Combinatorial Chemistry & High Throughput Screening - Volume 12, Issue 9, 2009

In the past decade, in vitro cell-based imaging has benefited from the maturing of automated devices and the advancement in image analysis tools. Applications of high content screening (HCS) have impacted both drug discovery and basic research in pharmaceutical industry and academic institutes. In this special issue dedicated to In Vitro Imaging, we are privileged to have some of the most distinguished movers and shakers of this field sharing their past experiences and their forward-thinking innovative development. This special thematic issue is divided into 3 sections. The first section includes practical applications and impact of HCS in Drug Discovery; and innovative new development, which will certainly impact the advancement of in vitro imaging.

Efficiency and accuracy in addressing drug safety issues proactively are critical in minimizing late-stage drug attritions. Discovery Toxicology has become a specialty subdivision of Toxicology seeking to effectively provide early predictions and safety assessment in the drug discovery process. Among the many technologies utilized to select safer compounds for further development, in vitro imaging technology is one of the best characterized and validated to provide translatable biomarkers towards clinically-relevant outcomes of drug safety. By carefully applying imaging technologies in genetic, hepatic, and cardiac toxicology, and integrating them with the rest of the drug discovery processes, it was possible to demonstrate significant impact of imaging technology on drug research and development and substantial returns on investment.

Building cellular models of disease based on the approach of Cellular Systems Biology (CSB)™ has the potential to improve the process of creating drugs as part of the continuum from early drug discovery through drug development and clinical trials and diagnostics. This paper focuses on the application of CSB to early drug discovery. We discuss the integration of protein-protein interaction biosensors with other multiplexed, functional biomarkers as an example in using CSB to optimize the identification of quality lead series compounds.

As technologies for high throughput and high content screening continue to evolve, new platforms for quantitative cellular imaging will play an increasingly important role in identifying and profiling lead compounds. To gain insight into the effects of a compound on cell morphology or intracellular events, it is necessary to have quality images and the ability to enumerate thousands of data points for statistical relevance. Imaging flow cytometry combines many of the features of flow cytometry, microscopy and imaging as well as a number of unique characteristics. The result is an instrument capable of highly quantitative analysis of cellular behaviors such as receptor internalization, phagocytosis, cell-cell communication, apoptosis and nuclear translocation. This promising new technology and unique type of flow cytometry provides enhanced capabilities for highly multiplexed assays. Here, we review the capabilities of the ImageStream imaging cytometer and discuss several applications relevant to compound screening and profiling.

Tumors are complex structures of malignant cells and stromal cells that function as an integrated system that promotes tumor progression. Immune cells and other stromal components serve vital cooperative functions that often support tumor growth and metastasis; stromal content and function are strongly associated with disease progression and clinical outcome in cancer patients. Cellular systems biology considers tissues and tumors, and the cells within them, as integrated and interactive networks that function in concert as a system. Assessment of tumors as a “system” within the system of a patient using the cellular systems biology approach has the potential to improve on the current diagnostic tools for breast cancer by creating high content profiles of an individual patient' tumor. The application of cellular systems biology (CSBTM) profiling to early drug discovery using cellular models of disease [1] and to drug development using the CellCiphrTM Cytotoxicity Profiling panels [2] can optimize the efficacy and decrease the potential toxicity of compounds taken into pre-clinical trials. However, it has become clear that patient sub-populations can respond differently to drug candidates in clinical trials due to patient variability. Therefore, cellular systems biology can also be a powerful approach to patient stratification for clinical trials and could become an important diagnostic tool. This review describes how the cellular systems biology approach can be applied to patient stratification and diagnostics in breast cancer, focusing on the advantages of quantifying functional biomarkers representing key tumor system processes in intact tissues from patients in order to make highly specific and sensitive predictions towards development of individualized medicine for breast cancer. We discuss the state-of-the-art of multiplexing of functional biomarkers in tissues and the practical utilization of the cellular systems biology approach in creating classifiers for patient stratification and diagnostics.

Over the last decade, imaging as a detection mode for cell based assays has opened a new world of opportunities to measure “phenotypic endpoints” in both current and developing biological models. These “high content” methods combine multiple measurements of cell physiology, whether it comes from sub-cellular compartments, multicellular structures, or model organisms. The resulting multifaceted data can be used to derive new insights into complex phenomena from cell differentiation to compound pharmacology and toxicity. Exploring the major application areas through review of the growing compendium of literature provides evidence that this technology is having a tangible impact on drug discovery and the life sciences.

