In the US alone, over 7,000 different rare diseases affect more than 30 million people[i]. Many of these conditions are life-threatening, and most do not have viable treatments. To address this, the pharma industry develops “orphan drugs” tailored for rare diseases, which do not attract the same level of research and development investment as more common conditions due to their small patient population size.
The US Orphan Drug Act[ii] (1983) defines a rare disease as a disease or condition that affects less than 200,000 people. To fill the treatment gap, the Orphan Drug Designation programme in the US and EU grants orphan status to rare drugs and biologics, offering incentives such as tax credits, user fee exemptions, and potential seven-year market exclusivity post-approval. However, drug development in rare diseases is often challenging, with complex biology and a lack of understanding of the natural history of many of these diseases making conducting clinical trials especially difficult.
The untapped potential of real-world data
With this information deficit driving the need for more research into such diseases, in 2019 the US Food and Drug Administration (FDA) published draft guidelines[iii] on the growing importance of natural history (NHx) research in helping drug development organisations react to unmet health needs, particularly in the context of rare diseases. Worldwide, the European Medicines Agency[iv] (EMA) and Japanese PMDA[v] have issued their own guidance, while the Australian TGA adopted the US FDA version in February 2023[vi].
Natural history studies use retrospective patient data from registries, medical records and prospective observational studies to better understand the course of the disease, its clinical outcomes, patient burden, and responses to current management.
These studies help drug developers understand diseases, their progression and responses to current therapies and identify both the available market for drug therapies and the most suitable patients for clinical trials. This enables developers to design and execute more efficient, adaptive trials with better dose selections and participant allocation.
The consequence is better trial outcomes, including increased participant engagement, more equitable socioeconomic access, and smaller and more efficient trials with fewer placebos and a greater proportion of participants accessing active drugs. Ultimately, natural history studies can lead to more accurate data, more successful outcomes and faster regulatory review. But how does this work in practice?
More accurate trials
Real-world studies can improve clinical trials by filling in the gaps with evidence that predict drug performance outside of a controlled environment. This data can be included at any point in the trial, supplementing participant and practitioner-generated data. Prospective and retrospective studies can draw meaningful conclusions about biomarkers, genetics and disease subtypes that might alter treatment performance. This is especially critical in oncology, where biomarker stratification drives precision medicine approaches and informs targeted therapy selection.
Diagnostics and prognostics can work together to inform trial course and participant responses to individual drugs. By accessing real-world data, developers can create robust clinical development plans that utilise confirmed epidemiological assumptions and clearly defined success criteria, essential for expedited regulatory submission and improved approval rates. In oncology trials, this approach can also reduce patient burden by minimising unnecessary procedures, streamlining monitoring, and increasing access to investigational treatments, ultimately improving the patient experience and retention.
Reducing placebo use of control arms in oncology trials with synthetic external control arms
Despite being the gold standard for drug testing and market safety, randomised clinical trials (RCTs) can pose challenges in patient recruitment and retention, especially for rare diseases, where population sizes are often too small to use an active control arm such as a placebo or even the current standard of care (SOC). Furthermore, patients may be more hesitant to participate if they know they may not receive the investigational therapy. This is particularly relevant in oncology where the treatment could potentially be lifesaving and as such introduces an important ethical dilemma for sponsors.
Data from NHx studies can be used to create an external control arm, allowing for comparison of the treated trial arm against pre-existing evidence for a placebo or SOC. The FDA guidance provides recommendations to sponsors and investigators considering the use of externally controlled clinical trials to provide evidence of the safety and effectiveness of a drug product, provided the external control group is similar to the testing group and valid epidemiology approaches are taken to reduce selection bias[vii].
For example, in the pivotal trial for tazemetostat, an EZH2 inhibitor for patients with histologically confirmed, metastatic or locally advanced epithelioid sarcoma (ES), an external control arm was established to study the natural history of ES patients who were taking standard therapies for the disease. This helped to understand unmet needs in the space and demonstrate the potential benefit of tazemetostat in a hard-to-study cancer population. A rare and aggressive cancer, epithelioid sarcoma is thought to account for approximately 1% of all soft tissue sarcomas in the US, while soft tissue sarcomas themselves make up just 1% of all adult cancers.[viii] In January 2020, based on the success of this Phase II trial, the FDA granted accelerated approval for tazemetostat in adults and paediatric patients aged 16 years and older with metastatic or locally advanced epithelioid sarcoma not eligible for complete surgical resection.
While RCTs remain the gold standard, the use of synthetic control arms in rare oncological disease research is growing.[ix] As of March 2025, there are 214 ongoing rare cancer trials with a historical control recorded in GlobalData’s Clinical Trials database. The majority of these (69%) are Phase II trials, followed by Phase I/II at 13%.[x]
Conclusion
The landscape of rare diseases is complex, with a significant number of individuals affected and a pressing need for improved diagnosis and treatment options. While advancements are being made, the challenges remain substantial, and continued efforts are necessary to address the unmet medical needs of patients with rare disorders.
Using the synthetic control arm method reduces the number of patients allocated to SOC and placebos, ensuring more patients have access to a potential lifesaving drug and allowing for faster trials and reduced time to market.
To learn more about the growing potential of real-world data in oncology, download the whitepaper below.
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