A smartphone- and wearable-based biomarker for the estimation of unipolar depression severity.

Drug development for mood disorders can greatly benefit from the development of robust, reliable, and objective biomarkers. The incorporation of smartphones and wearable devices in clinical trials provide a unique opportunity to monitor behavior in a non-invasive manner. The objective of this study is to identify the correlations between remotely monitored self-reported assessments and objectively measured activities with depression severity assessments often applied in clinical trials. 30 unipolar depressed patients and 29 age- and gender-matched healthy controls were enrolled in this study. Each participant's daily physiological, physical, and social activity were monitored using a smartphone-based application (CHDR MORE™) for 3 weeks continuously. Self-reported depression anxiety stress scale-21 (DASS-21) and positive and negative affect schedule (PANAS) were administered via smartphone weekly and daily respectively. The structured interview guide for the Hamilton depression scale and inventory of depressive symptomatology-clinical rated (SIGHD-IDSC) was administered in-clinic weekly. Nested cross-validated linear mixed-effects models were used to identify the correlation between the CHDR MORE™ features with the weekly in-clinic SIGHD-IDSC scores. The SIGHD-IDSC regression model demonstrated an explained variance (R2) of 0.80, and a Root Mean Square Error (RMSE) of ± 15 points. The SIGHD-IDSC total scores were positively correlated with the DASS and mean steps-per-minute, and negatively correlated with the travel duration. Unobtrusive, remotely monitored behavior and self-reported outcomes are correlated with depression severity. While these features cannot replace the SIGHD-IDSC for estimating depression severity, it can serve as a complementary approach for assessing depression and drug effects outside the clinic.

Smartphone and Wearable Sensors for the Estimation of Facioscapulohumeral Muscular Dystrophy Disease Severity: Cross-sectional Study.

BACKGROUND: Facioscapulohumeral muscular dystrophy (FSHD) is a progressive neuromuscular disease. Its slow and variable progression makes the development of new treatments highly dependent on validated biomarkers that can quantify disease progression and response to drug interventions. OBJECTIVE: We aimed to build a tool that estimates FSHD clinical severity based on behavioral features captured using smartphone and remote sensor data. The adoption of remote monitoring tools, such as smartphones and wearables, would provide a novel opportunity for continuous, passive, and objective monitoring of FSHD symptom severity outside the clinic. METHODS: In total, 38 genetically confirmed patients with FSHD were enrolled. The FSHD Clinical Score and the Timed Up and Go (TUG) test were used to assess FSHD symptom severity at days 0 and 42. Remote sensor data were collected using an Android smartphone, Withings Steel HR+, Body+, and BPM Connect+ for 6 continuous weeks. We created 2 single-task regression models that estimated the FSHD Clinical Score and TUG separately. Further, we built 1 multitask regression model that estimated the 2 clinical assessments simultaneously. Further, we assessed how an increasingly incremental time window affected the model performance. To do so, we trained the models on an incrementally increasing time window (from day 1 until day 14) and evaluated the predictions of the clinical severity on the remaining 4 weeks of data. RESULTS: The single-task regression models achieved an R2 of 0.57 and 0.59 and a root-mean-square error (RMSE) of 2.09 and 1.66 when estimating FSHD Clinical Score and TUG, respectively. Time spent at a health-related location (such as a gym or hospital) and call duration were features that were predictive of both clinical assessments. The multitask model achieved an R2 of 0.66 and 0.81 and an RMSE of 1.97 and 1.61 for the FSHD Clinical Score and TUG, respectively, and therefore outperformed the single-task models in estimating clinical severity. The 3 most important features selected by the multitask model were light sleep duration, total steps per day, and mean steps per minute. Using an increasing time window (starting from day 1 to day 14) for the FSHD Clinical Score, TUG, and multitask estimation yielded an average R2 of 0.65, 0.79, and 0.76 and an average RMSE of 3.37, 2.05, and 4.37, respectively. CONCLUSIONS: We demonstrated that smartphone and remote sensor data could be used to estimate FSHD clinical severity and therefore complement the assessment of FSHD outside the clinic. In addition, our results illustrated that training the models on the first week of data allows for consistent and stable prediction of FSHD symptom severity. Longitudinal follow-up studies should be conducted to further validate the reliability and validity of the multitask model as a tool to monitor disease progression over a longer period. TRIAL REGISTRATION: ClinicalTrials.gov NCT04999735; https://www.clinicaltrials.gov/ct2/show/NCT04999735.

