Special Medical Engineering Seminar
Circulating extracellular vesicles (EVs) contain a wealth of proteomic and genetic information, presenting an enormous opportunity for liquid biopsy. While microfluidics have been used to successfully isolate cells from complex samples, scaling these approaches for EV isolation has been limited by the low throughput and susceptibility to clogging of nanofluidics. Moreover, the analysis of EV biomarkers is confounded by substantial heterogeneity between patients and within a disease itself. To address these challenges, we developed a multichannel nanofluidic system to analyze crude clinical samples. Using this platform, we isolated EVs, profile the RNA cargo inside of these EVs, and apply a machine learning algorithm to generate predictive panels that could provide useful diagnostics for applications in traumatic brain injury and pancreatic cancer using both murine models and clinical samples. http://issadore.seas.upenn.edu/
The Issadore Lab's research focuses on the integration of microelectronics, microfluidics, nanomaterials and molecular targeting, and their application to medicine. This multidisciplinary approach enables them to explore new technologies to bring medical diagnostics from expensive, centralized facilities, directly to clinical and resource-limited settings. David has a PhD in Applied Physics from Harvard and did post-doctoral training at MGH in Systems Biology.