High-content screening moves to the front of the line

High-content screening (HCS) has been used in late-stage drug discovery for a decade. In the past few years, technological advances have expanded the role of HCS into the early stages of drug discovery, including high-throughput screening and hit-to-lead studies. More recently, computational advances in image analysis and technological advancements in general cell biology have extended the utility of HCS into target validation and basic biological studies, including RNAi screening. The use of HCS in target validation is expanding the work that can be done at this stage, especially the range of targets that can be characterized, and putting it into a more biological context.     

High-content screening: a new primary screening tool?

Given a pharmaceutical landscape in which fewer drugs are succeeding in reaching the market, pharmaceutical and biotechnological companies are seeking alternative screening methodologies that will be compatible with the large scale of current combinatorial chemical libraries. In this context, HCS has received considerable attention. Imaging technologies are playing an increasing role in the drug discovery and development process, and this role is projected to increase further in the future. Currently, these technologies are rarely applied in primary screening campaigns but, rather, are used in the processes that precede and follow primary screening. Imaging technologies are employed for target identification and validation, secondary screening, ADMET studies, and pharmacokinetic studies. Various labeling technologies are deployed for such imaging, including fluorescence, luminescence, PET and computer tomography (CT). This feature review discusses high-content analysis (HCA), including the HCS technology and methodology involved, and the future potential of HCA in the drug discovery process.     

An overview of cell phenotypes in HCS: limitations and advantages

Background: High-content screening (HCS) defines a series of cell-based multiparametric approaches for analysis at the single-cell level. In recent years, HCS has been increasingly pursued in the drug discovery field, adding to the repertoire of assay type, or increasing throughput in applications such as compound screening and mechanism of action studies, as well as for target identification/validation (siRNA screening). Obviously, as cells represent the objects of high-content assays, the outcome of any HCS assay is determined by the cell type: the choice of the most suitable cellular model for a given assay is a critical step that must follow biological and technical criteria. Method: Here, I discuss these criteria and report a systematic survey of cell types used so far in HCS, with particular emphasis on their strengths and drawbacks. I also illustrate my expectations for future advances on cellular models used in HCS. Conclusion: Despite the plethora of cell types potentially suitable for HCS, so far only a handful of cellular models (particularly human cancer cell lines) account for the great majority of HCS assays. In the future, the introduction of novel cell types, including engineered and primary cells, will further expand the potential of HCS for systems biology and drug discovery.     

Genetically Engineered Mouse Models for Drug Development and Preclinical Trials

Drug development and preclinical trials are challenging processes and more than 80% to 90% of drug candidates fail to gain approval from the United States Food and Drug Administration. Predictive and efficient tools are required to discover high quality targets and increase the probability of success in the process of new drug development. One such solution to the challenges faced in the development of new drugs and combination therapies is the use of low-cost and experimentally manageable in vivo animal models. Since the 1980’s, scientists have been able to genetically modify the mouse genome by removing or replacing a specific gene, which has improved the identification and validation of target genes of interest. Now genetically engineered mouse models (GEMMs) are widely used and have proved to be a powerful tool in drug discovery processes. This review particularly covers recent fascinating technologies for drug discovery and preclinical trials, targeted transgenesis and RNAi mouse, including application and combination of inducible system. Improvements in technologies and the development of new GEMMs are expected to guide future applications of these models to drug discovery and preclinical trials.     

Advances in high content screening for drug discovery

Cell-based target validation, secondary screening, lead optimization, and structure-activity relationships have been recast with the advent of HCS. Prior to HCS, a computational approach to the characterization of the functions of specific target proteins and other cellular constituents, along with whole-cell functions employing fluorescence cell-based assays and microscopy, required extensive interaction among the researcher, instrumentation, and software tools. Early HCS platforms were instrument-centric and addressed the need to interface fully automated fluorescence microscopy, plate-handling automation, and seamless image analysis. HCS has since evolved into an integrated solution for accelerated drug discovery by encompassing the workflow components of assay and reagent design, robust instrumentation for automated fixed-end-point and live cell kinetic analysis, generalized and specific BioApplication software (Cellomics, Pittsburgh, PA) modules that produce information on drug responses from cell image data, and informatics/bioinformatics solutions that build knowledge from this information while providing a means to globalize HCS throughout an entire organization. This review communicates how these recent advances are incorporated into the drug discovery workflow by presenting a real-world use case.     