Fit for purpose of on-the-road driving and simulated driving: A randomised crossover study using the effect of sleep deprivation.

INTRODUCTION: Drivers should be aware of possible impairing effects of alcohol, medicinal substance, or fatigue on driving performance. Such effects are assessed in clinical trials, including a driving task or related psychomotor tasks. However, a choice between predicting tasks must be made. Here, we compare driving performance with on-the-road driving, simulator driving, and psychomotor tasks using the effect of sleep deprivation. METHOD: This two-way cross over study included 24 healthy men with a minimum driving experience of 3000km per year. Psychomotor tasks, simulated driving, and on-the-road driving were assessed in the morning and the afternoon after a well-rested night and in the morning after a sleep-deprived night. Driving behaviour was examined by calculating the Standard Deviation of Lateral Position (SDLP). RESULTS: SDLP increased after sleep deprivation for simulated (10cm, 95%CI:6.7-13.3) and on-the-road driving (2.8cm, 95%CI:1.9-3.7). The psychomotor test battery detected effects of sleep deprivation in almost all tasks. Correlation between on-the-road tests and simulator SDLP after a well-rested night (0.63, p < .001) was not present after a night of sleep deprivation (0.31, p = .18). Regarding the effect of sleep deprivation on the psychomotor test battery, only adaptive tracking correlated with the SDLP of the driving simulator (-0.50, p = .02). Other significant correlations were related to subjective VAS scores. DISCUSSION: The lack of apparent correlations and difference in sensitivity of performance of the psychomotor tasks, simulated driving and, on-the-road driving indicates that the tasks may not be interchangeable and may assess different aspects of driving behaviour.

A crossover study evaluating the sex-dependent and sensitizing effects of sleep deprivation using a nociceptive test battery in healthy subjects.

AIM: We assessed whether total sleep deprivation (TSD) in combination with pain tests yields a reliable method to assess altered pain thresholds, which subsequently may be used to investigate (novel) analgesics in healthy subjects. METHODS: This was a two-part randomized crossover study in 24 healthy men and 24 women. Subjects were randomized 1:1 to first complete a day of nonsleep-deprived nociceptive threshold testing, followed directly by a TSD night and morning of sleep-deprived testing, or first complete the TSD night and morning sleep-deprived testing, returning 7 days later for a day of nonsleep-deprived testing. A validated pain test battery (heat, pressure, electrical burst and stair, cold pressor pain test and conditioned pain modulation [CPM] paradigm) and sleep questionnaires were performed. RESULTS: Subjects were significantly sleepier after TSD as measured using sleepiness questionnaires. Cold pressor pain tolerance (PTT, estimate of difference [ED] -10.8%, 95% CI -17.5 to -3.6%), CPM PTT (ED -0.69 mA, 95% CI -1.36 to -0.03 mA), pressure PTT (ED -11.2%, 95% CI -17.5% to -4.3%) and heat pain detection thresholds (ED -0.74 °C, 95% CI -1.34 to -0.14 °C) were significantly decreased after TSD compared to the baseline morning assessment in the combined analysis (men + women). Heat hyperalgesia was primarily driven by an effect of TSD in men, whereas cold and pressure hyperalgesia was primarily driven by the effects of TSD observed in women. CONCLUSIONS: TSD induced sex-dependent hyperalgesia on cold, heat and pressure pain, and CPM response. These results suggest that the TSD model may be suitable to evaluate (novel) analgesics in early-phase drug studies.

Muscle velocity recovery cycles as pharmacodynamic biomarker: Effects of mexiletine in a randomized double-blind placebo-controlled cross-over study.

