Natural History and Real‐World Data in Rare Diseases: Applications, Limitations, and Future Perspectives

• Published in: Journal of clinical pharmacology Vol. 62; pp. S38 - S55
• Main Authors: Liu, Jing, Barrett, Jeffrey S., Leonardi, Efthimia T., Lee, Lucy, Roychoudhury, Satrajit, Chen, Yong, Trifillis, Panayiota
• Format: Journal Article
• Language: English
• Published: England 01.12.2022
• Subjects: Artificial Intelligence; Disease Progression; disease progression modeling; Drug Development; Humans; natural history; rare diseases; Rare Diseases - drug therapy; Rare Diseases - genetics; real‐world data; real‐world evidence; Research Design; rare diseases; real-world data; real-world evidence; natural history; disease progression modeling

Rare diseases represent a highly heterogeneous group of disorders with high phenotypic and genotypic diversity within individual conditions. Due to the small numbers of people affected, there are unique challenges in understanding rare diseases and drug development for these conditions, including pa...