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Jiang - Key Trends in Digital Health and the Future of Clinical Trials in the US

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preface_schema: ‘1.0’ title: ‘Key Trends in Digital Health and the Future of Clinical Trials in the US’ source_type: ‘Academic’ publisher: ‘Yale School of Public Health’ publishing_date: ‘2021’ authors: [‘Jeannette Jiang’, ‘Maria Ciarleglio’, ‘Frederick Gertz’] available_at: ‘Unknown’ keywords: [‘from digital health studies from 2016-2020 … 31 figure 5. number of studies by therapeutic area of focus from 2006-2020 … 33 figure 6. digital health applications in clinical trials … 34 ---’] abstract: ‘With the increasing burden of chronic diseases on the global population, many stakeholders see digital health technologies and devices as potential solutions to improve patient self-management of their disease and offer novel treatment methods. Digital health holds great potential in improving and enhancing the traditional clinical trial by increasing patient recruitment and retention and introducing novel assessment and collection methods that shift clinical trials from the physical site to the patients’ home.‘

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Key Trends in Digital Health and the Future of Clinical Trials in the US Jeannette Jiang Committee Chair: Maria Ciarleglio, PhD Committee Member: Frederick Gertz, PhD A Thesis Submitted in Candidacy for the Degree of Master of Public Health Yale School of Public Health Chronic Disease Epidemiology 2021

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lio, PhD Committee Member: Frederick Gertz, PhD A Thesis Submitted in Candidacy for the Degree of Master of Public Health Yale School of Public Health Chronic Disease Epidemiology 2021

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Abstract With the increasing burden of chronic diseases on the global population, many stakeholders see digital health technologies and devices as potential solutions to improve patient self-management of their disease and offer novel treatment methods. Digital health solutions including mobile apps, web-based programs, texting, and connected devices have been applied to a wide variety of diseases. In recent years, interest in digital health technologies has exploded with almost 200 digital health related articles published in PubMed in 2019 alone. In particular, digital health holds great potential in improving and enhancing the traditional clinical trial by increasing patient recruitment and retention and introducing novel assessment and collection methods that shift clinical trials from the physical site to the patients’ home. Digital health is poised to fundamentally shift how clinical trials are conducted. However, serious challenges from potential regulatory restrictions and data privacy issues will need to be addressed before patients, physicians, and other stakeholders can fully realize the benefits of digital health.

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otential regulatory restrictions and data privacy issues will need to be addressed before patients, physicians, and other stakeholders can fully realize the benefits of digital health.

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Acknowledgments This thesis would not have been possible without the continued support of many individuals and I am extremely thankful for their guidance. I am extraordinary grateful for the assistance I received from Dr. Maria Ciarleglio who provided invaluable insight and expertise. I am deeply thankful for Chelsea Williams who provide me with her wisdom and persistent encouragement. I am fully indebted to her and without her support this thesis would not have been possible. Lastly, I would like to express my sincere gratitude to Frederick Gertz for his infinite knowledge and broad perspective and Julie Syu for her assistance in the analysis.

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Table of Contents List of Figures … 5 List of Tables … 6 Acronyms … 7 Introduction … 8 Methodology … 13 Literature Review … 14 Digital Health and Clinical Trials … 14 Types of Digital Health in Clinical Trials … 16 Mobile Apps …

… 14 Types of Digital Health in Clinical Trials … 16 Mobile Apps … 16 Smartphones … 18 Web-Based … 19 Remote Monitoring … 20 Short Message Service (SMS) … 21 Telehealth … 22 Wearables … 22 Connected Devices … 23 Other … 24 Prominent Therapeutic Areas with Digital Health … 25 Diabetes and Wellness … 25 Cardiovascular …

s and Wellness … 25 Cardiovascular … 26 Mental Health Disorders … 27 Discussion … 27 The Increasing Presence of Digital Health … 27 The Potential Future of Digital Health in Clinical Trials … 34 The Evolving Regulations Around Digital Health … 38 Conclusion … 44 Limitations … 45 Future Directions … 45 References… 46

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… 45 References… 46

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List of Figures Figure 1. Digital Health Maturity with Examples … 10 Figure 2. Methodology… 14 Figure 3. Number of Studies by Digital Health Device … 28 Figure 4. Top Keywords from Digital Health Studies from 2016-2020 … 31 Figure 5. Number of Studies by Therapeutic Area of Focus from 2006-2020 … 33 Figure 6. Digital Health Applications in Clinical Trials … 34

