Why Language Matters in Digital Endpoint Development: Harmonized Terminology as a Key Prerequisite for Evidence Generation.

Background: Developments in the field of digital measures and digitally derived endpoints demand greater attention on globally aligned approaches to enhance digital measure acceptance by regulatory authorities and health technology assessment (HTA) bodies for decision-making. In order to maximize the value of digital measures in global drug development programs and to ensure study teams and regulators are referring to the same items, greater alignment of concepts, definitions, and terminology is required. This is a fast-moving complex field; every day brings new technologies, algorithms, and possibilities. A common language is particularly important when working in multifunctional teams to ensure that there is a clear understanding of what is meant and understood. Summary: In the paper, the EFPIA digital endpoint joint subgroup reviews the challenges facing teams working to advance digital endpoints, where different terms are used to describe the same things, where common terms such as "monitoring" have significantly different meaning for different regulatory agencies, where the preface "e" to denote electronic is still used in some contexts, but the term "digital" is used in other, and where there is significant confusion as to what is understood by "raw" when it comes to data derived from digital health technologies. Key Message: The EFPIA subgroup is calling for an aligned lexicon. Alignment provides a more predictable path for development, validation, and use of the tools and measures used to collect digital endpoints supporting standardization and consistency in this new field of research, with the goal of increasing regulatory and payer harmonization and acceptance.

Digital health technology derived measures: Biomarkers or clinical outcome assessments?

Digital health technologies (DHTs) present unique opportunities for clinical evidence generation but pose certain challenges. These challenges stem, in part, from existing definitions of drug development tools, which were not created with DHT-derived measures in mind. DHT-derived measures can be leveraged as either clinical outcome assessments (COAs) or as biomarkers since they share properties with both categories of drug development tools. Examples from the literature indicate a variety of applications for DHT-derived data, including capturing disease physiology, symptom tracking, or response to therapies. The distinction between the categorization of DHT-derived measures as COAs or as biomarkers can be very fine, with terminology variability among regulatory authorities. This has significant implications for integration of DHT-derived measures in clinical trials, leading to confusion regarding the evidence required to support these tools' use in drug development. There is a need to amend definitions and create clear evidentiary requirements to support broad adoption of these new and innovative tools. The biopharma industry, the technology sector, consulting businesses, academic researchers, and regulators need a dialogue via multi-stakeholder collaborations to clarify questions around DHT-derived measures, to unify definitions, and to create the foundations for evidentiary package requirements, providing a path forward to predictable results.

Considerations for Conducting Bring Your Own "Device" (BYOD) Clinical Studies.

Background: Digital health technologies are attracting attention as novel tools for data collection in clinical research. They present alternative methods compared to in-clinic data collection, which often yields snapshots of the participants' physiology, behavior, and function that may be prone to biases and artifacts, e.g., white coat hypertension, and not representative of the data in free-living conditions. Modern digital health technologies equipped with multi-modal sensors combine different data streams to derive comprehensive endpoints that are important to study participants and are clinically meaningful. Used for data collection in clinical trials, they can be deployed as provisioned products where technology is given at study start or in a bring your own "device" (BYOD) manner where participants use their technologies to generate study data. Summary: The BYOD option has the potential to be more user-friendly, allowing participants to use technologies that they are familiar with, ensuring better participant compliance, and potentially reducing the bias that comes with introducing new technologies. However, this approach presents different technical, operational, regulatory, and ethical challenges to study teams. For example, BYOD data can be more heterogeneous, and recruiting historically underrepresented populations with limited access to technology and the internet can be challenging. Despite the rapid increase in digital health technologies for clinical and healthcare research, BYOD use in clinical trials is limited, and regulatory guidance is still evolving. Key Messages: We offer considerations for academic researchers, drug developers, and patient advocacy organizations on the design and deployment of BYOD models in clinical research. These considerations address: (1) early identification and engagement with internal and external stakeholders; (2) study design including informed consent and recruitment strategies; (3) outcome, endpoint, and technology selection; (4) data management including compliance and data monitoring; (5) statistical considerations to meet regulatory requirements. We believe that this article acts as a primer, providing insights into study design and operational requirements to ensure the successful implementation of BYOD clinical studies.

