The cartoon is by Phil Hubbe, who has had MS since 1985.
The cartoon is by Phil Hubbe, who has had MS since 1985.
Source: Phil Hubbe (grafics); University Hospital Carl Gustav Carus Dresden

Using digital twins to help treat multiple sclerosis

Scientists in Dresden are expanding their digital health expertise in multiple sclerosis (MS) therapy and research with an ambitious scientific project - creating a "digital twin“ from data.

The Multiple Sclerosis Center (MSC) at the Department of Neurology at the University Hospital Carl Gustav Carus Dresden has been continuously collecting and evaluating patient data for around 20 years - a good basis for further development work. "With the 'Digital MS Twin”, we are igniting the next stage of our digital health concept for our patients," says Prof. Tjalf Ziemssen, founder and director of the MS Centre at the Department of Neurology.

The conditions are good: with around 1,000 patients per month, it is one of the largest academic multiple sclerosis centers in Germany and has had a continuously expanded MS-specific patient documentation system, as well as numerous digital applications in everyday care that are tested and routinely used. These include not only the tablet-supported query of subjective symptoms, such as the fatigue that often occurs with MS, but also digital tests on concentration, walking ability, vision and dexterity of the hands, which are carried out by those affected themselves.

A detailed examination of the walking function is also carried out every six months with special sensors in order to be able to detect any gait disorders in the course of the disease. In addition to digitalised test procedures, the regular documentation of the actual condition and the monitoring of the course of the disease also take place predominantly digitally, as does the management of the data within the framework of MS care.

"With the consent of our patients, we have built up an enormous treasure trove of data over the last 20 years, which continues to grow strongly," says Prof. Ziemssen, describing the good starting position for the newly launched project of the 'Digital MS Twin'. In medicine, the 'digital twin' is referred to as a virtual mirror or digital image of a sick person. In the future, the concept will enable practitioners to simulate personal medical histories and the individual state of health. In addition to medical knowledge and data-driven calculation methods, artificial intelligence will also be used. 

The perspective for MS patients and their treatment teams is promising: the concept of the 'digital twin' includes computer-assisted simulation and modelling, which, among other things, enables the prediction of disease progression and treatment success as well as individual disease management. For example, the individual drug tolerance for those being treated can be tested in advance and without risk, making these therapies faster and more targeted.

The digital twin idea comes from space travel

Photo
Draft future vision of a dashboard for multidimensional gait analysis in multiple sclerosis.
Source: Multiple Sclerosis Center; University Hospital Carl Gustav Carus Dresden

The concept of the twin strategy originally comes from space travel. In NASA's Apollo program, two identical spacecraft were built in the beginning - one flew into space, the other stayed on Earth. This made it possible to exactly mirror the conditions of the launched vehicle in case of technical problems. In industry, there was first talk of a 'digital twin' in 2003: as a virtual representation of a physical object, with the aim of evaluating and optimising it on the computer. Examples are online operation monitoring of process plants or real-time monitoring systems for detecting leaks in oil and water pipelines.

Since 2012, the number of research studies on 'digital twins' has been increasing, including in the fields of healthcare and medicine. One example is decision support in choosing a specific therapy, which can be applied especially in the field of chronic diseases such as MS. The concept of the 'Digital MS Twin' enables sufferers to see what consequences arise from the decision for a certain course-modifying therapy: How many and which checks become necessary and when - for example an MRI, blood checks. If there is a choice between several therapies, those treated can see what the respective therapy means for them in the future.

In order to get closer to this and other prediction possibilities, the team of the MSC is planning a 'Digital MS Twin', which is paired with the highly individual patient characteristics and reflects them as comprehensively as possible. The 'Digital MS Twin' is based on various MS characteristics - such as parameters from neurological examinations and functional tests, imaging, novel neurobiological and immunological data, and information about the patient's life circumstances and plans - which are analysed using artificial intelligence-based computational methods. This enables practitioners to combine and process large amounts of patient data from different sources and use it for disease management. With a clear presentation of pre-analysed patient data on a dashboard, the physician can optimally advise the person to be treated and make individualised clinical decisions together with the person to be treated.

In addition, the 'Digital MS Twin' as an intelligent system presents the clinical path, i.e. the concrete path of the patient through the various procedures of treatment in the MS centre. Thus, it not only serves as a guide through the individual treatment, but at the same time represents a quality assurance tool for doctors and especially for patients. In this way, patients can follow the path through their personal pathway and see whether they are being treated well. They thus actively participate in the quality improvement of their treatment process. Medical staff, in turn, have the opportunity to optimise the treatment steps on the basis of specific quality indicators. 

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Innovative dashboard supports patient-centred care

"A dashboard that presents the data generated on the basis of the 'digital twin' in a user-friendly way has enormous potential. In many medical subjects, it can strengthen doctor-patient communication and support patient-centred care," says Prof. Heinz Reichmann, Director of the Department of Neurology at Dresden University Hospital. "Our subject seems virtually predestined for this innovation. As Clinic Director and Dean of the Medical Faculty, I am proud that the team of the MS Centre has succeeded in developing and introducing successful concepts of digital medicine at an early stage, so that Dresden University Hospital has also taken on a pioneering role in this field."

"In our vision of the 'Digital MS Twin', it will be possible for those treating patients to view numerous treatment data both retrospectively and prospectively - for example through simulations using data-driven calculation methods - in an understandable and clearly arranged manner on a dashboard," explains Prof. Ziemssen. For those suffering from multiple sclerosis, the concepts of the 'digital MS twin' and the dashboard linked to it are of great importance because they enable individualised, innovative disease management. In this way, the complexity of this chronic, multidimensional disease can be better managed. "'Digital twins' could decisively advance the necessary implementation of this individualised management of multiple sclerosis. Even though the development of the concept for MS patients is currently still in its infancy, it will develop into a revolutionary tool that can improve diagnosis, monitoring and therapy as well as the well-being of our patients," says Prof. Ziemssen. Other expected effects are better prevention of the progression of the disease and a reduction of costs in health care.

The data basis for the realisation of the 'Digital MS Twin' is formed by various already existing building blocks: The MSC already collects many disease-relevant data digitally. Examples are data from clinical examinations and clinical assessments. In perspective, so-called digital biomarkers - which are data patterns that can be derived from various sources such as portable sensor systems - and novel neurobiological and immunological data should be available. These must not only meet the demands of high quality, but also those of data protection and data security. Once this basis has been created, algorithms are developed and tested. However, before 'digital twins' can be used in the care of MS patients, the effectiveness and safety of their methods must be proven. This requires scientific studies in real settings. As long as the 'Digital MS Twin' is still in the development phase, experts will consider it a trainee in patient care and proactively guide, supervise and monitor its development before it can be used in clinical routine.

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