There are limited objective measurements of MG symptoms as well as a dearth of data at a granular level of MG (myasthenia gravis) symptoms and triggers occurring longitudinally.

This study is designed to use the strengths of mobile smartphones which enable participant-driven real time capture of data manually and through augmented sensors such as video and audio, in order to better characterize MG symptoms and flares.

The study aims to enroll approximately 200 participants for approximately 9 months until analyzable data is available from at least 100 participants. Participants will complete in-app surveys for 3 months with, audiovisual recording of symptoms. This will take approximately 35 minutes per week after the initial survey.

Using their smartphones, potential participants will download the doc.ai research mobile app. There will be a web pre-screening link where potential participants will self-screen to see if they meet the basic eligibility criteria for this study. The recruitment tool for this trial is developed for diversity, fairness, and inclusion. With the aim to ensure diversity in the demographics of the trial to better understand the health needs of different populations. So, while some interested potential participants do qualify, they may not be invited into the trial due to these diversity requirements.

Patients with myasthenia gravis (MG) who meet the inclusion criteria will be invited to join this digital health trial. Participants will sign the e-consent and self-enroll into the study. Once their eligibility is confirmed by the study team (to ensure eligibility criteria and validity of participant i.e. eliminate robo sign-ins) they will be asked to take a selfie, provide documented proof of MG diagnosis, respond to a series of survey questions regarding their demographics, current health, medical history, and other MG related information.

Enrolled participants will have a daily brief check-in, 2 weekly check-ins and a weekly check-in which will include an audiovisual check-in, and will maintain an audiovisual diary to keep track of their symptoms, connect data, record their voice (to detect vocal symptoms: weakness, nasality) and take videos of their face (to detect facial symptoms: ocular, mouth droop) on a daily to weekly basis through the various data collecting modules in the doc.ai research app for the duration of their study participation. doc.ai's digital health trial platform will be leveraged to collect this data.

The study aims to enroll approximately 200 participants in approximately 9 months. It is expected that a minimum of 100 participants will be included in the final analysis as at any given time there will be a lag between potential participants expressing interest in the study, their eligibility being assessed by the PI, and participants completing all required study procedures.

At the end of their participation, participants will be asked to complete a questionnaire. After the participant has completed their final survey, they will be able to connect to a link redeemable as an Amazon.com gift card worth $250. All participants will also receive an end-of-trial-summary of the data that they had collected during the study. No medical advice or direction will be given based on this study.

In addition, in the final survey participants will be asked if they would be willing to complete a usability interview after their participation in this trial has ended. This subset of participants invited to be part of a follow-up usability interview will include those who complete all study required procedures and some who may not have completed all study required procedures, in order to assess usability experience of the app for the duration of their participation. Participants will be contacted at their end of their period of participation until a total of 10-15 participants successfully complete the usability interview. Participants who successfully complete the usability interview will receive a link for a $50 in Amazon.com gift card via the app.

For this study the data and, audio and video recordings will be captured directly on the doc.ai research app and securely stored on a HIPAA compliant cloud provider (Google Cloud Platform).

This data will be used to understand the patterns of symptoms and triggers in order to better characterize factors such as the length and timing of flares and any unique symptom patterns in order to create more objective measures of MG symptoms. Ultimately this data would be used to build a machine learning model that could predict MG symptom flares.

Primary Objective:

Use a collection of digital health modules on the smartphone to collect myasthenia gravis (MG) symptoms and triggers to better characterize symptom patterns and flares.

Secondary Objective:

Use the data collected to develop an A.I. model to detect and/or predict symptom flares.

Inclusion Criteria:

1. Must have a documented diagnosis of Myasthenia Gravis
2. Must have ocular (eye drooping) and/or bulbar (speech) symptoms
3. Must be over the age of 18
4. Must reside in the US for the duration of the study
5. Must be able to read, understand, and write in English
6. Must have a smartphone supported by the doc.ai research app (iOS and Android)

Exclusion Criteria:

None

Patients with myasthenia gravis (MG) who meet the inclusion criteria will be invited to join this digital health trial.

There will be a web pre-screening link where potential participants will self-screen to see if they meet the basic eligibility criteria for this study. The recruitment tool for this trial is developed for diversity, fairness, and inclusion. With the aim to ensure diversity in the demographics of the trial to better understand the health needs of different populations. So, while some interested potential participants do qualify, they may not be invited into the trial due to these diversity requirements.

Data will be reviewed, and analysis will be done by personnel of doc.ai, and the medical experts. Population-level results of the data analysis in the form of a presentation/report, as well as the resulting proof-of-concept predictive AI model, will be shared with UCB Biopharma (SRL) (who are funding this study). No participant PII or PHI will be shared with UCB Biopharma (SRL) or any other 3rd parties.

At the end of the study, upon completion of the analysis.