A comparison of the age at first calving of contract-reared versus home-reared replacement dairy heifers.

Recent rapid expansion and increased specialisation of dairy industries internationally has prompted growing interest in collaborative farming enterprises such as contract-rearing of replacement heifers. While contract-rearing provides obvious benefits to dairy farmers intending to expand their herd, it may adversely impact heifer reproductive performance as the farmer no longer manages the heifers on a day-to-day basis. Hence, the objective of this study was to determine if contract-rearing impacted heifer reproductive performance and ultimately achievement of the industry target age at first calving (AFC) of 24 months. Live weight, body condition score (BCS) and morbidity data were collected from 3908 heifers on 99 farms (54 contract-rearing dairy farms; 45 home-rearing dairy farms) on three occasions between one month of age and prior to commencement of their first breeding season; average daily gain (ADG) between farm visits was calculated. Heifer birth dates, breeds, economic breeding index (EBI), mating start dates (MSD) and calving dates were extracted from the national cattle breeding database. To assess the reproductive performance of study heifers, the outcome of interest was age at first calving (AFC). In addition to the effect of heifer rearing system, the association between pre-breeding ADG, body weight and BCS and AFC was also investigated. Descriptive and survival analysis was performed to calculate the distribution of AFC across study farms and to assess the association of rearing strategy and other variables on AFC. Results indicate that there was no difference in median AFC between home and contract-reared heifers (24.4 months). At univariate level, variables significantly associated with AFC were occurrence of pyrexia before MSD, pre-breeding ADG, body weight and BCS. However, when the frailty effect of farm was incorporated into the multivariable model, these variables were no longer significant, indicating wide variation in individual farm management practices not measured in this study. It was concluded that rearing strategy (home versus contract-rearing) did not significantly affect heifer AFC.

The overlooked vital sign: The importance of measuring sleep in drug development studies.

Sleep is rarely considered in drug development studies. Pre-existing sleep problems or changes in sleep parameters in response to therapeutics have the potential to diminish the true utility of the agent under development. Sleep is integral to human health and affects virtually every disease. We present evidence that indicates how sleep quality and quantity can be predictive of disease risk, progression, remission, and recurrence. Supporting the premise that we should conceptualize sleep as a 'vital sign' and measure sleep as an integral component in drug development. We highlight the emergence of digital health technologies that have enabled the capture of this 'vital sign' and ask the question: why is sleep still largely ignored in drug development studies?

Longitudinal Prevalence of Antibodies to Endemic Pathogens in Bulk Tank Milk Samples From Dairy Herds Engaged or Not in Contract Heifer Rearing.

Since the abolition of EU milk production quotas in 2015, Europe's dairy industries have undergone a period of rapid expansion with possible resultant increased inter-herd transmission of endemic pathogens. The aims of this study were (1) to establish the post-2015 prevalence of antibodies to selected endemic infectious diseases and (2) to determine if prevalences differed between herds where heifers were reared at home and those where heifers were sent out for contract-rearing. Three bulk tank milk (BTM) samples were collected annually between May and August of 2018-20 inclusively from 120 Irish dairy herds. Additionally, herd vaccination status was collected by questionnaire. Milk samples were tested using commercially available ELISAs for eight pathogens: bovine viral diarrhea virus (BVDV), bovine herpesvirus 1 (BoHv-1), bovine respiratory syncytial virus (BRSV), Mycoplasma bovis, Mycobacterium avium subspecies paratuberculosis (MAP), Salmonella Dublin (S. Dublin), Leptospira Hardjo (L. Hardjo), and Neospora caninum (N. caninum). The true prevalence of each pathogen was calculated using a Rogan-Gladen estimator. The true prevalences (95% CI) of BTM antibodies in unvaccinated herds across the 3 years were as follows (i) BVDV: 57, 86, and 73% (95% CI: 40.7-65.9, 74-94, and 58-85) (n = 56, 56, and 48), (ii) BoHv-1: 47, 49, and 19% (95% CI: 26.3-69.7, 25-75, and 1-56) (n = 21, 20, and 11), (iii) L. Hardjo: 34, 59, and 73% (95% CI: 12.5-63, 33-82, and 33-99) (n = 15, 21, and 10), (iv) S. Dublin 32, 57, and 11% (95% CI: 12.21-68.1, 30.2-90.1, and 0) (n = 19, 22, and 13), (v) BRSV: 100% (95% CI: 99.5-100, 100, and 100) (n = 120, 109, and 91), (vi) MAP: 0% (95% CI: 0, 0, and 0) (n = 120, 109, and 91) (vii) N. caninum 0% (95% CI: 0, 0, and 0) (n = 120, 109, and 91) and (viii) M. bovis (ELISA) 53, 0.42, and 30% (95% CI: 3.95-6.84, 0, and 21-41) (n = 120, 109, and 91). M. bovis was detected by PCR in 0, 1, and 0% of herds in 2018, 2019, and 2020, respectively. This study showed that expanding Irish dairy herds are endemically infected with several of the studied pathogens. No differences in herd prevalence of infectious agents were observed between farms with different heifer rearing strategies (contract-rearing vs. traditional rearing).

