Identifying and quantifying heterogeneity in high content analysis: application of heterogeneity indices to drug discovery.

One of the greatest challenges in biomedical research, drug discovery and diagnostics is understanding how seemingly identical cells can respond differently to perturbagens including drugs for disease treatment. Although heterogeneity has become an accepted characteristic of a population of cells, in drug discovery it is not routinely evaluated or reported. The standard practice for cell-based, high content assays has been to assume a normal distribution and to report a well-to-well average value with a standard deviation.

Development of high-content imaging assays for lethal viral pathogens.

Filoviruses such as Ebola (EBOV) and Marburg (MARV) are single-stranded negative sense RNA viruses that cause acute hemorrhagic fever with high mortality rates. Currently, there are no licensed vaccines or therapeutics to counter filovirus infections in humans. The development of higher throughput/high-content primary screening assays followed by validation using the low-throughput traditional plaque or real-time PCR assays will greatly aid efforts toward the discovery of novel antiviral therapeutics.