Developing predictive assays: the phenotypic screening "rule of 3"

Opportunities and challenges in phenotypic drug discovery: an industry perspective

Phenotypic drug discovery (PDD) approaches do not rely on knowledge of the identity of a specific drug target or a hypothesis about its role in disease, in contrast to the target-based strategies that have been widely used in the pharmaceutical industry in the past three decades. However, in recent years, there has been a resurgence in interest in PDD approaches based on their potential to address the incompletely understood complexity of diseases and their promise of delivering first-in-class drugs, as well as major advances in the tools for cell-based phenotypic screening. Nevertheless, PDD approaches also have considerable challenges, such as hit validation and target deconvolution. This article focuses on the lessons learned by researchers engaged in PDD in the pharmaceutical industry and considers the impact of 'omics' knowledge in defining a cellular disease phenotype in the era of precision medicine, introducing the concept of a chain of translatability. We particularly aim to identify features and areas in which PDD can best deliver value to drug discovery portfolios and can contribute to the identification and the development of novel medicines, and to illustrate the challenges and uncertainties that are associated with PDD in order to help set realistic expectations with regard to its benefits and costs.

Turning the Light On in the Phenotypic Drug Discovery Black Box

In this issue, Drawnel et al. (2017) introduce the concept of a "molecular phenotype" and demonstrate how "big data" coming from gene expression profiling, combined with signaling pathway information, small-molecule chemical information, preclinical animal models, and clinical samples can empower phenotypic discovery at several critical levels.

Label-Free Dynamic Mass Redistribution and Bio-Impedance Methods for Drug Discovery

Label-free biosensors are increasingly employed in drug discovery. Cell-based biosensors provide valuable insights into the biological consequences of exposing cells and tissues to chemical agents and the underlying molecular mechanisms associated with these effects. Optical biosensors based on the detection of dynamic mass redistribution (DMR) and impedance biosensors using cellular dielectric spectroscopy (CDS) capture changes of the cytoskeleton of living cells in real time. Because signal transduction correlates with changes in cell morphology, DMR and CDS biosensors are exquisitely suited for recording integrated cell responses in an unbiased, yet pathway-specific manner without the use of labels that may interfere with cell function. Described in this unit are several experimental approaches utilizing optical label-free system capturing dynamic mass redistribution (DMR) in living cells (Epic System) and an impedance-based CDS technology (CellKey). In addition, potential pitfalls associated with these assays and alternative approaches for overcoming such technical challenges are discussed. © 2017 by John Wiley & Sons, Inc.

Live-single-cell phenotypic cancer biomarkers-future role in precision oncology?

The promise of precision and personalized medicine is rooted in accurate, highly sensitive, and specific disease biomarkers. This is particularly true for cancer-a disease characterized by marked tumor heterogeneity and diverse molecular signatures. Although thousands of biomarkers have been described, only a very small number have been successfully translated into clinical use. Undoubtedly, there is need for rapid, quantitative, and more cost effective biomarkers for tumor diagnosis and prognosis, to allow for better risk stratification and aid clinicians in making personalized treatment decisions. This is particularly true for cancers where specific biomarkers are either not available (e.g., renal cell carcinoma) or where current biomarkers tend to classify individuals into broad risk categories unable to accurately assess individual tumor aggressiveness and adverse pathology potential (e.g., prostate cancer), thereby leading to problems of over-diagnosis and over-treatment of indolent cancer and under-treatment of aggressive cancer. This perspective highlights an emerging class of cancer biomarkers-live-single-cell phenotypic biomarkers, as compared to genomic biomarkers, and their potential application for cancer diagnosis, risk-stratification, and prognosis.

High content analysis in amyotrophic lateral sclerosis

Amyotrophic lateral sclerosis (ALS) is a devastating disease characterized by the progressive loss of motor neurons. Neurons, astrocytes, oligodendrocytes and microglial cells all undergo pathological modifications in the onset and progression of ALS. A number of genes involved in the etiopathology of the disease have been identified, but a complete understanding of the molecular mechanisms of ALS has yet to be determined. Currently, people affected by ALS have a life expectancy of only two to five years from diagnosis. The search for a treatment has been slow and mostly unsuccessful, leaving patients in desperate need of better therapies. Until recently, most pre-clinical studies utilized the available ALS animal models. In the past years, the development of new protocols for isolation of patient cells and differentiation into relevant cell types has provided new tools to model ALS, potentially more relevant to the disease itself as they directly come from patients. The use of stem cells is showing promise to facilitate ALS research by expanding our understanding of the disease and help to identify potential new therapeutic targets and therapies to help patients. Advancements in high content analysis (HCA) have the power to contribute to move ALS research forward by combining automated image acquisition along with digital image analysis. With modern HCA machines it is possible, in a period of just a few hours, to observe changes in morphology and survival of cells, under the stimulation of hundreds, if not thousands of drugs and compounds. In this article, we will summarize the major molecular and cellular hallmarks of ALS, describe the advancements provided by the in vitro models developed in the last few years, and review the studies that have applied HCA to the ALS field to date.