The Effect of Contract-Rearing on the Health Status of Replacement Dairy Heifers.

The aim of this study was to compare the health status of contract- vs. conventionally reared replacement dairy heifers over a 2-year period. A total of 120 dairy farmers were enrolled in the study in spring 2018: 55 farmers were rearing their own heifers (control farmers; CFs), and 65 were sending heifers to a contract-rearing farm (source dairy farmers; SDFs). Between spring 2018 and autumn 2019, approximately 5500 replacement heifers from these farms were monitored for signs of ill health during four farm visits using a modified version of the Wisconsin calf health scoring system. Additionally, faecal and nasal swabs were taken from a proportion of heifers with clinical signs of diarrhoea and respiratory disease to determine the associated aetiological agents. Results indicate few differences in the health status and pathogen exposure status of home-reared versus contract-reared heifers. Additionally, the number of source dairy farms represented and commingling of heifers from multiple origins at the rearing unit were not associated with an increased incidence of respiratory disease or diarrhoea among contract-reared heifers. It was concluded that contract-rearing did not result in adverse health outcomes for replacement dairy heifers. This is the first study to demonstrate this finding in a robust, longitudinal, herd-level population study.

Using Methods From Computational Decision-making to Predict Nonadherence to Fitness Goals: Protocol for an Observational Study.

BACKGROUND: Can methods from computational models of decision-making be used to build a predictive model to identify individuals most likely to be nonadherent to personal fitness goals? Such a model may have significant value in the global battle against obesity. Despite growing awareness of the impact of physical inactivity on human health, sedentary behavior is increasingly linked to premature death in the developed world. The annual impact of sedentary behavior is significant, causing an estimated 2 million deaths. From a global perspective, sedentary behavior is one of the 10 leading causes of mortality and morbidity. Annually, considerable funding and countless public health initiatives are applied to promote physical fitness, with little impact on sustained behavioral change. Predictive models developed from multimodal methodologies combining data from decision-making tasks with contextual insights and objective physical activity data could be used to identify those most likely to abandon their fitness goals. This has the potential to enable development of more targeted support to ensure that those who embark on fitness programs are successful. OBJECTIVE: The aim of this study is to determine whether it is possible to use decision-making tasks such as the Iowa Gambling Task to help determine those most likely to abandon their fitness goals. Predictive models built using methods from computational models of decision-making, combining objective data from a fitness tracker with personality traits and modeling from decision-making games delivered via a mobile app, will be used to ascertain whether a predictive algorithm can identify digital personae most likely to be nonadherent to self-determined exercise goals. If it is possible to phenotype these individuals, it may be possible to tailor initiatives to support these individuals to continue exercising. METHODS: This is a siteless study design based on a bring your own device model. A total of 200 healthy adults who are novice exercisers and own a Fitbit (Fitbit Inc) physical activity tracker will be recruited via social media for this study. Participants will provide consent via the study app, which they will download from the Google Play store (Alphabet Inc) or Apple App Store (Apple Inc). They will also provide consent to share their Fitbit data. Necessary demographic information concerning age and sex will be collected as part of the recruitment process. Over 12 months, the scheduled study assessments will be pushed to the subjects to complete. The Iowa Gambling Task will be administered via a web app shared via a URL. RESULTS: Ethics approval was received from Dublin City University in December 2020. At manuscript submission, study recruitment was pending. The expected results will be published in 2022. CONCLUSIONS: It is hoped that the study results will support the development of a predictive model and the study design will inform future research approaches. TRIAL REGISTRATION: ClinicalTrials.gov NCT04783298; https://clinicaltrials.gov/ct2/show/NCT04783298.