Measuring muscle velocity recovery cycles (MVRCs) is a method to obtain information on muscle cell excitability, independent of neuromuscular transmission. The goal was to validate MVRC as a pharmacodynamic (PD) biomarker for drugs targeting muscle excitability. As proof-of-concept, sensitivity of MVRC to detect effects of mexiletine, a voltage-gated sodium channel (Nav ) blocker, was assessed. In a randomized, double-blind, two-way crossover study, effects of a single pharmacologically active oral dose of 333 mg mexiletine was compared to placebo in 15 healthy male subjects. MVRC was performed predose, and 3- and 5-h postdose using QTrac. Effects of mexiletine versus placebo were calculated using a mixed effects model with baseline as covariate. Mexiletine had significant effects on MVRC when compared to placebo. Early supernormality after five conditioning stimuli was decreased by mexiletine (estimated difference -2.78% [95% confidence interval: -4.16, -1.40]; p value = 0.0003). Moreover, mexiletine decreased the difference in late supernormality after five versus one conditioning stimuli (5XLSN; ED -1.46% [-2.26, -0.65]; p = 0.001). These results indicate that mexiletine decreases the percentage increase in velocity of the muscle fiber action potential after five conditioning stimuli, at long and short interstimulus intervals, which corresponds to a decrease in muscle membrane excitability. This is in line with the pharmacological activity of mexiletine, which leads to use-dependent NaV 1.4 blockade affecting muscle membrane potentials. This study shows that effects of mexiletine can be detected using MVRC in healthy subjects, thereby indicating that MVRC can be used as a tool to demonstrate PD effects of drugs targeting muscle excitability in early phase drug development.

Objective Monitoring of Facioscapulohumeral Dystrophy During Clinical Trials Using a Smartphone App and Wearables: Observational Study.

BACKGROUND: Facioscapulohumeral dystrophy (FSHD) is a progressive muscle dystrophy disorder leading to significant disability. Currently, FSHD symptom severity is assessed by clinical assessments such as the FSHD clinical score and the Timed Up-and-Go test. These assessments are limited in their ability to capture changes continuously and the full impact of the disease on patients' quality of life. Real-world data related to physical activity, sleep, and social behavior could potentially provide additional insight into the impact of the disease and might be useful in assessing treatment effects on aspects that are important contributors to the functioning and well-being of patients with FSHD. OBJECTIVE: This study investigated the feasibility of using smartphones and wearables to capture symptoms related to FSHD based on a continuous collection of multiple features, such as the number of steps, sleep, and app use. We also identified features that can be used to differentiate between patients with FSHD and non-FSHD controls. METHODS: In this exploratory noninterventional study, 58 participants (n=38, 66%, patients with FSHD and n=20, 34%, non-FSHD controls) were monitored using a smartphone monitoring app for 6 weeks. On the first and last day of the study period, clinicians assessed the participants' FSHD clinical score and Timed Up-and-Go test time. Participants installed the app on their Android smartphones, were given a smartwatch, and were instructed to measure their weight and blood pressure on a weekly basis using a scale and blood pressure monitor. The user experience and perceived burden of the app on participants' smartphones were assessed at 6 weeks using a questionnaire. With the data collected, we sought to identify the behavioral features that were most salient in distinguishing the 2 groups (patients with FSHD and non-FSHD controls) and the optimal time window to perform the classification. RESULTS: Overall, the participants stated that the app was well tolerated, but 67% (39/58) noticed a difference in battery life using all 6 weeks of data, we classified patients with FSHD and non-FSHD controls with 93% accuracy, 100% sensitivity, and 80% specificity. We found that the optimal time window for the classification is the first day of data collection and the first week of data collection, which yielded an accuracy, sensitivity, and specificity of 95.8%, 100%, and 94.4%, respectively. Features relating to smartphone acceleration, app use, location, physical activity, sleep, and call behavior were the most salient features for the classification. CONCLUSIONS: Remotely monitored data collection allowed for the collection of daily activity data in patients with FSHD and non-FSHD controls for 6 weeks. We demonstrated the initial ability to detect differences in features in patients with FSHD and non-FSHD controls using smartphones and wearables, mainly based on data related to physical and social activity. TRIAL REGISTRATION: ClinicalTrials.gov NCT04999735; https://www.clinicaltrials.gov/ct2/show/NCT04999735.