Induced pluripotent stem cell technology: a decade of progress

Since the advent of induced pluripotent stem cell (iPSC) technology a decade ago, enormous progress has been made in stem cell biology and regenerative medicine. Human iPSCs have been widely used for disease modelling, drug discovery and cell therapy development. Novel pathological mechanisms have been elucidated, new drugs originating from iPSC screens are in the pipeline and the first clinical trial using human iPSC-derived products has been initiated. In particular, the combination of human iPSC technology with recent developments in gene editing and 3D organoids makes iPSC-based platforms even more powerful in each area of their application, including precision medicine. In this Review, we discuss the progress in applications of iPSC technology that are particularly relevant to drug discovery and regenerative medicine, and consider the remaining challenges and the emerging opportunities in the field.

Phenotypic Screen for Cardiac Regeneration Identifies Molecules with Differential Activity in Human Epicardium-Derived Cells versus Cardiac Fibroblasts

Activation and proliferation of resident cardiac progenitor cells has therapeutic potential to repair the heart after injury. However, research has been impeded by a lack of well-defined and characterized cell sources and difficulties in translation to screening platforms. Here, we describe the development, validation, and use of a 384-well phenotypic assay in primary human epicardium-derived cells (EPDCs) to identify compounds that induce proliferation while maintaining the progenitor phenotype. Using this assay, we screened 7400 structurally diverse compounds where greater than 90% are biologically annotated and known to modulate a broad range of biological targets. From the primary screen, we identified and validated hits and expanded upon the lead molecules of interest. A counterscreen was developed in human cardiac fibroblasts to filter out compounds with a general proliferative effect, after which the activity of selected molecules was confirmed across multiple EPDC donors. To further examine the mechanism of action of compounds with annotated targets, we performed knockdown experiments to understand whether a single known target was responsible for the proliferative effect, confirming results with protein expression and activity assays. Here, we were able to show that the annotated targets of compounds of interest were not responsible for the proliferative effect, which highlights potential differences in cell types and signaling pathways and possible polypharmacology. These studies demonstrate the feasibility of using relevant human primary cells in a phenotypic screen to identify compounds as novel biological tools and starting points for drug discovery projects, and we disclose the first small molecules to proliferate human primary EPDCs.

Discovery of a Chemical Probe Bisamide (CCT251236): An Orally Bioavailable Efficacious Pirin Ligand from a Heat Shock Transcription Factor 1 (HSF1) Phenotypic Screen

Phenotypic screens, which focus on measuring and quantifying discrete cellular changes rather than affinity for individual recombinant proteins, have recently attracted renewed interest as an efficient strategy for drug discovery. In this article, we describe the discovery of a new chemical probe, bisamide (CCT251236), identified using an unbiased phenotypic screen to detect inhibitors of the HSF1 stress pathway. The chemical probe is orally bioavailable and displays efficacy in a human ovarian carcinoma xenograft model. By developing cell-based SAR and using chemical proteomics, we identified pirin as a high affinity molecular target, which was confirmed by SPR and crystallography.

Enabling 1536-Well High-Throughput Cell-Based Screening through the Application of Novel Centrifugal Plate Washing

Cell-based assays have long been important within hit discovery paradigms; however, improving the disease relevance of the assay system can positively affect the translation of small-molecule drug discovery, especially if adopted in the initial hit identification assay. Consequently, there is an increasing need for disease-relevant assay systems capable of running at large scale, including the use of induced pluripotent stem cells and donor-derived primary cells. Major hurdles to adopting these assays for high-throughput screening are the cost, availability of cells, and complex protocols. Miniaturization of such assays to 1536-well format is an approach that can reduce costs and increase throughput. Adaptation of these complex cell assays to 1536-well format brings major challenges in liquid handling for high-content assays requiring washing steps and coating of plates. In addition, problematic edge effects and reduced assay quality are frequently encountered. In this study, we describe the novel application of a centrifugal plate washer to facilitate miniaturization of a range of 1536-well cell assays and techniques to reduce edge effects, all of which improved throughput and data quality. Cell assays currently limited in throughput because of cost and complex protocols may be enabled by the techniques presented in this study.

