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.

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

A Randomized Trial Assessing the Safety, Pharmacokinetics, and Efficacy During Morning Off of AZ-009

Background

Inhalation of apomorphine could be a faster‐acting and more user‐friendly alternative to subcutaneous injection for treating off periods in Parkinson's disease (PD).

Objective

The aim of this study was to compare the safety and pharmacokinetics of inhaled apomorphine (AZ‐009) with subcutaneous apomorphine (APO‐go PEN) in healthy volunteers (HVs) and to examine the safety, pharmacokinetics, and efficacy of AZ‐009 in patients with PD.

Methods

In part A of this study, eight HVs received 1 mg AZ‐009 and 2 mg subcutaneous apomorphine in a randomized crossover manner. In the subsequent single ascending dose parts in HVs (part B, n = 16) and patients with PD (part C, n = 25), participants were randomized to placebo or AZ‐009 up to 4 mg. In patients, after medication withdrawal, Movement Disorder Society‐Unified Parkinson's Disease Rating Scale part III and on/off states were assessed predose and postdose.

Results

AZ‐009 was rapidly absorbed with peak plasma concentrations at 2 minutes, as compared to 30 minutes for subcutaneous apomorphine. Adverse events for AZ‐009 were comparable to subcutaneous apomorphine, except for mild and transient throat irritation. Adverse events limited AZ‐009 dose escalation in HVs to 3 mg. Patients tolerated up to 4 mg. In patients with PD, 2, 3, and 4 mg AZ‐009 reduced mean Movement Disorder Society‐Unified Parkinson's Disease Rating Scale part III score (standard deviation) by 10.7 (13.6), 12.8 (7.9), and 10.3 (3.7) points, respectively, compared to 4.8 (4.9) after placebo at 10 minutes postdose. The percentage of patients achieving full on within 45 minutes postdose increased dose dependently: 0% (placebo), 17% (2 mg), 50% (3 mg), and 83% (4 mg).

Conclusions

AZ‐009 appears to be a rapid‐acting and reasonably well‐tolerated formulation for treating off periods. © 2022 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society

A Phase 1, open-label, multicentre study to compare the capsule and tablet formulations of AZD5363 and explore the effect of food on the pharmacokinetic exposure, safety and tolerability of AZD5363 in patients with advanced solid malignancies: OAK

PURPOSE

AZD5363 is a potent pan-AKT inhibitor originally formulated as a capsule; a tablet was developed for patient convenience and manufacturing ease. This study assessed the PK comparability of both formulations (Part A) and the effect of food (Part B) on the PK/safety of the tablet.

METHODS

Adults with advanced solid tumours received AZD5363 480 mg bid in a partially fasted state by tablet (Week 1) and capsule (Week 2) in a '4-days-on/3-days-off' schedule (Part A). PK parameters were evaluated using pre-defined 90% CIs for AUCτ and Cmax ratios of 0.75-1.33 to assess comparability. In Part B, AZD5363 tablet was given to a new cohort of patients under the same conditions as Part A, except on the morning of PK assessment days, when it was administered after an overnight fast (Week 1) and standard meal (Week 2).

RESULTS

In evaluable patients (N = 11), the geometric least-squares mean ratios (tablet:capsule) for AUCτ and Cmax were 0.90 (0.77-1.06) and 1.02 (0.86-1.20), respectively, demonstrating comparable PK in the partially fasted state. Tablet and capsule safety data were also comparable. Tablet PK profiles indicated later tmax and lower Cmax after food versus overnight fast. Fed and fasted AUCτ and Cmax ratios were 0.89 (0.76-1.05) and 0.67 (0.55-0.82), respectively (N = 9). The safety/tolerability profile of the tablet was comparable between fed and fasted states.

CONCLUSIONS

PK and safety/tolerability of AZD5363 tablet and capsule were comparable. Food did not affect the bioavailability of AZD5363, but reduced the absorption rate without discernibly affecting safety/tolerability.