High Content Phenotypic Characterization for Prostate Cancer Drug Discovery

The Sexton lab focuses primarily on phenotypic-based drug discovery and development for the interrelated set of disorders involving diabetes, obesity, metabolic syndrome, and associated complications. They use functional outcomes of tissues and cells to guide drug discovery around metabolic endpoints. The current strategy for drug development uses a combination of phenotypic and molecular target-driven approaches with core competencies in pancreatic islet technologies, fatty liver disease, and metabolic regulation in muscle tissue coupled with in vivo models of diabetes and obesity. The main technology focus is high content screening - an automated epifluorescence microscopy approach to biological imaging coupled with image analysis to yield quantitative and clinically relevant endpoints in cellular models of disease.

At Core Life Analytics we have a passion for the democratization of data science. Our StratoMineR platform gives biologists the ability to independently mine their or datasets, allowing them to leverage the full power of phenotypic screening & profiling methods.

Victor Wong has a strong background in using cell and molecular biology and physiological tools for various diseases areas, ranging from metabolic disorders, audiology and neuroscience. He completed one of his postdoctoral fellowships Weill Cornell Medicine using high-throughput (HTS) and high content screening (HCS) approaches. It was at this point where Victor realized a growing problem: HCS approaches precipitated a growing problem where the capacity for data analysis was overwhelmed by the speed at which the data was being generated. Victor joined Core Life Analytics looking to empower biologists to quickly find useful biological insights in large complex data to accelerate their discovery process.