWatch. [31]
  • The EpiWatch app detects movement, orientation, and heart rate using the watch's built-in sensors.
  • When a user suspects they are about to have a seizure, many people notice an "aura," a change in vision or smell before the occurrence that can activate the program.
  • The app captures a person's movements and pulse rate, which generally jumps, for ten minutes — before, during, and after a seizure that usually lasts for five minutes.
  • It asks the user to play a memory game during the seizure to measure their response and level of consciousness and to determine when the seizure will finish.
  • It next asks questions regarding the type of seizure, likely causes, and whether or not drugs were used.
The results published on December 20, 2021, revealed that:
Most of the seizures are not associated with triggers.
The seizures associated with triggers are most commonly associated with stress and insomnia/irregular sleep patterns.
Triggers were more frequent in patients taking 3 or more 3 anti-convulsants medication.
Relaxation techniques, such as yoga, may be beneficial in reducing seizure frequency and duration, especially for people who report stress and related triggers.
Other triggers may be mitigated by improving overall health hygiene through sleep and nutrition routines.
Epiwatch app was feasible to use by patients during and after seizures to get their triggers and further information recorded.
  • The results are encouraging for the use of EpiWatch in recording seizures and identifying their triggers.

Employing Digital Health in Cognitive Impairment Assessment

  • In December 2021, the results of the Einstein Aging Study were reported, in which variability in cognitive performance was compared in mildly cognitively impaired patients and cognitively unimpaired patients, establishing it as a digital biomarker. [32]
  • Cognitive competence was measured by smartphone devices assessing parameters of memory, executive function, attention, language and visuospatial orientation.
  • Results showed that the patients with cognitive impairment have lower mobility performance, as they were 0.88 sec slower than the cognitively unimpaired patients.
  • However, variability in mobile cognitive performance was found to be the potential indicator of MCI. Further mobility metrics should be identified to determine cognitive impairment.

Resources

Digital Medical Society
DiMe’s Library of Digital Endpoints
Clinical Trial Transformation Initiative

Further Reading

  • Center. (2021). Digital Health Center of Excellence. U.S. Food and Drug Administration. https://www.fda.gov/medical-devices/digital-health-center-excellence
  • Transforming Trials 2030 - CTTI. (2022, January 3). CTTI. https://ctti-clinicaltrials.org/who_we_are/transforming-trials-2030

