To examine the safety and efficacy of new pharmaceuticals, a multi-stage process involving drug discovery, animal studies, and human clinical trials is used. Rare disease medication development entails a lower number of patients, a higher proportion of children, and a more convoluted clinical presentation. Post-approval studies are intended to address a lot of faults that have been identified in rare disease clinical trials. Observational studies, pragmatic trials, and randomized controlled studies are all examples of post-approval research for rare disorders. Original data collecting studies and the utilization of secondary data are both examples of observational studies (retrospective studies). Original data collection can help retrospective investigations overcome restrictions caused by inadequate information in secondary data sources. Disease registries focus on specific health care outcomes associated with a single product and may include a comparator of an alternative therapy or therapies, whereas product-related registries focus on specific health care outcomes associated with a single product and may include a comparator of an alternative therapy or therapies.
Title : The foundation for rare disease and its role in the european rare disease research landscape
Daniel Scherman, Foundation for Rare Diseases, France
Title : The effect of Eupalinolide B on amyotrophic lateral sclerosis: A case report
Wang Huaixiu, Shanxi Provincial Hospital, China
Title : Progress related in genetic research on kawasaki disease
Jiao Fuyong, Shaanxi Provincial People’s Hospital, China
Title : Covid-19 seems to be Initiated by the heparan-sulfate dysregulation by coronavirus: The use of low-molecular- weight heparin (LMWH) can prevent and treat covid-19 when it Is used in early stages, as a heparan-sulfate-regulating medicine
Fereshteh Sedaghat, Sedaghat Memory Clinic, Iran (Islamic Republic of)
Title : Lumevoq gene therapy in leber hereditary optic neuropathy
Magali Taiel, GenSight Biologics, France
Title : Drug recommendation system using a collaborative filtering in machine learning
J. Somasekar, Jain University, India