Each month, we gather partners from the MAGIC project to discuss aspects in relation to gene therapies. Readers will learn who the people behind the MAGIC Project are, why we are committed to advancing gene therapies, and how our roles in MAGIC are crucial for achieving better health outcomes for people living with muscular dystrophies. This time, we are speaking with Sergiu Siminiuc from Duchenne Data Foundation.

In brief words, please let us know who you are individually and on behalf of which project partner organization. 

My name is Sergiu Siminiuc, and I’m a Technical Officer at the Duchenne Data Foundation (DDF). In my role, I’m responsible for developing, managing, and overseeing the technical infrastructure and workflows that ensure data is accessible and reusable by a wide range of stakeholders in the dystrophinopathy community. 

DDF is a non-profit organization that was both initiated and is run by patients. It’s a global collaboration aimed at improving our understanding of dystrophinopathies: Duchenne and Becker muscular dystrophy. Our goal is to gather and share data to better understand the progression of these diseases, evaluate treatment effects, and address the needs and preferences of those living with these conditions, as well as their families. We focus on all aspects of their lives to ensure we’re making a meaningful impact. 

Why are you participating in the MAGIC project? How can your perspectives complement the MAGIC project goal to accelerate the development of genetic therapies for muscular dystrophies? 

We are proud to be part of the MAGIC consortium. At DDF, we believe that data-driven approaches are crucial to speeding up the development of therapies for neuromuscular diseases. Our expertise in dystrophinopathy data management, and particularly when it comes to responsible and FAIR (Findable, Accessible, Interoperable, and Reusable) data practices, enables us to contribute meaningfully in the consortium. We focus on ensuring that data management aligns with patients’ needs and preferences, which allows us to act as facilitators. Essentially, we help bridge the gap between raw information and its practical application in therapy development. 

What have been the current challenges regarding the development of genetic therapies for muscular dystrophies for you? 

The collection and use of data for the development of genetic therapies face numerous challenges. These span from technical issues related to data volume, complexity, and quality, to ethical concerns around privacy and equitable access, as well as regulatory and legal hurdles. During the MAGIC project we aim to make the dataset description (metadata) FAIR: Findable, Accessible, Interoperable and Reusable. This structured approach to data curation, will allow the discoverability and accessibility of the MAGIC data by humans and machines.

One of the biggest challenges in developing genetic therapies for muscular dystrophies is ensuring that data is managed in a way that is both secure and accessible. The challenge we try to tackle is in managing large amounts of data from different sources, making it findable, shareable, and reusable, all while adhering to strict security regulations.We need to ensure that this data is accessible and interoperable for researchers, clinicians, and other stakeholders. To do so we must balance the need for open data sharing with the responsibility to protect patient privacy and ensure that data is used ethically. This, in my opinion, is the biggest challenge for DDF.

What are the main outcomes (direct results) you expect from the project? 

Our goal is to make data easier to find, share, and reuse, all within a responsible and FAIR framework. This means we ensure data is Findable, Accessible, Interoperable, and Reusable, while also respecting the specific requirements of data users. We strictly follow European data protection and privacy regulations and adhere to the latest security standards.

The main outcomes we expect are:

• Enhanced collaboration between MAGIC partners through improved data accessibility and interoperability.
• Development of metadata models for improved data discovery both by humans and machines.
• Controlled accessibility of the data through a secure cloud server.
• Increased data reusability.

These outcomes will lead to higher-quality data, more streamlined workflows, and an increase in the impact and reuse of research data for improving care and accelerating therapeutic developments.

What are the expected impacts on your organisation from participating in the project? 

Our involvement in the MAGIC project is a fantastic opportunity to engage young researchers in the principles and practical implementation of responsible and FAIR data management. By doing so, we aim to maximize the value of the MAGIC data for future reuse. We see this as a chance to strengthen our role as a patient advocacy group within the FAIR ecosystem. We also look forward to gaining expertise in managing new data formats and developing innovative digital solutions, which will further enhance our contributions to the field.