In neurodegenerative diseases, misfolded protein aggregates accumulate in the brain and/or spinal cord; for example, Aβ and tau in Alzheimer’s disease (AD), α-synuclein in Parkinson’s disease (PD), and TDP-43 in amyotrophic lateral sclerosis (ALS). However, the mechanisms by which these protein aggregates exert toxicity and contribute to neurodegeneration and its associated symptoms remain unclear. Additionally, there is substantial evidence that inflammation plays a role in neurodegenerative diseases, but the specific contributions of neuroinflammatory conditions to the clinical phenotype, as well as the cell types primarily involved, are still unknown. Under these circumstances, researchers have developed somewhat artificial in vitro model systems for drug discovery screening. However, few, if any, of these drugs have been successful in clinical settings. 

Therefore, there is a need for clinically relevant bioassay systems that faithfully recapitulate human disease conditions to develop therapeutics that are effective in the real world. In recent years, there has been substantial progress in technologies related to genomics, proteomics, imaging, and AI-assisted analysis methods. These advancements may help identify and develop unique pathophysiologically relevant bioassay systems to discover new drug targets and enhance drug discovery, significantly increasing the probability of success compared to classical assays.