Choosing a Mobile Sensor Technology for a Clinical Trial: Statistical Considerations, Developments and Learnings.

The DIA Study Endpoints Community Working Group on Mobile Sensor Technology (MST) series addresses considerations that may be useful for selecting MST for use in a clinical trial. This article describes considerations regarding the selection of MST for clinical trials including expectations around technology specifications, verification (bench testing), regulatory clearance and certification status. We identify useful statistical methods needed to establish agreement of the MST with respect to a clinical 'gold' standard technology in terms of accuracy and precision, and to combine data across trials, data types or device versions. In addition to describing key considerations, this manuscript also serves as a central location citing those resources where additional detail can be found.

Determining Minimum Wear Time for Mobile Sensor Technology.

Part 1 in the DIA Study Endpoint Community Working Group on Mobile Sensor Technology (MST) series addresses considerations that may be useful when determining the minimum wear time associated with mobile sensor use to ensure reliable estimation of the clinical endpoint under consideration. What constitutes a minimum valid data set is a dilemma facing those using MSTs in clinical studies. If this alignment does not occur, the integrity of the data collected and conclusions drawn from these data may be in incorrect. While study participants should consent to engage with MSTs as defined in a protocol, participant behavior or technology lapses may result in capturing incomplete data. Drawing from the literature, we review what constitutes a minimum data set, the risks associated with missing data, alignment with the clinical endpoint(s) and goals of a study, as well as managing patient burden.

A Roadmap to Inform Development, Validation and Approval of Digital Mobility Outcomes: The Mobilise-D Approach.

Health care has had to adapt rapidly to COVID-19, and this in turn has highlighted a pressing need for tools to facilitate remote visits and monitoring. Digital health technology, including body-worn devices, offers a solution using digital outcomes to measure and monitor disease status and provide outcomes meaningful to both patients and health care professionals. Remote monitoring of physical mobility is a prime example, because mobility is among the most advanced modalities that can be assessed digitally and remotely. Loss of mobility is also an important feature of many health conditions, providing a read-out of health as well as a target for intervention. Real-world, continuous digital measures of mobility (digital mobility outcomes or DMOs) provide an opportunity for novel insights into health care conditions complementing existing mobility measures. Accepted and approved DMOs are not yet widely available. The need for large collaborative efforts to tackle the critical steps to adoption is widely recognised. Mobilise-D is an example. It is a multidisciplinary consortium of 34 institutions from academia and industry funded through the European Innovative Medicines Initiative 2 Joint Undertaking. Members of Mobilise-D are collaborating to address the critical steps for DMOs to be adopted in clinical trials and ultimately health care. To achieve this, the consortium has developed a roadmap to inform the development, validation and approval of DMOs in Parkinson's disease, multiple sclerosis, chronic obstructive pulmonary disease and recovery from proximal femoral fracture. Here we aim to describe the proposed approach and provide a high-level view of the ongoing and planned work of the Mobilise-D consortium. Ultimately, Mobilise-D aims to stimulate widespread adoption of DMOs through the provision of device agnostic software, standards and robust validation in order to bring digital outcomes from concept to use in clinical trials and health care.

Measurement Equivalence of Patient-Reported Outcome Measure Response Scale Types Collected Using Bring Your Own Device Compared to Paper and a Provisioned Device: Results of a Randomized Equivalence Trial.

