High-Content Screening, Imaging, and Analysis

As the complexity of automated high-throughput assays has increased, the subsequent “high-content” assays return more information and allow the investigation of more scientific questions. The incorporation of automated imaging into high-throughput assays not only broadens scientific possibilities, but also creates some confusion over the terms used to refer to such work, such as high-content screening (HCS), high-content analysis (HCA), and high-content imaging (HCI). This article looks at how HCS, HCA, and HCI are essential today for advancing the drug discovery process.

A different emphasis

Though often used interchangeably, the terms HCS, HCA, and HCI can reflect different emphases when it comes to deriving multi-parametric, quantitative data from cells in an automated, high-throughput format. Imaging is common but not required, so HCI implies that high-content data are obtained by imaging. Use of the term HCS leans toward the idea of more samples processed and fewer parameters measured, whereas HCA or HCI suggests the opposite. “Users often have to compromise between the number of samples they run and the number of images they analyze per sample,” says Jacob Tesdorpf, Life Sciences Market Segment Leader at Revvity. “Some reserve the term HCS for experiments that screen many samples and but yield an optimized amount of data per sample.”

Some use HCA/HCI as a process to explore possible parameters for subsequent HCS. When you first start developing a high-content assay, it’s a good idea to extract as much data as possible, including multiple imaging magnifications, z-planes, or time points. Analyzing this information with the aim of refining the assay could be construed as HCA, notes Tesdorpf. “The resulting data and iterations of the experimental design enable you to choose the optimal settings for a higher-throughput screening assay, for which you want to reduce data volumes, time, and cost without sacrificing the scientific value,” he says.

High-content assays in drug discovery

High-content assays—with their capacity to quantify hundreds of cellular parameters in response to drug treatment—are particularly well-suited to phenotypic drug discovery, says Roger Clark, Head of High Throughput Screening at Charles River Laboratories. “Where we are seeing increasing value for our clients is deploying HCS at the early hit identification stage, within the context of true phenotypic screening,” says Clark. “Over recent years, we have seen an increasing resurgence in clients going after compounds or modulators that drive a particular cellular phenotype, rather than driving activity against a single defined molecular target,” he adds.

HCS is also useful at multiple points during the drug discovery process, from early hit identification or in vitro toxicology testing, to later-stage mechanistic profiling in complex cellular systems, notes Clark. “We leverage the unique power of HCS at each of these phases, combining image acquisition (on either wide-field or confocal devices) with image analysis techniques to extract maximum value from the data,” he says. “We have multiple examples of HCS and multi-parametric techniques moving drug discovery projects forward, where simpler ‘whole-well’ single end-point [assays] would not have answered the key experimental questions.” High-content screening assays are also adaptable throughout the process of scientific inquiry. “Additional markers can be added [to the same assay] to look at modulation of a second target, for example, if a hypothesis develops that needs to be explored,” says Clark.

Image-based high-content screening is often used in earlier stages of the drug discovery process, when screening compound libraries for efficacy and toxicity, notes Sebastian Peck, Senior Product Manager for Cellular Imaging at Molecular Devices. “It’s really important that if a drug is going to fail the screening process, that it fail fast,” he says. “The faster you can see what’s not going to work, the better, because every step of the way becomes more expensive.”

3D cultures in drug discovery

The increasing use of 3D cell cultures, such as organoids and spheroids, is changing the process of drug development. “Currently, a big paradigm shift is occurring in moving from 2D to 3D cell cultures in high-content drug screening,” says Peck. “If you’re screening for a drug to treat, say, cardiac or liver disease, organoids created from patient-derived cardiac cells will give you a much better idea of the drug’s efficacy and toxicity on that type of native tissue.”

Indeed, HCS using 3D cell cultures will play an important role in assessing and even predicting the toxicity of drug candidates going forward. “Damage to the heart is one of the most common side effects of anti-cancer drugs,” says Peck. “In order to predict cardiac toxicity, organoids provide a valuable model to test developing drugs or chemicals for potential toxic effects to the human heart.”

In addition to providing more physiological model systems, the use of 3D cultures in HCS may also reduce the amount of animal testing in the future, notes Peck. The U.S. Congress recently passed the FDA Modernization Act, which removes a 1938 federal mandate to perform toxicity testing in other animals prior to clinical trials in humans. Technological advances since 1938 have demonstrated that animal testing can be an inconsistent predictor of toxicity in humans. The use of modern cell-based assays, and 3D cultures such as organoids and spheroids derived from human tissues, offers scientifically rigorous alternatives for screening when suitable.

As the basic structural and functional unit of life, cells are central to drug discovery. The ability to assay cells in environments more similar to in vivo conditions will only serve to improve drug discovery. “The need to employ physiologically relevant models of disease has been recognized throughout the industry, and more recently cells are even used as therapies,” says Tesdorpf. “Therefore HCS plays an increasingly important role from target discovery to preclinical development.”