The development of high-content screening (HCS) technology and its importance to drug discovery

ABSTRACT

Introduction: High-content screening (HCS) was introduced about twenty years ago as a promising analytical approach to facilitate some critical aspects of drug discovery. Its application has spread progressively within the pharmaceutical industry and academia to the point that it today represents a fundamental tool in supporting drug discovery and development.

Areas covered: Here, the authors review some of significant progress in the HCS field in terms of biological models and assay readouts. They highlight the importance of high-content screening in drug discovery, as testified by its numerous applications in a variety of therapeutic areas: oncology, infective diseases, cardiovascular and neurodegenerative diseases. They also dissect the role of HCS technology in different phases of the drug discovery pipeline: target identification, primary compound screening, secondary assays, mechanism of action studies and in vitro toxicology.

Expert opinion: Recent advances in cellular assay technologies, such as the introduction of three-dimensional (3D) cultures, induced pluripotent stem cells (iPSCs) and genome editing technologies (e.g., CRISPR/Cas9), have tremendously expanded the potential of high-content assays to contribute to the drug discovery process. Increasingly predictive cellular models and readouts, together with the development of more sophisticated and affordable HCS readers, will further consolidate the role of HCS technology in drug discovery.     

Prioritizing hits from phenotypic high-content screens

In the past decade, advances in the field of high-content screening (HCS) have provided researchers with a powerful new screening tool to observe treatment effects on multiple experimental parameters. While extremely useful, HCS has resulted in the collection of large datasets of increased complexity that require intensive analysis. Recently, approaches have been developed to analyze multi-parametric HCS data more completely and, when used in conjunction with RNA interference, target-based biochemistry and structural analysis, these approaches have begun to unlock the potential of this screening format in aiding drug discovery. This review illustrates how the combination of these technologies has been used to successfully drive the drug discovery process.     

Antisense and RNAi: powerful tools in drug target discovery and validation

Drug target discovery and validation are complex processes that require significant resource investments and impose a substantial economic burden on the pharmaceutical industry. Technologies that accelerate or enhance the precision of target selection are, therefore, in high demand. Traditional antisense and RNA interference (RNAi) technologies are powerful tools with applications in multiple phases of drug target discovery and validation. These approaches elicit potent and highly selective cleavage of a target mRNA, permitting evaluation of the role of the corresponding protein based on a loss-of-function phenotype. Incorporation of these technologies into high-throughput screens, in vitro biological assays and in vivo disease models provides valuable insight into gene function. Efforts are also underway to develop these agents as drugs. This review presents recent studies involving antisense and RNAi, and discusses how these technologies are facilitating target selection at various stages of the drug development process.     

High-content assays in oncology drug discovery: opportunities and challenges

High-content screening (HCS), a process that combines fluorescence microscopic imaging and automated image analysis, has had a significant impact on drug discovery since its introduction in the mid 1990s. The application of HCS within pharmaceutical drug discovery has become widespread, notably within oncology drug discovery. The trends, challenges and considerations for HCS that affect the successful and pragmatic implementation of this process in drug discovery will be outlined.     

High-content siRNA screening for target identification and validation

Background: Automated microscopy and image analysis have progressed tremendously over the past 10 years and opened up a new era of high-content screening. In parallel, RNA interference (RNAi) has revolutionized the functional analysis of genes. Objective: The focus of this review is screening of RNAi libraries, and in particular in screening of short interfering RNA (siRNA) libraries for target identification and validation in mammalian cell systems. Methods: Recent literature of high-content siRNA screening in oncology, in intracellular trafficking and infection biology, and in neurobiology is reviewed and placed in the context of a discussion on hit verification. Results/conclusion: Various methods have been established for the application of RNAi in mammalian cells also, which allows efficient and reproducible silencing of individual genes to gain functional information on each individual gene. Complex multi-parametric cell-based assays, combined with both technologies, provide an extraordinary valuable tool to help understand biological and pathological processes in a systematic way and discover new targets for pharmaceutical exploitation.     

