Microfluidic and Computational Tools for Neurodegeneration Studies

Understanding the molecular, cellular, and physiological components of neurodegenerative diseases (NDs) is paramount for developing accurate diagnostics and efficacious therapies. However, the complexity of ND pathology and the limitations associated with conventional analytical methods undermine research. Fortunately, microfluidic technology can facilitate discoveries through improved biomarker quantification, brain organoid culture, and small animal model manipulation. Because this technology can increase experimental throughput and the number of metrics that can be studied in concert, it demands more sophisticated computational tools to process and analyze results. Advanced analytical algorithms and machine learning platforms can address this challenge in data generated from microfluidic systems, but they can also be used outside of devices to discern patterns in genomic, proteomic, anatomical, and cognitive data sets. We discuss these approaches and their potential to expedite research discoveries and improve clinical outcomes through ND characterization, diagnosis, and treatment platforms.