Progress does not just come in giant leaps: adapting techniques for the study of inflammation to novel applications

INTRODUCTION

Discussion of the relevance of suitable experimental models for the effective translation of drug effects to clinical inflammatory diseases has a long history. Much emphasis is placed these days on genetically transformed mice, which may have developmental drawbacks. But are established models redundant?

FINDINGS

Drawn from personal experience, examples are provided of the success of tinkering with technology in the context of inflammation. These include the use of specific dietary deficiency conditions, the development of new applications for established drugs and the introduction of a variety of readouts to assess outcome in studies on established disease models. Such approaches have been used to demonstrate inflammation-modulating effects of prostaglandin E, in the development of ebselen, for the introduction of immunomodulatory macrolide drugs and in new approaches to the therapy of multiple sclerosis.

CONCLUSION

Fine tuning of experimental approaches and evaluation technologies can often still provide innovative, clinically relevant insights into the potential beneficial effects of drugs and pharmacological agents.

Screening out irrelevant cell-based models of disease

The common and persistent failures to translate promising preclinical drug candidates into clinical success highlight the limited effectiveness of disease models currently used in drug discovery. An apparent reluctance to explore and adopt alternative cell- and tissue-based model systems, coupled with a detachment from clinical practice during assay validation, contributes to ineffective translational research. To help address these issues and stimulate debate, here we propose a set of principles to facilitate the definition and development of disease-relevant assays, and we discuss new opportunities for exploiting the latest advances in cell-based assay technologies in drug discovery, including induced pluripotent stem cells, three-dimensional (3D) co-culture and organ-on-a-chip systems, complemented by advances in single-cell imaging and gene editing technologies. Funding to support precompetitive, multidisciplinary collaborations to develop novel preclinical models and cell-based screening technologies could have a key role in improving their clinical relevance, and ultimately increase clinical success rates.

Inflammatory pathway network-based drug repositioning and molecular phenomics

Inflammation is a protective biological response to body/tissue damage that involves immune cells, blood vessels and molecular mediators. In this work, we constructed the pathway network of inflammation, including 11 sub-pathways of inflammatory factors. Pathway-based network efficiency and network flux were adopted to evaluate drug efficacy. By using approved and experimentally validated anti-inflammatory drugs as training sets, a predictive model was built to screen potential anti-inflammatory drugs from approved drugs in DrugBank. This drug repositioning approach would bring a fast and cheap way to find new indications for approved drugs. Moreover, molecular phenomics profiles of the expression of inflammatory factors will provide new insight into the drug mechanism of action.

SD, Verho O, Dandapani S, Wagner BK, Clemons PA, Booker-Milburn K, Boskovic ZV, Schreiber SL. Real-Time Biological Annotation of Synthetic Compounds

Organic chemists are able to synthesize molecules in greater number and chemical complexity than ever before. Yet, a majority of these compounds go untested in biological systems, and those that do are often tested long after the chemist can incorporate the results into synthetic planning. We propose the use of high-dimensional "multiplex" assays, which are capable of measuring thousands of cellular features in one experiment, to annotate rapidly and inexpensively the biological activities of newly synthesized compounds. This readily accessible and inexpensive "real-time" profiling method can be used in a prospective manner to facilitate, for example, the efficient construction of performance-diverse small-molecule libraries that are enriched in bioactives. Here, we demonstrate this concept by synthesizing ten triads of constitutionally isomeric compounds via complexity-generating photochemical and thermal rearrangements and measuring compound-induced changes in cellular morphology via an imaging-based "cell painting" assay. Our results indicate that real-time biological annotation can inform optimization efforts and library syntheses by illuminating trends relating to biological activity that would be difficult to predict if only chemical structure were considered. We anticipate that probe and drug discovery will benefit from the use of optimization efforts and libraries that implement this approach.

Phenotypic Assessment and the Discovery of Topiramate

The role of phenotypic assessment in drug discovery is discussed, along with the discovery and development of TOPAMAX (topiramate), a billion-dollar molecule for the treatment of epilepsy and migraine.