OBJECTIVES: The aim of this study was to assess the measurement equivalence of individual response scale types by using a patient reported outcome measure (PROM) collected on paper and migrated into electronic format for use on the subject's own mobile device (BYOD) and on a provisioned device (site device). METHODS: Subjects suffering from chronic health conditions causing daily pain or discomfort were invited to participate in this single-site, single visit, three-way crossover study. Association between individual item and instrument subscale scores was assessed by using the intraclass correlation coefficient (ICC) and its CI. Participant attitudes toward the use of BYOD in a clinical trial were assessed through use of a questionnaire. RESULTS: In this study, 155 subjects (females 83 [54%]; males 72 [46%]) ages 19 to 69 years (mean ± SD: 48.6 ± 13.1) were recruited. High association between the modes of administration (paper, BYOD, site device) was shown with analysis of ICCs (0.79-0.98) for each response scale type, including visual analogue scale, numeric rating scale, verbal response scale, and Likert scale. Of the subjects, 94% (146 of 155) stated that they would definitely or probably be willing to download an app onto their own mobile device for a forthcoming clinical trial. Forty-five percent of subjects felt BYOD would be more convenient compared with 15% preferring a provisioned device (40% had no preference). CONCLUSIONS: This study provides strong evidence supporting the use of BYOD for PROM collection in terms of the conservation of instrument measurement equivalence across the most widely used response scale types, and high patient acceptance of the approach.

Prosopagnosia as a Type of Conversion Disorder.

BACKGROUND: Conversion disorder is a common and debilitating condition that remains poorly understood. We present a previously undescribed form of conversion disorder to highlight the complexity of the condition and consider the interplay of factors that produce conversion symptoms. CASE: A 50-year-old male presented with acquired prosopagnosia and language impairment. Neuropsychological testing indicated right temporal lobe dysfunction. Extensive work-up outruled an organic aetiology. Reactivation of childhood trauma coincided with the onset of his symptoms. Childhood trauma is known to have adverse effects on the developing brain which may affect an individual's emotional behaviour and coping style. Functional neuroimaging techniques suggest that conversion symptoms may be linked to the disruption of higher order neural circuitry involved in the integration of emotional processing and cortical functioning. CONCLUSIONS: We propose that our patient's adverse childhood experiences led to the development of a particular personality and coping style that "primed" him for a later abnormal emotional and behavioural response when confronted with reminders of his traumatic background. Further interdisciplinary studies are required to further elucidate the neurobiological basis for this condition.

Brain Monitoring Devices in Neuroscience Clinical Research: The Potential of Remote Monitoring Using Sensors, Wearables, and Mobile Devices.

The increasing miniaturization and affordability of sensors and circuitry has led to the current level of innovation in the area of wearable and microsensor solutions for health monitoring. This facilitates the development of solutions that can be used to measure complex health outcomes in nonspecialist and remote settings. In this article, we review a number of innovations related to brain monitoring including portable and wearable solutions to directly measure brain electrical activity, and solutions measuring aspects related to brain function such as sleep patterns, gait, cognition, voice acoustics, and gaze analysis. Despite the need for more scientific validation work, we conclude that there is enough understanding of how to implement these approaches as exploratory tools that may provide additional valuable insights due to the rich and frequent data they produce, to justify their inclusion in clinical study protocols.

The positive impacts of Real-World Data on the challenges facing the evolution of biopharma.

Demand for healthcare services is unprecedented. Society is struggling to afford the cost. Pricing of biopharmaceutical products is under scrutiny, especially by payers and Health Technology Assessment agencies. As we discuss here, rapidly advancing technologies, such as Real-World Data (RWD), are being utilized to increase understanding of disease. RWD, when captured and analyzed, produces the Real-World Evidence (RWE) that underpins the economic case for innovative medicines. Furthermore, RWD can inform the understanding of disease, help identify new therapeutic intervention points, and improve the efficiency of research and development (R&D), especially clinical trials. Pursuing precompetitive collaborations to define shared requirements for the use of RWD would equip service-providers with the specifications needed to implement cloud-based solutions for RWD acquisition, management and analysis. Only this approach would deliver cost-effective solutions to an industry-wide problem.