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Acronyms Acronym Definition ADHD Attention-Deficit/Hyperactivity Disorder AI/ML Artificial Intelligence/Machine Learning CBT Cognitive Based Therapy CDC Centers of Disease Control CIED Cardiac Implantable Electronic Devices CIED Cardiac Implantable Electronic Device CMS Centers for Medicare & Medicaid Services DHCoE Digital Health Center of Excellence DTx Digital Therapeutics EHR Electronic Health Record FDA Food and Drug Administration NLP Natural Learning Processing PrEP Pre-Exposure Prophylaxis PRO Patient Reported Outcomes SaMD Software as Medical Device SMS Short Message Service

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d FDA Food and Drug Administration NLP Natural Learning Processing PrEP Pre-Exposure Prophylaxis PRO Patient Reported Outcomes SaMD Software as Medical Device SMS Short Message Service

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Introduction Addressing chronic disease is one of the greatest public health challenges of the modern era. According to the Centers for Disease Control, 6 in 10 US adults suffer from a chronic disease and 4 in 10 US adults have two or more chronic conditions (Centers for Disease Control and Prevention [CDC], 2021). There is an increasing prevalence of chronic conditions and comorbidities with more than half of older adults having three or more chronic conditions, such as diabetes, cardiovascular disease, cancer, arthritis, mental illness, or high blood pressure (American Geriatrics Society, 2012). By 2030, an estimated 170 million Americans will have a chronic disease, a staggering increase from 118 million individuals in 1995 (Newman, 2020). There is greater healthcare cost and service utilization for patients with chronic disease, where those with more conditions have higher associated costs (CDC, 2021). Americans with five or more chronic conditions require 14 times more spending than those with no conditions and represent 41% of total healthcare costs despite only representing 12% of the population (Buttorff et al., 2017). Chronic diseases can have a serious impact on quality of life and lead to future disability, thus posing an even greater burden on health services. Many chronic diseases are caused by identifiable risk factors and behaviors. Avoiding these key factors and maintaining a healthy lifestyle can greatly reduce the likelihood of getting a chronic disease. Health literacy and education can play a critical role in informing patients of regularly exercising, eating healthy, getting properly screened, and avoiding risky behaviors (Poureslami et al., 2017). For those already suffering from a chronic condition, taking their medication is critical to maintai

eating healthy, getting properly screened, and avoiding risky behaviors (Poureslami et al., 2017). For those already suffering from a chronic condition, taking their medication is critical to maintaining their health and preventing future disability. However, medication adherence is a serious problem and it is estimated that patient may be nonadherent to their medications 50% of the time (Brown et al., 2016).

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Digital health has been seen as a device or tool to facilitate aspects of healthcare from screening, diagnostics, preventative care, and treatment. These devices may serve to support existing health interventions or act independently to improve health outcomes. Digital health can be utilized in many forms but by enabling and encouraging patients to play active roles in managing their health, there has been a focus on their use in chronic diseases and long-term self-management. Basic use of digital health may simplify healthcare through digitization, changing the method of data collection from paper to digital means. One prominent example is the almost ubiquitous use of electronic health records (EHR) over paper forms. However, as digital health evolves, there is increasing focus on digitalization, where current processes are improved and altered through the use of digital health such as online patient recruitment or medication tracking. Recruitment via online modalities has been found to be cost-effective, faster, and achieves higher recruitment rates compared to traditional methods (Brøgger-Mikkelsen et al., 2020). Quisel et al (2019) found that those who actively used their digital health activity trackers were more likely to be adherent to their cardiovascular medication. Digitalization may encourage fundamental behavior change in patients through improved efficiency in current process that lower barriers to better health behaviors. Digital maturity is the ultimate form where digital health is utilized to innovate and fundamentally alter t

ough improved efficiency in current process that lower barriers to better health behaviors. Digital maturity is the ultimate form where digital health is utilized to innovate and fundamentally alter the healthcare paradigm. This is an area that is yet to be explored but a revolution in healthcare will occur when patients, physicians, and other healthcare stakeholders can integrate mature digital health devices and tools into regular care (Figure 1).

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Figure 1. Digital Health Maturity with Examples Regardless, the digital health field is manifesting in many forms from mobile devices, software as a medical device (SaMD), wearable devices, telemedicine, digital therapeutics, and connected drug combination products. The potential of digital health in reducing ever-growing healthcare costs, improving outcomes, and providing new treatment modalities cannot be understated. Sophisticated digital health technologies can monitor patient outcomes, address gaps in patient care, and even support medication optimization. Digital health has been explored as a possible solution to issues surrounding adherence, patient administration techniques, disease self- management, and data outcomes at scale (Bittner, et al., 2019). These technologies are rapidly expanding to provide new and innovative ways to improve health outcomes and many healthcare stakeholders are exploring how digital health can be used.

er, et al., 2019). These technologies are rapidly expanding to provide new and innovative ways to improve health outcomes and many healthcare stakeholders are exploring how digital health can be used.

