With the advancement of precision medicine, genetic stratification – dividing patients into subgroups based on their specific mutations – is a key starting point in the drug development lifecycle for rare genetic diseases.
Incorporating a clear stratification plan is a key part of developing an effective Target Product Profile (TPP), which serves as a blueprint for product development by defining what “success” looks like early on, and aligning clinical, regulatory, and commercial strategies to meet patient needs, and regulatory and market requirements.
Chronic Kidney Disease (CKD) affects more than 10% of the population worldwide and is often associated with other conditions such as diabetes and hypertension. However, rare kidney diseases, although individually rare, collectively exert a notable impact on kidney health – accounting for an estimated 5–10% of CKD cases.
Despite their impact, rare kidney diseases often remain underdiagnosed and under-recognised within CKD care and policy frameworks. This raises critical questions: Why do so many rare kidney conditions go undiagnosed? Could rare kidney diseases account for more CKD cases than previously thought? And what would earlier diagnosis and targeted intervention mean for patients, health systems, and payers? This article aims to address these questions.
One of the main challenges faced by all companies conducting strategic planning for rare diseases is obtaining accurate data on the size of these often complex patient populations. The challenge of accurately estimating the prevalence of rare diseases is illustrated in the literature, where prevalence figures often span strikingly wide ranges – sometimes varying by orders of magnitude between studies. This level of uncertainty affects every step of the molecule-to-market planning cycle. The growing availability of large-scale genetic databases offers a solution to close the gap on wide ranging rare disease prevalence estimates, and can complement the data derived from other sources including the literature and information gathered from clinical practice.
HealthLumen has recently conducted a genetic database analysis study in partnership with Rallybio, a clinical-stage biotechnology company, focused on understanding the proportions of women at higher risk for Foetal and Neonatal Alloimmune Thrombocytopenia (FNAIT) across a broad population of diverse ancestries. The results demonstrated that the proportion of women at higher risk for FNAIT was […]
Genetic diseases are conditions caused by abnormalities in an individual’s DNA. They can be inherited from one or both parents, or can occur as a result of spontaneous genetic mutations. They may be caused by a mutation in a single gene (monogenic); by a chromosomal change where there are more or fewer copies than usual; […]
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