How Statistical and Data Analysis Can Support Research Innovations in Rare Disease
Giles Partington, Lindsay Govan, Paddy O’Hara, Emily Foreman, and Jennifer Visser-Rogers | Phastar
A key challenge in drug development for rare disease is difficulty in obtaining relevant data due to a lack of suitable trial participants for each specific condition. Conservative estimates suggest there are 300 million people worldwide living with more than 6,000 clinically-defined rare diseases . However, this does not take into account rare cancers, nor rare bacterial or viral infectious diseases and poisonings, meaning these numbers are likely considerably higher. Despite this, analysis has shown the number of trials for rare diseases is limited, especially for non-cancer-related conditions .
While there is a need to expand the amount of rare disease clinical trials, we must also make sure we optimise those already running by enabling effective and efficient data analysis. Biometrics expertise can be deployed to support vital research innovations, increase trial success rates and help those living with rare diseases (between 3.5% and 5.9% of the global population at any given time¹).
In this article we will outline the challenges facing rare-disease research, explore how data can be optimised to help mitigate these challenges and support innovation, and share a real-world case study from a rare-disease trial at Great Street Ormond Street Hospital, London.
Originally published by Pharmafocus
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