January 15, 2014 (Vol. 34, No. 2)

Applying Multiplexing Capabilities to a Range of Drug Discovery Activities

Clinical failure in the pharmaceutical industry remains at a staggering 90%. Failed drugs are costly, both financially and in terms of human suffering. The debate rages on about how best to fix the drug discovery process, but there is a consistent notion that improving toxicological screening, using more relevant and predictive models, and identifying effective biomarkers before clinical development would make a dramatic impact.

As the discovery engine whirs, certain compounds are turned, through attrition, from samples in a library, to hits with activities in primary assays, to potential leads, and panels of physical and biological secondary assays define the compounds’ “pharmaco-reality” in the form of compound profiles. However, compounds do not choose themselves. They are continuously evaluated by the scientific brains of the process, and decisions about who passes through the gate are made based on the available information. So the real problem is generating the right data at the right moment to make the best decisions.

Creating the right data means using more physiologically relevant assays. The desire for physiological relevance in screening environments has driven the industry to increase the role of cell-based assays and expand the breadth and depth of information that can be gleaned from them.

One of the most significant advances in cell-based assays has been the development of high-content screening technologies. Measuring individual cells, making multiple measurements per cell, and measuring multiple cell populations per well are hallmarks of high-content approaches enabling the identification of complex phenotypes.

The first high-content technology was commercialized over a decade ago and was based on microscopy imaging. High-content imaging is optimized for adherent cell assay formats and generates primarily morphology phenotyping where the spatial location of probes define the size and shape of organelles, cells, and multicellular structures.

High-Content Screening

Recently, IntelliCyt introduced a new high-content screening platform, based on flow cytometry detection, called the iQue™ Screener.

Developed to complement high-content imaging, the iQue Screener is optimized for suspension assay formats with cells, beads, microbes, and mixtures. The platform provides a mechanism for subpopulation phenotyping—where multiple subpopulations are identified by size and density then correlated with intensities of multiple fluorescent probes on a per object basis.

Researchers can rapidly profile compound effects on nonadherent cell lines, including primary immune system cells, and determine molecular interactions using cell or bead-based assays.

The iQue Screener platform operates with ForeCyt® Data Acquisition and Analysis Software featuring low-volume, high-throughput, multiplexed endpoints in an automation-friendly system. Screening is carried out in terms of relevant metrics (hits or dose responses, which can be identified directly from the software), and multiplexed datasets are easily correlated for relevance.

So IntelliCyt can help to generate the right data, but what about providing information at the right point in the process? It is generally agreed that the earlier that information on the compound activity profile can be obtained, the better the decisions will be. Positioning an assay earlier in the drug discovery process requires higher capacity, reasonable cost, and the confidence that comes from scalable, reproducible, and statistically relevant sampling.

The iQue Screener’s patented technology is fast, enabling 384-well plates to be automatically sampled, analyzed, and visualized in as little as 15 minutes. All object measurements are collected simultaneously at a rate of up to 10,000 objects per second, achieving consistent statistical relevance even for relatively small subpopulations. Extremely sensitive, seven-decade dynamic range and hardware-based artifact rejection enable no-wash assay formats for many applications. Another key feature is the ability to sample as little as 1 µL with no dead volume, allowing miniaturization of sample volumes and much lower critical reagent usage.

Capitalizing on these unique attributes of the iQue Screener system, we present a case study of compound profiling where our robust, high-throughput profiling platform was used to generate information on five different cellular endpoints using a single microscale compound treatment.

Figure 1. Compound profiling with iQue Screener technology

Case Study

For this study, we used a compound library selected by Exquiron Biotech using its structure-activity relationship expansion protocol. Starting with a set of templates derived from five known cell cycle inhibitors, Exquiron computationally expanded the set into a virtual collection of ~13,000 compounds with structural features similar to cell-cycle modulators. A subset of 160 compounds was chosen from Exquiron’s library for a profiling feasibility experiment.

Preparation of compound treatment plates is often the most time-consuming and variable component of an assay. To save time, reduce variability, and improve the ability to cross-correlate results between multiple assays, we used a single 384-well compound treatment of Jurkat cells to generate a five-endpoint profile for each compound. Small aliquots from the compound treatment plate were used for staining with IntelliCyt’s MultiCyt™ Cell Cycle and Apoptosis kits. The resulting compound profile contained cell cycle status, caspase 3/7 activation, phosphatidyl serine surface expression, viability, and mitochondrial depolarization.

After treating Jurkat cells with the compounds in 50 µL volumes in 384-well plates, aliquots of the treated cells were transferred to two separate assay plates: one for cell cycle analysis and one for four-plex apoptosis analysis. The experimental workflow is shown in Figure 1. The kit chemistries utilized in this study are formulated in no-wash, mix-and-read assay formats with one-hour staining times.

Figure 2. Radar plots show that the seven identified compounds can be grouped into two categories which differ from mean distributions, as exemplified by cells treated with DMSO (red). Those altering the percentage of cells in the S phase do not show induction of apoptosis at the 24th timepoint (left panel). Compounds resulting in an arrest in the G2/M phase after the 24th timepoint induce apoptosis (right panel), similar to the canonical cell cycle inhibitors nocodazole and taxol.

From this study we were able to observe two apparent profiles for the compounds tested: 1) potential G2/M-phase cell cycle modulators that also induced apoptosis and 2) potential S-phase cell cycle modulators that did not induce apoptosis. Seven of the 160 compounds (4.4%) demonstrated perturbation of either the S-phase or G2/M phase of the cell cycle. Of these seven compounds, three demonstrated concomitant induction of all four apoptosis-specific markers. The remaining four compounds demonstrated cell cycle perturbation without evidence of apoptosis induction (Figure 2). Replicate measurements across different days showed high correlation demonstrating reproducibility of the experimental results (Figure 3).


Information gathered from multiplexed phenotypic screens enables the characterization and classification of compounds based on cellular efficacy, mechanism of action, and cytotoxicity. This information can be crucial to improving the success of potential chemical series as they move through the discovery process. Taking advantage of low assay volume requirements and multiplexed assays, we demonstrated a phenotypic screening technology that can be used as a powerful compound profiling platform. By aliquoting small volumes into multiple assay plates, an extensive phenotypic profile can be generated from a single compound treatment plate.

This not only results in cost savings both in terms of labor and material cost, but also enables researchers to uniquely cross-correlate results by using a single compound treatment to profile compounds with multiple assays. Whereas the primary target of this screen was to identify potential cell cycle modulators, parallel analysis in a multiparameter apoptosis assay resulted in additional valuable information, aiding in the classification of those compounds selected for further profiling in time-course and dose-response assays.

Figure 3. Correlation plots of two independent determinations at 20 µM. Plotted are the percentage of cells in the S phase (blue, left panel) or the G2/M phase (orange, right panel). Seven representative compounds with a difference >3 standard deviations from the mean (values indicated) are circled.

Kim Luu, Ph.D. ([email protected]), is manager, assay development at IntelliCyt. Daniela Brodbeck works at Exquiron Biotech.

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