Bioanalytics – Chemical
2019 PharmSci 360
Rare diseases are often under- or misdiagnosed. For those people that are accurately diagnosed, they often face a lack of treatment options for their rare disease at the end of a long diagnostic odyssey. With limited data and sparse, often heterogeneous, patient populations, it has been difficult to characterize the clinical manifestations, natural history and evolution of rare diseases to the extent necessary for clinical drug development.
Real-world data has the potential to change how we understand and diagnose rare diseases. From the perspective of those developing new therapeutics, real-world data can also inform trial design with more appropriate, patient-centric protocols. Real-world longitudinal datasets including objective laboratory testing and physician diagnostic coding from the patient care setting can provide “virtual natural histories” with insight into disease evolution, comorbidities, genotype-phenotype linkage, and the patient’s diagnostic journey, all critical elements for drug development for rare diseases.
This presentation provides a novel view of the development and application of longitudinal real-world datasets as a means of gaining insight and enabling clinical development into a rare disease by using examples derived from one the world’s largest real-world databases.