Application of atelocollagen-mediated siRNA delivery for RNAi therapies

RNAi has rapidly become a powerful tool for drug target discovery and validation in an in vitro culture system and, consequently, interest is rapidly growing for extension of its application to in vivo systems, such as animal disease models and human therapeutics. Novel treatments and drug discovery in pre-clinical studies based on RNAi are currently targeting a wide range of diseases, including viral infections and cancers by the local administration of synthetic small interfering RNA (siRNA) that target local lesions. Recently, specific methods for the systemic administration of siRNAs have been reported to treat non-human primates or a cancer metastasis model. In vivo siRNA-delivery technology is a key hurdle to the successful therapeutic application of RNAi. This article reviews the non-viral delivery system of atelocollagen for siRNA, which could be useful for functional screening of the genes in vitro and in vivo, and will provide a foundation for further development of RNAi therapeutics.     

Imaged-based high-throughput screening for anti-angiogenic drug discovery

Recent developments in high-content screening (HCS) technologies make it an attractive alternative for anti-angiogenic drug discovery. HCS integrates high-throughput methodologies with automated multicolor fluorescence microscopy to collect quantitative morphological and molecular data from complex biological systems. Organotypic systems based on primary vascular cells model many facets of angiogenesis. The adaptation of these complex in vitro assay systems to high-throughput HCS formats with automated image acquisition enables large-scale chemical library screening campaigns. These HCS principles can be extended further to allow small molecule compounds in in vivo model organisms such as zebrafish. In this review we discuss the latest developments within automated image-based high-throughput screening of chemical libraries for anti-angiogenic compounds.     

High-content screening for the discovery of pharmacological compounds: advantages,challenges and potential benefits of recent technological developments

Importance of the field: Screening compounds with cell-based assays and microscopy image-based analysis is an approach currently favored for drug discovery. Because of its high information yield, the strategy is called high-content screening (HCS).

Areas covered in this review: This review covers the application of HCS in drug discovery and also in basic research of potential new pathways that can be targeted for treatment of pathophysiological diseases. HCS faces several challenges, however, including the extraction of pertinent information from the massive amount of data generated from images. Several proposed approaches to HCS data acquisition and analysis are reviewed.

What the reader will gain: Different solutions from the fields of mathematics, bioinformatics and biotechnology are presented. Potential applications and limits of these recent technical developments are also discussed.

Take home message: HCS is a multidisciplinary and multistep approach for understanding the effects of compounds on biological processes at the cellular level. Reliable results depend on the quality of the overall process and require strong interdisciplinary collaborations.     

Strategic Research Institute--first international siRNA conference. Prospect for new therapeutics and commercial opportunities for pharma and biotech. 24-25 March 2003, LaJolla,CA, USA

Small interfering RNAs (siRNAs), with their power to selectively silence genes, have gained much attention from biotech and pharmaceutical companies and investors. Key players in the field, from innovative biotech start-ups to big pharmaceutical companies, gathered at Strategic Research Institute's First International siRNA conference in the scenic Hilton La Jolla Torrey Pines. Topics addressed ranged from the latest technology advances and applications of RNA interference (RNAi) in drug discovery, to critical business issues such as intellectual property portfolio strategy and market prospects. While RNAi is indisputably accepted as a powerful tool in target validation and functional genomics, the concept of an siRNA drug is still viewed by big pharma companies as next-generation therapeutics. Yet challenges seem tractable. Several companies, such as Ribozyme Pharmaceuticals Inc, Alnylam Pharmaceuticals and Intradigm Corp, are working hard to prove that the bigger companies are being too conservative. The conference provided a clear vision of RNAi in drug discovery today, its potential and remaining challenges.     