Next-generation phenotypic screening

Phenotypic drug discovery (PDD) strategies are defined by screening and selection of hit or lead compounds based on quantifiable phenotypic endpoints without prior knowledge of the drug target. We outline the challenges associated with traditional phenotypic screening strategies and propose solutions and new opportunities to be gained by adopting modern PDD technologies. We highlight both historical and recent examples of approved drugs and new drug candidates discovered by modern phenotypic screening. Finally, we offer a prospective view of a new era of PDD underpinned by a wealth of technology advances in the areas of in vitro model development, high-content imaging and image informatics, mechanism-of-action profiling and target deconvolution.

Novel drug discovery for Chagas disease

INTRODUCTION

Chagas disease is a chronic infection associated with long-term morbidity. Increased funding and advocacy for drug discovery for neglected diseases have prompted the introduction of several important technological advances, and Chagas disease is among the neglected conditions that has mostly benefited from technological developments. A number of screening campaigns, and the development of new and improved in vitro and in vivo assays, has led to advances in the field of drug discovery.

AREAS COVERED

This review highlights the major advances in Chagas disease drug screening, and how these are being used not only to discover novel chemical entities and drug candidates, but also increase our knowledge about the disease and the parasite. Different methodologies used for compound screening and prioritization are discussed, as well as novel techniques for the investigation of these targets. The molecular mechanism of action is also discussed.

EXPERT OPINION

Technological advances have been executed with scientific rigour for the development of new in vitro cell-based assays and in vivo animal models, to bring about novel and better drugs for Chagas disease, as well as to increase our understanding of what are the necessary properties for a compound to be successful in the clinic. The gained knowledge, combined with new exciting approaches toward target deconvolution, will help identifying new targets for Chagas disease chemotherapy in the future.

The Power of Sophisticated Phenotypic Screening and Modern Mechanism-of-Action Methods

The enthusiasm for phenotypic screening as an approach for small-molecule discovery has increased dramatically over the last several years. The recent increase in phenotype-based discoveries is in part due to advancements in phenotypic readouts in improved disease models that recapitulate clinically relevant biology in cell culture. Of course, a major historical barrier to using phenotypic assays in chemical biology has been the challenge in determining the mechanism of action (MoA) for compounds of interest. With the combination of medically inspired phenotypic screening and the development of modern MoA methods, we can now start implementing this approach in chemical probe and drug discovery. In this Perspective, we highlight recent advances in phenotypic readouts and MoA determination by discussing several case studies in which both activities were required for understanding the chemical biology involved and, in some cases, advancing toward clinical development.

Patient-Specific Induced Pluripotent Stem Cells for Disease Modeling and Phenotypic Drug Discovery

In vitro cell models are invaluable tools for studying diseases and discovering drugs. Human induced pluripotent stem cells, particularly derived from patients, are an advantageous resource for generating ample supplies of cells to create unique platforms that model disease. This manuscript will review recent developments in modeling a variety of diseases (including their cellular phenotypes) with induced pluripotent stem cells derived from patients. It will also describe how researchers have exploited these models to validate drugs as potential therapeutics for these devastating diseases.

Unknown unknowns in biomedical research: does an inability to deal with ambiguity contribute to issues of irreproducibility?

The credibility and consequent sustainability of the biomedical research "ecosystem" is in jeopardy, in part due to an inability to reproduce data from the peer-reviewed literature. Despite obvious and relatively inexpensive solutions to improve reproducibility-ensuring that experimental reagents, specifically cancer cell lines and antibodies, are authenticated/validated before use and that best practices in statistical usage are incorporated into the design, analysis, and reporting of experiments-these are routinely ignored, a reflection of hubris and a comfort with the status quo on the part of many investigators. New guidelines for the peer review of publications and grant applications introduced in the past year, while well-intended, lack the necessary consequences, e.g., denial of funding, that would result in sustained improvements when scientific rigor is lacking and/or transparency is, at best, opaque. An additional factor contributing to irreproducibility is a reductionist mindset that prioritizes certainty in research outcomes over the ambiguity intrinsic to biological systems that is often reflected in "unknown unknowns". This has resulted in a tendency towards codifying "rules" that can provide "yes-no" outcomes that represent a poor substitute for the intellectual challenge and skepticism that leads to an awareness and consideration of "unknown unknowns". When acknowledged as potential causes of unexpected experimental outcomes, these can often transition into the "knowns" that facilitate positive, disruptive innovation in biomedical research like the human microbiome. Changes in investigator mindset, both in terms of validating reagents and embracing ambiguity, are necessary to aid in reducing issues with reproducibility.