[Image 1]: The photograph is a diagram illustrating the progression of digital tools in healthcare, moving from traditional methods to advanced digital maturity. It shows three stages: Digitization (transforming analog data to digital), Digitalization (improving efficiency with technology), and Digital Maturity (using digital tools for innovation). The diagram uses a black background with white and blue text boxes to highlight key elements like patient outcome collection and recruitment methods. The main subject is the evolution of digital healthcare practices, with the setting being a structured visual flowchart and colors primarily black, white, and blue.

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Clinical trials have become increasingly costly following Eroom’s Law, an observation that drug discovery is becoming slower and more expensive despite technological advancements (Scannell et al., 2012). Developing these technological advancements is extremely costly, and study sponsors are under intense scrutiny from competitors, regulatory agencies, and consumers to develop effective products. Fierce competition to develop more complex drug products and meet FDA requirements has resulted in a convoluted clinical trial process. DiMasi (2016) found that the number of study endpoints required by the FDA increased by 86% from 2001-2005 to 2011- 2015 and almost 60% of protocols required a major amendment, which came at a median cost of $141,000. As a result, biopharmaceutical companies are looking at how digital health cannot only reduce costs, patient burden, and reliance on in-person clinic visits but also improve outcome measurements and validation methods. Traditional clinical trials are heavily restrained by cost, duration, and patient engagement. Throughout the course of a traditional c

its but also improve outcome measurements and validation methods. Traditional clinical trials are heavily restrained by cost, duration, and patient engagement. Throughout the course of a traditional clinical trial there are many lost opportunities to monitor a variety of endpoints for disease progression, pharmacokinetics, pharmacodynamics, and safety beyond periodic assessments. End points that are monitored may be heavily dependent on patient engagement and willingness and be subjected to reliability and validity concerns. Furthermore, the trial endpoints may fulfil FDA requirements for drug approval but could be a measurement that is not necessarily meaningful to patients or healthcare providers. The biopharmaceutical industry has recognized the potential of digital health and is driving innovation with guidance from the FDA’s newly established Digital Health Center of Excellence (DHCoE) and other regulatory agencies (Food & Drug Administration [FDA], 2020). The application and value of digital health to clinical trials is currently being explored. These so called decentralized, siteless, remote, or virtual clinical trials integrate digital health in the

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and value of digital health to clinical trials is currently being explored. These so called decentralized, siteless, remote, or virtual clinical trials integrate digital health in the

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delivery of care to move the trial outside of the clinic and enable remote and real-time collection of traditional and novel data. Ideally, digitalization would improve recruitment and retention, data collection, and analytics (Inan et al., 2020). Clinical trials have consistently had low patient adherence and persistence where Murthy et al. (2004) found that only 8% of cancer patients enroll in clinical trials. Recruitment and retainment using digital methods increases access to appropriate and diverse patient populations. Clinical trial language is often confusing to patients and they may not know what participating in a clinical trial may require of them. Having clear guidelines and directions delivered digitally could ensure patients understand the requirements needed from them to participate in the clinical trial. Additionally, patients recruited through relevant online health communities may be more engaged and willing to complete the clinical trial, resulting in better data to determine drug efficacy. With digital recruitment strategies, communication methods can be more tailored towards the targeted population to overcome communication barriers or issues of mistrust and fear in ethnic groups. Decentralized trials will enable participants to take part in a clinical trial regardless of their location, considerably reducing patient burden for travel. Even in so called hybrid trials, where a portion of the clinical trial is still conducted at a study site, there is still improved accessibility. Patients may be required to meet the investigator in the beginning of the trial but could transition completely to virtual meetings as the trial proceeds. Furthermore, telemedicine can improve communication between patients and investigators by providing a method for patien

trial but could transition completely to virtual meetings as the trial proceeds. Furthermore, telemedicine can improve communication between patients and investigators by providing a method for patients to ask questions. For investigators of clinical trials, a virtual trial allows them to oversee more patients in a larger area compared to traditional clinical trials that limited their oversight to their site. Digital health tools can collect more data thorough patient-reported outcomes (PRO) and biomarkers through technologies such as wearable and mobile sensors. Digital biomarkers, physiological or Reproduced with permission of copyright owner. Further reproduction prohibited without permission.

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