Bibliography

  1. Examination of Clinical Trial Costs and Barriers for Drug Development. (2014). ASPE. https://aspe.hhs.gov/reports/examination-clinical-trial-costs-barriers-drug-development-0
  1. DiMasi, J. A., Hansen, R. W., & Grabowski, H. G. (2003). The price of innovation: new estimates of drug development costs. Journal of Health Economics22(2), 151–185. https://doi.org/10.1016/s0167-6296(02)00126-1
  1. Transforming Clinical Research in the United States. (2013). Retrieved January 28, 2022, from Google Books website: https://books.google.com.pk/books?hl=en&lr=&id=0TocNJRXypkC&oi=fnd&pg=PP2&dq=#v=onepage&q&f=false
  1. Wong, C. H., Siah, K. W., & Lo, A. W. (2019). Estimation of clinical trial success rates and related parameters. Biostatistics (Oxford, England)20(2), 273–286. https://doi.org/10.1093/biostatistics/kxx069
  1. Gkioni, E., Rius, R., Dodd, S., & Gamble, C. (2019). A systematic review describes models for recruitment prediction at the design stage of a clinical trial. Journal of Clinical Epidemiology115, 141–149. https://doi.org/10.1016/j.jclinepi.2019.07.002
  1. Bell, M. L., Kenward, M. G., Fairclough, D. L., & Horton, N. J. (2013). Differential dropout and bias in randomised controlled trials: when it matters and when it may not. BMJ346(jan21 1), e8668–e8668. https://doi.org/10.1136/bmj.e8668
  1. Kantor, E. (2015). 25+ useful clinical trial recruitment statistics for better results. Retrieved January 28, 2022, from Antidote.me website: https://www.antidote.me/blog/25-useful-clinical-trial-recruitment-statistics-for-better-results
  1. Getz, K. A., & Zuckerman, R. (2010). Today's global site landscape. Applied clinical trials19(6), 34.
  1. Califf, R. M., Filerman, G. L., Murray, R. K., & Rosenblatt, M. (2012). The Clinical Trials Enterprise in the United States: A Call for Disruptive Innovation. NAM Perspectives2(4). https://doi.org/10.31478/201204d
  1. Moorcraft, S. Y., Marriott, C., Peckitt, C., Cunningham, D., Chau, I., Starling, N., … Rao, S. (2016). Patients’ willingness to participate in clinical trials and their views on aspects of cancer research: results of a prospective patient survey. Trials17(1). https://doi.org/10.1186/s13063-015-1105-3
  1. Hamel, L. M., Penner, L. A., Albrecht, T. L., Heath, E., Gwede, C. K., & Eggly, S. (2016). Barriers to Clinical Trial Enrollment in Racial and Ethnic Minority Patients with Cancer. Cancer Control23(4), 327–337. https://doi.org/10.1177/107327481602300404
  1. Wikipedia Contributors. (2022, February 1). White Americans. Wikipedia; Wikimedia Foundation. https://en.wikipedia.org/wiki/White_Americans
  1. Washington. (2011). Dialogues on Diversifying Clinical Trials Successful Strategies for Engaging Women and Minorities in Clinical Trials. https://www.fda.gov/files/science%20&%20research/published/White-Paper-on-the-Dialogues-on-Diversifying-Clinical-Trials-Conference.pdf
  1. Steinberg, J. R., Turner, B. E., Weeks, B. T., Magnani, C. J., Wong, B. O., Rodriguez, F., Yee, L. M., & Cullen, M. R. (2021). Analysis of Female Enrollment and Participant Sex by Burden of Disease in US Clinical Trials Between 2000 and 2020. JAMA Network Open4(6), e2113749. https://doi.org/10.1001/jamanetworkopen.2021.13749
  1. Trends, Charts, and Maps - ClinicalTrials.gov. (2021). Clinicaltrials.gov. https://clinicaltrials.gov/ct2/resources/trends
  1. The emerging influence of digital biomarkers on healthcare | Rock Health. (2016, February). Rock Health | We’re Powering the Future of Healthcare. Rock Health Is a Seed and Early-Stage Venture Fund That Supports Startups Building the next Generation of Technologies Transforming Healthcare. https://rockhealth.com/insights/the-emerging-influence-of-digital-biomarkers-on-healthcare/
  1. Center. (2021). Digital Health Technologies for Remote Data Acquisition in Clinical In. U.S. Food and Drug Administration. https://www.fda.gov/regulatory-information/search-fda-guidance-documents/digital-health-technologies-remote-data-acquisition-clinical-investigations
  1. Nicola S;Stoicu-Tivadar L. (2018). Mixed Reality Supporting Modern Medical Education. Studies in Health Technology and Informatics255. https://pubmed.ncbi.nlm.nih.gov/30306945/
