During the last decade, we have seen tremendous progress in understanding the genetic basis of rare epilepsies. However, while genetic studies can be performed at scale, review of clinical data and outcomes still remains a largely manual tasks. This discrepancy has resulted in a significant "phenotyping gap" where the genetic cause of many rare epilepsies is known, but natural history is not well understood. Novel data science technologies using harmonized clinical data, including large-scale information from the Electronic Medical Records, allow for a systematic analysis of clinical data. In addition, progress has been made in enabling documentation of seizure and non-seizure outcomes in standardized ways. This enables frameworks to assess treatment effects, natural history, and comparative effectiveness studies to help better understand the longitudinal history and responses to new and established treatments in rare epilepsies.
Why would this research priority transform epilepsy research, our understanding of the epilepsies, and/or treatment of the epilepsies? :
Idea No. 169