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Stéphane Auvin, child neurologist and epileptologist, discusses the role of natural history studies and collaborative data sharing in addressing the challenges rare diseases present in the quest for effective therapies

By Stéphane Auvin, M.D., Ph.D., child neurologist and epileptologist
full professor, Robert-Debré University Hospital and Paris-Cité University

Across the rare disease community, patients, families, clinicians, researchers and companies developing medicines share a common mission. We seek to bring safe and effective treatments to the community as quickly as possible while ensuring conclusions about benefit and risk remain reliable. This focus shapes how research is conducted and data is interpreted.

Historically, randomised controlled trials (RCTs) have served as the standard for evaluating whether a therapy works. In this model, some participants receive the investigational treatment while others receive a placebo or undergo a sham procedure (typically followed by treatment at a later date). Regulatory authorities, such as the US Food and Drug Administration (FDA) and the European Medicines Agency (EMA), review scientific evidence to decide whether new therapies can be approved, and rely on these comparisons to confirm that observed changes are truly due to treatment rather than chance or external influences.

Rare diseases present challenges to this traditional approach. Patient populations are small, disease courses may vary widely, and participation in research can place significant demands on families. Increasingly, the community is exploring how to use existing data more effectively so that fewer patients are assigned to control groups. At the same time, scientific rigour must remain the foundation of trial design. In rare diseases, where each data point represents a child or family’s experience, flawed methods or biased conclusions carry ethical consequences.

What is natural history?

To reduce patients in the control group of trials, researchers must first understand a disease’s natural progression in the absence of an investigational therapy. Natural history research helps establish this foundation.

Through structured observation and standardised assessments, these studies follow patients over time to document symptoms, development and daily functioning. This evidence helps researchers determine whether trial outcomes reflect the course of the disease or a potential treatment effect.

Data is typically gathered in two complementary ways. Patient registries collect ongoing reports on symptoms, developmental milestones and quality of life. Families often contribute directly, offering insights into day-to-day realities that may not be fully visible during clinical visits. Natural history studies, by contrast, are formal clinic-based programmes in which individuals undergo repeated neurological assessments, imaging and functional evaluations conducted by trained research teams using consistent methods, often across many years. Sometimes, these approaches are combined to incorporate both patient and clinician perspectives.

Importantly, natural history research is not based on a single assessment. Meaningful changes often become apparent only through repeated follow-up at different stages of disease. These insights help clinicians anticipate safety concerns, refine monitoring and identify relevant trial endpoints.

The synthetic control: a data-driven alternative

One important application of natural history data is the development of external control arms, also referred to as synthetic controls. In this approach, patient data from natural history studies are used as the comparison group for participants receiving an investigational therapy.

This model offers a potential benefit for patients and families. More participants, and in some cases all participants, may be able to receive the investigational treatment rather than being randomised to a placebo or sham procedure. In rare paediatric diseases, this can be particularly meaningful.

However, relying on synthetic controls is not a regulatory shortcut; it demands rigorous scientific integrity. The strength of this approach rests on the depth and quality of the underlying patient data. For the comparison to be meaningful, the historical data must carefully and accurately match the specific characteristics of the patients enrolled in clinical trials. Differences in assessment methods, follow-up intervals or patient characteristics can introduce bias. Regulators therefore require robust statistical methods, transparent study design and de-identified individual (“raw”) data to ensure that comparisons remain scientifically credible and unbiased. When applied appropriately, synthetic controls help balance methodological rigour with patient-centred trial approaches.

The necessity of longitudinal tracking in paediatric neurodevelopmental diseases

In paediatric neurodevelopmental conditions, the clinical course is rarely a straight line. Children may gain new skills, remain stable for a time, or lose abilities at different stages. Because progression is non-linear, short-term observation is often insufficient to determine whether changes seen during research reflect expected development or the genuine effects of a therapy.

This is where long-term, or longitudinal, data becomes critical. Unlike many neurodegenerative disorders that often follow a consistent downward trajectory, neurodevelopmental conditions require us to look for treatment-associated gains in function that exceed what the child was expected to achieve based on the known course of the condition.

For families, routine assessments can feel demanding. Yet consistent data collection over time is exactly what makes natural history studies valuable. These observations build the context needed to understand how the condition evolves over years rather than months. By documenting this complex journey, the community establishes the evidence required to recognise when a therapy is responsible for a child’s improvement.

The vital link: access to high-quality patient-level data

Natural history research is widely recognised as essential in rare disease. However, using these data in clinical trials often depends on whether companies developing medicines and researchers can responsibly access detailed patient-level information. Regulators require this level of evidence when considering alternative approaches such as external control arms.

When high-quality datasets remain siloed or are not prepared for responsible sharing, companies developing medicines may need to launch new observational studies rather than build on existing knowledge. This may lengthen development timelines and increase the likelihood that placebo or sham designs will be used.

Access to well-curated natural history data may make trial designs more efficient. In some cases, this can reduce the need for additional studies and help new treatments for severe rare diseases reach patients years earlier.

Strengthening research through collaboration

Natural history data is a critical resource for the rare disease community. To ensure that it benefits as many people as possible, collaboration across patients and families, clinicians, researchers and companies developing medicines is essential.

When data are collected and shared across organisations using appropriate standards and frameworks, it strengthens the research ecosystem, supports development of new therapies and can help enable trial designs that reduce unnecessary burden on families participating in research while maintaining scientific credibility. Irrespective of who is running it, families who join registries or natural history studies should ask whether informed consent forms allow their de-identified individual data to be shared for research or drug development purposes, helping support both ethical oversight and scientific progress.

Patient organisations, clinicians and academic investigators also play an important role in encouraging data practices that make datasets prepared for responsible sharing. They may also help families understand the benefits of sharing de-identified information with teams developing new medicines. By supporting appropriate access to patient-level information, the community can help create stronger foundations for evaluating potential treatment effects.

Building the path together

The path toward faster, more ethical and scientifically robust clinical trials is built on high-quality patient data–and the patient community is critical for this! By advocating for thoughtful data sharing today, the rare disease community can help shape a future in which clinical trial design better reflects both scientific realities and patient priorities.

Participation in natural history research, combined with responsible data sharing, is not only a contribution to knowledge but an important step toward advancing therapies that may transform lives.

For more information on Encoded Therapeutics visit https://encoded.com/

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