DRApp - Rare Disease App

According to the Brazilian Ministry of Health (2014), 13 million people in Brazil have some rare disease. Yet, according to Araújo et. al. (2018), rare neuromuscular diseases such as Duchenne Muscular Dystrophy affect 1 in 3500 people worldwide. Spinal Muscular Atrophy affects one in 7000 people. According to data collected by Fga (2009), one in 50 thousand people worldwide were diagnosed with Amyotrophic Lateral Sclerosis, characterizing a population of 12,000 people with ALS in Brazil. When we analyze the process of treating these diseases in countries with a context similar to Brazil, it is possible to see that access to treatment for patients varies significantly from region to region, and also regarding the access to practices for the follow-up of these patients. In general, motor and functional assessment scales and validated quality of life scales are adopted to identify the natural progress of the disease, and it is often necessary to share this information among people from a multidisciplinary team. Still, this process does not always guarantee adequate communication, the systematic use of methods that generate reliable information, or some degree of convergence from the point of view of data analysis for decision making. In this context, this initiative proposes to solve the following challenge:

• How can we use computer technology, machine learning, and solutions for mobile devices to assist in the process of capturing, storing, and monitoring the indicators generated by assessment scales in the context of treatment and care for patients with neuromuscular diseases?

Still, we understand that some problems complement our challenge, namely:

• How can we democratize access to monitoring the natural history of the disease, ensuring quality using technological resources?
• How can we use data intelligence to help understand this monitoring process?
• How can we share these results with the professionals involved, ensuring adequate communication while respecting data protection guarantees?

Our solution answers these questions and proposes an ecosystem for monitoring the natural history of rare diseases, such as ALS, SMA, and DMD, using motor, functional, and quality of life assessment scales. Furthermore, we suggest that making this type of digital solution democratic, connected, and accessible will allow more professionals to use the best technological resources to monitor their patients and, in a second moment, to extract suggestions for their medical strategies through data intelligence.

A digital platform that supports the process of motor, functional, and quality of life assessment of patients with rare neuromuscular diseases. This platform allows the monitoring of the natural history of the disease through the patient's journey through records of digitalized and standardized assessments.

The proposed solution allows physiotherapists to:

• register their patients with rare neuromuscular diseases

• record assessments of their patients according to consolidated scales

• ask questions about scales and how to evaluate each item

• include patient notes, photos, and videos

• monitor the progress of patients

With the development and wide use of our solution, it will be possible to:

• Improve the assessment process of patients with rare neuromuscular diseases

• Improve communication between professionals who attend to patients: medical staff and rehabilitation professionals

• Use AI resources to support decision making

• Provide a copy of the assessments to patients and their families and consequently allow the appropriation of data on the natural history of the disease

• Monitor the evolution of the disease and plan rehabilitation strategies

• Provide predictors about the course of the disease

• Analyze reliable data on the stages of the disease due to the systematization of the assessment process

• Improve patients' quality of life

Currently, physiotherapists who conduct assessments of patients with rare diseases take notes on paper and are often unaware of the consolidated scales to ensure quality assessments.

The proposed solution is an application that will guide the use of scales and the digitization of assessment results during the process. In addition to the scale items, physiotherapists can include photos, videos, and observations without worrying about storing, organizing, and classifying paper and files. Professionals will have at hand a powerful tool with all patient’s data, their assessments, and evolutions.

Patients with rare neuromuscular diseases and their families will be better served and access reports to follow the disease’s natural evolution.

Our team is composed of researchers from the fields of engineering (electrical, mechanical, computer) and health sciences (occupational therapists, physiotherapists, biologists). In the last ten years, we have been researching and developing technological solutions to support people with disabilities in their daily life activities (electronics for motorized wheelchairs, adapted interfaces for computer controls, accessible interface studies for interactive Digital TV). We have developed solutions for people with disabilities in educational activities (Scratch for the blind, accessible educational tablets), in addition to the development of solutions that support health professionals in caring for people with disabilities (wheelchair adaptation prescription system).

Regarding projects that attend to people with rare diseases, we started the development of the DRApp platform for people with Duchenne Muscular Dystrophy. With the support of Sarepta, it was possible to create the prototype of the solution.

This project’s team comprises mechanical and electrical engineers, computer scientists, physicists, occupational therapists, biologists, and designers specializing in technology applied to health.