Automated high content screening and analysis (HCS/HCA) technology solutions have become indispensable in expediting the pace of drug discovery. Because of the complexity involved in designing, building, and validating HCS/HCA platforms, it is important to design, build, and validate a HCS/HCA platform before it is actually needed. Managed properly, collaboration between technology providers and end users in research is essential in accelerating development of the hardware and software of new HCS/HCA platforms before they become commercially available. Such a collaboration results in the cost effective creation of new technologies that meet specific and customized industrial requirements. This review outlines the history of, and considerations relevant to, the development of the Cytometrix™ Profiling System by Cytokinetics, Inc. and the “Complete Imaging Solution” for high content screening, developed by Molecular Devices Corporation (MDC) (now MDS Analytical Technologies), from original conception and testing of various components, to multiple development cycles from 1998 to the present, and finally to market consolidation.

Widely diverse biological queries are now routinely analyzed on the various optical platforms: laser line scanners, nonconfocal imagers and confocal imagers. These analyses may be performed to query a limited number of samples or range to include the evaluation of a million samples as is the goal of many screening departments in the pharmaceutical drug discovery area. First we review the key elements that distinguish the optical pathway and the hardware features used amongst the three classifications of automated imaging platforms. Recognizing the need for both resolution and throughput and maximizing the use of optics we discuss some of the influences that address how to best match some of the more common biological assays with the current hardware imaging platforms. We describe here some considerations with respect to the biology, the cell types, and the goals of the screening efforts.

The field of High Content Screening (HCS) has evolved from a technology used exclusively by the pharmaceutical industry for secondary drug screening, to a technology used for primary drug screening and basic research in academia. The size and the complexity of the screens have been steadily increasing. This is reflected in the fact that the major challenges facing the field at the present are data mining and data storage due to the large amount of data generated during HCS. On the one hand, technological progress of fully automated image acquisition platforms, and on the other hand advances in the field of automated image analysis have made this technology more powerful and more accessible to less specialized users. Image analysis solutions for many biological problems exist and more are being developed to increase both the quality and the quantity of data extracted from the images acquired during the screens. We highlight in this review some of the major challenges facing automatic high throughput image analysis and present some of the software solutions available on the market or from academic open source solutions.

Biomedicine has seen tremendous advances in the field of image acquisition. The generation of digital images of high information content has become so straightforward and efficient that the volume of images accumulating in biomedical disciplines is posing significant challenges. Until now, conventional image analysis solutions are generally pixel-based and limited in the amount of information that they extract. However, a software system enabling the complex analysis of biomedical images should not impose restrictions on detection, classification and quantification of structures, but rather allow unlimited freedom to answer exhaustively all conceivable questions about the interactions and relationships between structures. Crucial to this is the precise and robust segmentation of relevant structures in digital micrographs. This challenge involves bringing structure, morphology and context into play. Based on the Definiens Cognition Network Technology®, solutions have been deployed for use in biomedicine. The technology is object-oriented, multi-scale, context-driven and knowledge-based. Images are interpreted on the properties of networked image objects, which results in numerous advantages. This approach enables users to bring in detailed expert knowledge and enables complex analyses to be performed with unprecedented accuracy, even on poor quality data or for structures exhibiting heterogeneous properties or variable phenotypes. Extracted structures are the basis for detailed morphometric, structural and relational measurements which can be exported for each individual structure. These data can be used for decision support or correlated against experimental or molecular data, thus bridging classical biomedicine with molecular biology. An overview of the technology is provided with examples from different biomedical applications.

High Content Screening (HCS) and High Content Analysis (HCA) have emerged over the past 10 years as a powerful technology for both drug discovery and systems biology. Founded on the automated, quantitative image analysis of fluorescently labeled cells or engineered cell lines, HCS provides unparalleled levels of multi-parameter data on cellular events and is being widely adopted, with great benefits, in many aspects of life science from gaining a better understanding of disease processes, through better models of toxicity, to generating systems views of cellular processes. This paper looks at the role of informatics and bioinformatics in both enabling and driving HCS to further our understanding of both the genome and the cellome and looks into the future to see where such deep knowledge could take us.

Flora Tang started biotech consulting on drug discovery operation and technology in 2007. Flora has extensive pharmaceutical experiences working at Amgen as Director of Research; SUGEN (subsidiary of Pharmacia) as Director of Discovery Technology; Eli Lilly; and GlaxoSmithKline. The scope of her work experiences involves high throughput biology using cutting-edge technologies and managing business operations. Flora started applying high content screening to drug discovery process soon after the inception of HCS.