In addition to these pharmacological approaches, bioinformatics coupled with large-scale data sets have driven the development of computational resources52,53 that can suggest candidate drugs in the FDA library from patterns of changes in gene expression. Moreover, evaluation of multiple drugs in multiple models might identify candidate drugs as add-on therapies that could be used more broadly than for just for rare genetic conditions. Indeed, a large number of epilepsy models have been or are being made from various genes identified in patients with rare epilepsies (eg, sodium channels, potassium channels, postsynaptic ligand-gated ion channels, synaptic proteins), which will provide patient-relevant models in which to assess new pharmacological strategies. These same models can be used to understand developmental compensation, transformation of the foci with time, and pharmacological sensitivity. It seems likely that some compensatory mechanisms will be shared across these different models and may inform treatment of refractory epilepsy. In addition to rodent models, use of companion models and organisms (fly, zebrafish, mice, iPSC-derived neuronal cultures, and organoids) could provide faster and more efficient drug screening43 as well as evaluation of compensatory mechanisms.