At the moment, the financial incentive will cover a relevant part of our expenses for developing the platform. We are in the phase of structuring a pilot. The financial resources would allow us to overcome some barriers, such as (i) turning our prototype into a pilot version and expanding for tests all over Brazil  (ii) expansion of technical aspects, directing part of the resource to expand the team, and consequently, ensure a process of acceleration of the prototype development to the pilot phase and (ii) cultural aspects: with the resolution of the item (i) also it will be possible to ensure that more physiotherapists participate in the pilot phase, ensuring closer monitoring of users in this phase, and consequently, guaranteeing the Co-Design of the Solution. Thus allowing the implementation of a pilot for Duchenne Muscular Dystrophy disease.

Therefore, the partnership with MIT solve will promote our insertion in a group that discusses the technologies in our focus of interest at a high level—also allowing us to expand the possibilities of implementing the platform in other countries, mainly in a Latin American context in this first phase.

Currently, the process of monitoring the natural history of the disease is carried out through sessions that take place between the patient and a multidisciplinary rehabilitation team, usually formed by doctors, physiotherapists, nutritionists, occupational therapists, speech therapists, among others, and may be accompanied by the presence of guardians when the patient is a minor. This process relies on the use of motor and functional assessment scales, which suggest a specific rehabilitation program for each case that will be conducted by the physiotherapist and that, in the end, generates a score for classifying the progress of the disease. The process also includes professional records and the construction of a report that may or may not be formalized and may also include sharing with other health professionals. These records are almost always made analogically, using pen and paper. Still, in most cases, these scales were developed in other countries, written in another language, and are rarely addressed in higher education institutions. This makes physiotherapists often seek additional training for this type of tool. Our solution is innovative as it directly impacts the cultural aspects of this practice, as it allows the digitization of this process and, consequently, the storage of this data for a Computer-Assisted Rare Disease Monitoring practice. In this sense, we understand that this cultural and theoretical change implies a paradigm shift regarding clinical trials, favoring a more democratic and inclusive process for professionals who use the tool. This occurs from the patient's registration to the choices/indications of the most promising scales for the patient's current stage in the context of the disease. Furthermore, we understand that the data generated also allows us to identify deviations or changes in these scores, suggest practices adopted by other professionals who use the platform, and review possible inconsistencies in the monitoring process. In addition, we understand that innovation is favored by using a solution implemented for mobile devices, which aims to incorporate a large volume of data and machine learning to characterize the natural progress of the disease. Finally, there is an innovation from the health point of view, with the possibility of anticipating markers, such as the loss of the ability to walk for patients with Duchenne Muscular Dystrophy, for example, or the need for breathing aids.

This initiative has partner entities in the field of rare diseases in the Brazilian context. We understand that for the next year, our goals are related to implementing a pilot action with at least 50 physiotherapists who will attend Duchenne Muscular Dystrophy, SMA, or 50 ALS patients. The experimental design highlights the need to validate this solution in plural scenarios, which can allow interaction with professionals and patients with different demographic, disease history, and geolocation characteristics. Also, we emphasize that for the pilot, we also intend to value the plurality of professionals, considering their training, experience, and access to technological resources (connectivity and devices). Therefore, in this first year, we intend to have a pilot version with these professionals to follow up on their Duchenne Muscular Dystrophy patients for at least three months. For the next five years, we intend in Phase 1 to broaden the scope of the ecosystem to include Spinal Muscular Atrophy and Amyotrophic Lateral Sclerosis. IN Phase 2, we want to structure a database that allows the anonymized use of some indicators for the benefit of Phase 3 and the possibility of generating reports to share among health professionals and with the patient's family for each disease. In addition, in Phase 3, we will expand the use of the tool to make the solution more scalable so that we can include data intelligence. Finally, in Phase 4, the idea is to improve the use of Data Intelligence so that it is possible to guarantee aspects related to Business Intelligence and, at the same time, to structure APIs to enhance research in Brazil and with partners.

To measure the project’s progress in Phase 1, standardized questionnaires will be applied to assess the experience and usability quality of the 50 professionals who will participate in the pilot project and collect information to establish new requirements for the platform. In addition, we consider the platform’s performance under plural conditions of access and devices to be an essential metric. In phase 2, quality and consistency indicators will be applied to the database, and the reports will be generated based on the anonymized data. In addition, the evolution of patients assisted by the platform will be compared with a natural history of each of the diseases contemplated in the project to ensure that the platform generates the quality of life and a measurable positive impact on patients’ lives.

