click to enlarge The IN Cell Analyzer 2000 shows human embryonic stem cell–derived cardiomyocytes in a live multiplexed toxicity assay. (Source: GE Healthcare)

To see how compounds impact cells, many researchers now use high content approaches. Typically, this involves automatically capturing and photographing cells, and then applying image analysis. Researchers can look for changes in diseased cells or ones treated with a compound.

According to Jacob Tesdorpf, PhD, director, high content screening instruments and applications at PerkinElmer, Waltham, Mass., several trends exist in high-content screening for drug discovery and development, including the use of live cell assays and more in depth analysis.

For live cell assays, PerkinElmer developed the Operetta High Content Analysis System. This system’s software benefits from the new PhenoLOGIC machine learning, which Tesdorpf says, “enables customers to segment and classify by simply pointing and clicking on a few cells. The software then uses these training points to determine optimal segmentation and classification parameters.” 

Advances such as these will be welcome in drug discovery and development. As Tesdorpf explains, “Keeping cells alive during imaging, whilst being able to reliably analyze even the more subtle phenotypic changes, enables customers to utilize cell types, such as primary hepatocytes, whose responses to potential treatments are more predictive. Previously, these types of cells have proved difficult to image and analyze.”

Research scientists already reap many benefits from high-content approaches. In October 2010, Michael Freeley, PhD, of Trinity College in Dublin, won the first GE Healthcare High-Content Analysis award for work using the IN Cell Analyzer, essentially an automated microscope. Freeley and his colleagues—Dara Dunican, PhD, Gabor Bakos, Anthony Davies, PhD, Dermot Kelleher, MD, and Aideen Long, PhD—used the Analyzer to study the proteins involved when T cells migrate from blood to tissue, which happens in multiple sclerosis and other autoimmune diseases. “We could quickly see the cell shapes that were the most important in analyzing T-cell migration,” Freeley says. In fact, they did it about 20 times faster than would have been possible manually.

click to enlarge This interactive analysis of a neurite outgrowth data set using Genedata Screener High Content Analyzer includes: 1) plate overview; 2) individual plate drill-down; 3) result confirmation; and 4) feature selection and interactive analysis. (Source: Genedata)

Peter O’Brien, PhD, of University College in Dublin—a pathologist with experience in the pharmaceutical industry and academics—says that the IN Cell Analyzer enhances predictive toxicology from in vitro models. He says, “We compared high-content analysis to seven other well-published, conventional cell-based approaches to toxicology and found an order of magnitude improvement in predictiveness.” He adds that “the sensitivity of this approach let’s us assess morphology and track up to four biochemical parameters simultaneously.”

Integrating the Options
In January 2011, Genedata, headquartered Basel, Switzerland, is scheduled to unveil version 9 of Genedata Screener. This enterprise software, according to Stephan Heyse, PhD, head of Genedata Screener, “covers all of the high content technologies that are available at this moment in screening.” Heyse adds, “With readers becoming cheaper, companies acquire several of them to match specific assay technologies or throughput needs.” That creates the challenge of integrating and interpreting complex data, which is just one dimension of Genedata Screener.

Genedata Screener simplifies the integration of different high content systems—such as imagers of various kinds, image analysis packages, and image-management systems—with standard research processes, IT systems, and discovery workflows. “Our portfolio of standard, off-the-shelf integration solutions is continually evolving to meet market demands,” says Heyse. Even if a customer uses an instrument that is not yet part of the portfolio, Heyse says that they can usually make it work in just a couple of days.

Beyond gathering HCS data, Genedata Screener provides in-depth statistical analysis. At any point, though, a researcher can pull up the original image that was used and take a closer look. As Heyse says, “Scientists want to see the pixels because they can sometimes see more in an image than 1,000 data points can show.”

About the Author
Mike May is a publishing consultant for science and technology based in Houston, Texas.