Effects of Mexiletine and Lacosamide on Nerve Excitability in Healthy Subjects: A Randomized, Double-Blind, Placebo-Controlled, Crossover Study.

Selective voltage-gated sodium channel blockers are of growing interest as treatment for pain. For drug development of such compounds, it would be critical to have a biomarker that can be used for proof-of-mechanism. We aimed to evaluate whether drug-induced changes in sodium conductance can be detected in the peripheral nerve excitability profile in 18 healthy subjects. In a randomized, double-blind, 3-way crossover study, effects of single oral doses of 333 mg mexiletine and 300 mg lacosamide were compared with placebo. On each study visit, motor and sensory nerve excitability measurements of the median nerve were performed (predose; and 3 and 6 hours postdose) using Qtrac. Treatment effects were calculated using an analysis of covariance (ANCOVA) with baseline as covariate. Mexiletine and lacosamide had significant effects on multiple motor and sensory nerve excitability variables. Depolarizing threshold electrotonus (TEd40 (40-60 ms)) decreased by mexiletine (estimated difference (ED) -1.37% (95% confidence interval (CI): -2.20, -0.547; P = 0.002) and lacosamide (ED -1.27%, 95% CI: -2.10, -0.443; P = 0.004) in motor nerves. Moreover, mexiletine and lacosamide decreased superexcitability (less negative) in motor nerves (ED 1.74%, 95% CI: 0.615, 2.87; P = 0.004, and ED 1.47%, 95% CI: 0.341, 2.60; P = 0.013, respectively). Strength-duration time constant decreased after lacosamide in motor- (ED -0.0342 ms, 95% CI: -0.0571, -0.0112; P = 0.005) and sensory nerves (ED -0.0778 ms, 95% CI: -0.116, -0.0399; P < 0.001). Mexiletine and lacosamide significantly decrease excitability of motor and sensory nerves, in line with their suggested mechanism of action. Results of this study indicate that nerve excitability threshold tracking can be an effective pharmacodynamic biomarker. The method could be a valuable tool in clinical drug development.

Simultaneous measurement of intra-epidermal electric detection thresholds and evoked potentials for observation of nociceptive processing following sleep deprivation.

Sleep deprivation has been shown to increase pain intensity and decrease pain thresholds in healthy subjects. In chronic pain patients, sleep impairment often worsens the perceived pain intensity. This increased pain perception is the result of altered nociceptive processing. We recently developed a method to quantify and monitor altered nociceptive processing by simultaneous tracking of psychophysical detection thresholds and recording of evoked cortical potentials during intra-epidermal electric stimulation. In this study, we assessed the sensitivity of nociceptive detection thresholds and evoked potentials to altered nociceptive processing after sleep deprivation in an exploratory study with 24 healthy male and 24 healthy female subjects. In each subject, we tracked nociceptive detection thresholds and recorded central evoked potentials in response to 180 single- and 180 double-pulse intra-epidermal electric stimuli. Results showed that the detection thresholds for single- and double-pulse stimuli and the average central evoked potential for single-pulse stimuli were significantly decreased after sleep deprivation. When analyzed separated by sex, these effects were only significant in the male population. Multivariate analysis showed that the decrease of central evoked potential was associated with a decrease of task-related evoked activity. Measurement repetition led to a decrease of the detection threshold to double-pulse stimuli in the mixed and the female population, but did not significantly affect any other outcome measures. These results suggest that simultaneous tracking of psychophysical detection thresholds and evoked potentials is a useful method to observe altered nociceptive processing after sleep deprivation, but is also sensitive to sex differences and measurement repetition.