Standards for Instrument Migration When Implementing Paper Patient-Reported Outcome Instruments Electronically: Recommendations from a Qualitative Synthesis of Cognitive Interview and Usability Studies.

OBJECTIVES: To synthesize the findings of cognitive interview and usability studies performed to assess the measurement equivalence of patient-reported outcome (PRO) instruments migrated from paper to electronic formats (ePRO), and make recommendations regarding future migration validation requirements and ePRO design best practice. METHODS: We synthesized findings from all cognitive interview and usability studies performed by a contract research organization between 2012 and 2015: 53 studies comprising 68 unique instruments and 101 instrument evaluations. We summarized study findings to make recommendations for best practice and future validation requirements. RESULTS: Five studies (9%) identified minor findings during cognitive interview that may possibly affect instrument measurement properties. All findings could be addressed by application of ePRO best practice, such as eliminating scrolling, ensuring appropriate font size, ensuring suitable thickness of visual analogue scale lines, and providing suitable instructions. Similarly, regarding solution usability, 49 of the 53 studies (92%) recommended no changes in display clarity, navigation, operation, and completion without help. Reported usability findings could be eliminated by following good product design such as the size, location, and responsiveness of navigation buttons. CONCLUSIONS: With the benefit of accumulating evidence, it is possible to relax the need to routinely conduct cognitive interview and usability studies when implementing minor changes during instrument migration. Application of design best practice and selecting vendor solutions with good user interface and user experience properties that have been assessed in a representative group may enable many instrument migrations to be accepted without formal validation studies by instead conducting a structured expert screen review.

FOCUS on excellence: making a difference through global initiatives.

The Center of Excellence (COE) designation in the category of"student learning and professional development" has hallmarked Regis College as having nursing programs that create environments for students to excel academically, professionally, and personally. As a designated COE nursing program, our efforts have focused on creating and sustaining a curriculum that has a strong enculturation of diversity, with numerous local, regional, national, and international learning experiences. Examples of learning opportunities through global outreach health initiatives are included, demonstrating how the COE designation has provided recognition and led to further opportunities for faculty and students to become involved in health-related activities.

Wake-related activity of tuberomammillary neurons in rats.

Histaminergic neurons of the tuberomammillary nucleus (TMN) are hypothesized to promote wakefulness, but little is known about the activity of these cells during spontaneous behavior. We measured histaminergic neuron activity in the dorsomedial, ventrolateral, and caudal TMN at four different times using Fos and adenosine deaminase immunohistochemistry and recordings of sleep/wake behavior. Because circadian factors could influence neuronal activity, we then assessed TMN neuron activity in predominantly sleeping or awake animals, all killed at the same time of day. In both experiments, Fos expression in histaminergic neurons of all three TMN subnuclei was higher during periods of wakefulness. These results demonstrate that histaminergic neurons throughout the TMN are wake-active, and this activity is largely independent of the time of day.

The impact of alcohol use in community-dwelling older adults.

The purpose of this study was to explore the use of alcohol in community-dwelling older adults and to consider differences in physical and mental health, function, cognitive status, and social supports between those who drink minimal (1 to 3 glasses weekly), moderate (4 to 7 glasses weekly), or no alcohol. A total of 3305 older adults with a mean age of 81.6 -/+ 6.0 participated in the study. Twenty-two percent (n = 709) of the participants had 1 to 3 drinks weekly, only 1% (n = 18) reported 4 to 7 drinks weekly, and none of the participants admitted to 8 or more drinks. There was no difference in drinking behavior with regard to age (F = 1.1, p >.05) or social supports (F =.39, p >.05). There was a difference in drinking behavior with regard to physical health (F = 4.9, p <.05), functional status (F = 7.7, p <.05), cognitive status (F = 11.8, p <.05), and mental health (F = 6.9, p <.05). Health care providers should use an individualized approach to alcohol use in older adults and help these individuals establish, as appropriate, safe drinking habits that will augment health and quality of life.