High-content screening for the discovery of pharmacological compounds: advantages, challenges and potential benefits of recent technological developments

Importance of the field: Screening compounds with cell-based assays and microscopy image-based analysis is an approach currently favored for drug discovery. Because of its high information yield, the strategy is called high-content screening (HCS). Areas covered in this review: This review covers the application of HCS in drug discovery and also in basic research of potential new pathways that can be targeted for treatment of pathophysiological diseases. HCS faces several challenges, however, including the extraction of pertinent information from the massive amount of data generated from images. Several proposed approaches to HCS data acquisition and analysis are reviewed. What the reader will gain: Different solutions from the fields of mathematics, bioinformatics and biotechnology are presented. Potential applications and limits of these recent technical developments are also discussed. Take home message: HCS is a multidisciplinary and multistep approach for understanding the effects of compounds on biological processes at the cellular level. Reliable results depend on the quality of the overall process and require strong interdisciplinary collaborations.     

Primary cells and stem cells in drug discovery: emerging tools for high-throughput screening

Many drug discovery screening programs employ immortalized cells, recombinantly engineered to express a defined molecular target. Several technologies are now emerging that render it feasible to employ more physiologically, and clinically relevant, cell phenotypes. Consequently, numerous approaches use primary cells, which retain many functions seen in vivo, as well as endogenously expressing the target of interest. Furthermore, stem cells, of either embryonic or adult origin, as well as those derived from differentiated cells, are now finding a place in drug discovery. Collectively, these cells are expanding the utility of authentic human cells, either as screening tools or as therapeutics, as well as providing cells derived directly from patients. Nonetheless, the growing use of phenotypically relevant cells (including primary cells or stem cells) is not without technical difficulties, particularly when their envisioned use lies in high-throughput screening (HTS) protocols. In particular, the limited availability of homogeneous primary or stem cell populations for HTS mandates that novel technologies be developed to accelerate their adoption. These technologies include detection of responses with very few cells as well as protocols to generate cell lines in abundant, homogeneous populations. In parallel, the growing use of changes in cell phenotype as the assay readout is driving greater use of high-throughput imaging techniques in screening. Taken together, the greater availability of novel primary and stem cell phenotypes as well as new detection technologies is heralding a new era of cellular screening. This convergence offers unique opportunities to identify drug candidates for disorders at which few therapeutics are presently available.     

Aptamers as tools for target prioritization and lead identification

The increasing number of potential drug target candidates has driven the development of novel technologies designed to identify functionally important targets and enhance the subsequent lead discovery process. Highly specific synthetic nucleic acid ligands – also known as aptamers – offer a new exciting route in the drug discovery process by linking target validation directly with HTS. Recently, aptamers have proven to be valuable tools for modulating the function of endogenous cellular proteins in their natural environment. A set of technologies has been developed to use these sophisticated ligands for the validation of potential drug targets in disease models. Moreover, aptamers that are specific antagonists of protein function can act as substitute interaction partners in HTS assays to facilitate the identification of small-molecule lead compounds.     

Genomics in the real world

The term genomics has evolved into a catch-all term for a variety of information intensive biological methodologies. While the promise of genomics in the bio/pharmaceutical industry is great, its impact on the drug discovery pipeline has not yet been realized, excluding a few notable exceptions. As companies acquire several years of experience in working with genomic data, it is likely that the impact on the discovery process will slowly emerge as we learn to integrate these new technologies into individual discovery programs. It is clear that extracting novel biologically valid targets targets from exponentially growing amounts of sequence data requires time and considerable investment in biological research infrastructure. In order to accelerate the process of target validation, a variety of functional genomics technologies are also being developed to try to predict the effect of inhibitory compounds in advance of development. Resources spent on early stage exploratory efforts such as these can pay off by improving the success rate for screening and medicinal chemistry.