  1. Cabinio, M., Rossetto, F., Isernia, S., Saibene, F. L., Di Cesare, M., Borgnis, F., Pazzi, S., Migliazza, T., Alberoni, M., Blasi, V., & Baglio, F. (2020). The Use of a Virtual Reality Platform for the Assessment of the Memory Decline and the Hippocampal Neural Injury in Subjects with Mild Cognitive Impairment: The Validity of Smart Aging Serious Game (SASG). Journal of Clinical Medicine9(5), 1355. https://doi.org/10.3390/jcm9051355
  1. Ahmadpour, N., Randall, H., Choksi, H., Gao, A., Vaughan, C., & Poronnik, P. (2019). Virtual Reality interventions for acute and chronic pain management. The International Journal of Biochemistry & Cell Biology114, 105568. https://doi.org/10.1016/j.biocel.2019.105568
  1. Han, S. G., Kim, Y. D., Kong, T. Y., & Cho, J. (2021). Virtual reality-based neurological examination teaching tool(VRNET) versus standardized patient in teaching neurological examinations for the medical students: a randomized, single-blind study. BMC Medical Education21(1). https://doi.org/10.1186/s12909-021-02920-
  1. Turakhia, M. P., Desai, M., Hedlin, H., Rajmane, A., Talati, N., Ferris, T., Desai, S., Nag, D., Patel, M., Kowey, P., Rumsfeld, J. S., Russo, A. M., Hills, M. T., Granger, C. B., Mahaffey, K. W., & Perez, M. V. (2019). Rationale and design of a large-scale, app-based study to identify cardiac arrhythmias using a smartwatch: The Apple Heart Study. American heart journal207, 66–75. https://doi.org/10.1016/j.ahj.2018.09.002
  1. Tamura, T. (2019). Current progress of photoplethysmography and SPO2 for health monitoring. Biomedical Engineering Letters9(1), 21–36. https://doi.org/10.1007/s13534-019-00097-w
  1. Steinhubl, S. R., Waalen, J., Edwards, A. M., Ariniello, L. M., Mehta, R. R., Ebner, G. S., Carter, C., Baca-Motes, K., Felicione, E., Sarich, T., & Topol, E. J. (2018). Effect of a Home-Based Wearable Continuous ECG Monitoring Patch on Detection of Undiagnosed Atrial Fibrillation: The mSToPS Randomized Clinical Trial. JAMA320(2), 146–155. https://doi.org/10.1001/jama.2018.8102
  1. CNBC NEWS. The Apple Watch just got a lot better at tracking symptoms of Parkinson’s Disease-Christina Farr. Published online June 10, 2018. Accessed January 10, 2022. https://www.cnbc.com/2018/06/09/apple-watch-adds-tech-to-track-parkinsons-disease.html
  1. FDA Addresses the Role of Digital Health Technology in Clinical Trials. (2022). The National Law Review. https://www.natlawreview.com/article/fda-addresses-role-digital-health-technology-clinical-trials
  1. Unpacking the FDA’s New Guidance on Remote Data Acquisition - DCRI. (2022, January 11). DCRI. https://dcri.org/unpacking-the-fdas-new-guidance-on-remote-data-acquisition/
  1. Statistics. (2020). Parkinson’s Foundation. https://www.parkinson.org/Understanding-Parkinsons/Statistics#:~:text=Approximately%2060%2C000%20Americans%20are%20diagnosed,are%20diagnosed%20before%20age%2050.
  1. van Brummelen, E., Ziagkos, D., de Boon, W., Hart, E. P., Doll, R. J., Huttunen, T., Kolehmainen, P., & Groeneveld, G. J. (2020). Quantification of tremor using consumer product accelerometry is feasible in patients with essential tremor and Parkinson's disease: a comparative study. Journal of clinical movement disorders7, 4. https://doi.org/10.1186/s40734-020-00086-7
  1. World. (2019, June 20). Epilepsy. Who.int; World Health Organization: WHO. https://www.who.int/news-room/fact-sheets/detail/epilepsy
  1. Ge, A., Gutierrez, E. G., Wook Lee, S., Shah, S., Carmenate, Y., Collard, M., Crone, N. E., & Krauss, G. L. (2022). Seizure triggers identified postictally using a smartwatch reporting system. Epilepsy & behaviour: E&B126, 108472. https://doi.org/10.1016/j.yebeh.2021.108472
  1. Cerino, E. S., Katz, M. J., Wang, C., Qin, J., Gao, Q., Hyun, J., Hakun, J. G., Roque, N. A., Derby, C. A., Lipton, R. B., & Sliwinski, M. J. (2021). Variability in Cognitive Performance on Mobile Devices Is Sensitive to Mild Cognitive Impairment: Results From the Einstein Aging Study. Frontiers in Digital Health3. https://doi.org/10.3389/fdgth.2021.758031
Hidden

Potential Benefits of VCT

  • Gathering previously unobtainable, objective, "real-world" data from patients in their everyday lives.
  • A more diverse range of subjects and a more representative population
  • Lower expenses associated with conducting clinical trials - Reduced obstacles to participation
  1. https://www.baltimoresun.com/health/bs-hs-epilepsy-watch-study-20151122-story.html