Transform rare disease challenges into opportunities for breakthroughs with our expert biometric services, your ally in pioneering next-generation treatments. We have helped our customers solve their specific rare disease trial challenges, such as tackling the statistical implications of small populations, slow recruitment rates, lack of controls due to ethical reasons and choice of suitable endpoints. Recently we supported an orphan drug application by providing both statistical and medical writing activities to a study investigating the safety and efficacy of recombinant human C1 inhibitor, for the treatment of acute attacks in patients with hereditary angioedema. In addition, we have experience of estimating prevalence for an orphan drug application in Parkinson's disease, and head and neck cancers.
At Quanticate, we have worked on various rare disease studies by providing support in data management, statistics, programming and medical writing services, using our experience from over 30 years of heritage as a leading biometric Clinical Research Organization (CRO).
Clinical research studies focusing on rare diseases face several unique challenges, often stemming from the rarity and complexity of these conditions. Addressing these challenges requires a multifaceted approach, including developing innovative trial designs, fostering collaborations across stakeholders, and advocating for more funding and awareness of rare diseases. Here are the top challenges typically encountered:
Partnering with a biometric CRO can provide specialized expertise, resources, and global reach, significantly mitigating the challenges inherent in rare disease research and enhancing the prospects of successful clinical trials.
As a Biometric CRO specializing in the statistical and data management aspects of clinical trials, we possess deeper expertise in biostatistics, data management, and bioinformatics, which is crucial for rare disease studies where data analysis can be complex and nuanced.
As most rare diseases are serious or life-threatening and have unmet medical needs, clinical trials must demonstrate efficacy in such a way as to minimize prolonged exposure to an ineffective treatment. To be able to design such a study, ideally an understanding of the disease history and suitability of endpoints is required, but often this information is lacking. This is frequently a difficultly found for gene therapies, as the endpoint choice can be further complicated by guidance asking for demonstration of a treatment outcome that virtually never occurs in the natural course of the disease, as in the case of haemophilia gene therapies.
These items will be discussed alongside approaches for the development of a suitable clinical assessment tool for the validation of suitable biomarkers, use of historical control data and an introduction to adaptive randomisation methods.
The data management of a rare disease study should ensure all data is captured in a manner that maximizes information collected, whilst minimizing the burden placed on often very sick patients. Commonly, long term surveillance of patients will be required, and these datasets must also be collected and cleaned in a controlled way. The following points should be considered:
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