Our theory of change starts from the importance of understanding the evolution of diseases and the measurable impacts of interventions on this evolution.

The first positive short-term impact is the standardization of data collection and the creation of a comprehensive database on these patients.

From this database and machine learning tools, it will be possible to evaluate the most effective treatments for each patient profile.

Thus, data on the patient's condition, treatments, and changes in the situation, in the long term, will generate a reliable tool to support the decision-making process of professionals.

The project includes the use of some computational technologies. We understand that the solution must allow the integration of data storage. Therefore we intend to use cloud computing storage. Access to the data will be available anywhere under login and password to respect the guarantees of data protection. We will use messaging resources to interact with the Brazilian population (family members) who do not have e-mail and to authenticate and trigger important information/alerts. For this, we will implement a digital platform, which must include (i) a web application and (ii) an application for mobile devices. This application for mobile devices will use camera, GPS, accelerometer and computer vision resources to prepare the scenario in which the assessment scales will be conducted. For example: in a typical assessment routine, the physiotherapist should be able to record some patient movements with images and short videos, however, in other assessment items it may be necessary to monitor the time a task is completed or the maximum height in which a patient was able to dislocate his upper limbs. In this last item, for example, computer vision favors this registration with more precision (also using augmented reality for characterization on the mobile device screen). Still, we understand that the use of (iii) artificial intelligence allows to identify patterns among some patient indicators that share common characteristics and thus favor insights for the physical therapist OR assist in the verification of the patient's natural history, so that based on their own data it is possible to anticipate events such as loss of ability to walk.

Our working environment is essentially inclusive. We believe in diversity of gender, professions, and ethnicity. Diverse teams understand problems with  different points of view and result in better solutions. Our teams are mixed, with approximately 50% female and 50% male. We are mostly white, about 70%, but include black and mulatto. Our team's leaders are primarily female.

The users directly impacted by the solution are (i) physiotherapists, who will get help to apply the assessment of neuromuscular diseases and can count on a reliable tool for their practices to monitor these diseases and use reports to support their practices (ii) patients, who will receive quality treatment, with more reliable information and will have feedback with a lower error rate. Still, from the point of view of the quality of life, these patients will also benefit from the anticipation of markers. For example, by anticipating the loss of the ability to walk, it is possible to avoid the suffering of patients who could have a better quality of life with the use of a wheelchair OR allow the medical team to anticipate other paths for patient follow-up. (iii) higher education and research institutions, which will have an API for data consumption and for innovation and research (iv) the pharmaceutical industry, which will have a robust tool for monitoring its clinical trials (v) medical teams that will monitor a clinical case, sharing reliable information and that favor communication between professionals.

The main products expected for this solution involve the development of an ecosystem, initially for Duchenne Muscular Dystrophy, which includes the digitization of motor, functional, and quality of life assessment scales; sharing of information between professionals of the same clinical case; democratization of the use of reliable scales; possibility of experiencing a guided experience of using the scales by the app itself.

In addition, we understand that some services will also be offered (i) data intelligence and business intelligence for medical teams and the physiotherapist, (ii) data access API for research institutions, and (iii) report generation for pharmaceutical industries in the clinical trial period.

Partnerships with pharmaceutical companies that are interested in understanding the effectiveness of available treatments.

Partnerships with the government to offer an understanding of the most efficient investments to promote quality of life for these patients.

Sale of plans to health insurance operators.

In addition, we understand that upon reaching Phase 3 and Phase 4 of our solution (projection for five years), it will be possible to obtain a source of revenue through the provision of data/business intelligence services and access to an API for research/innovation.

The initial research that demonstrated the feasibility and necessity of the project was financed by the Sarepta Company, which cannot continue with the partnership due to the closure of its activities in Brazil.

At this time, the project was presented to two large Pharmaceutical Companies with activities of global reach. Both companies have shown strong interest in partnering, and conversations are moving forward.

In addition, our group has extensive experience in raising government funds through public biddings and other forms of grants and partnerships to bring the solutions developed by our laboratory to the public health system.