High Content 2017 - 4th Annual SBI2 Conference
Hardware & Image Acquisition
Image & Data Analysis
Tissue based imaging
Effect-Size Measures as Descriptors of HCS Assay Quality
CRISPR for HCS
High Content 2017 Educational Courses, Day 1
09:00 – 10:00 AM, Room 30C, Introduction: Hardware and Image Acquisition, Doug Bowman, Takeda Pharmaceuticals
Abstract: This course will review the concepts and technologies related to instrumentation (e.g. optics, camera, and illumination), infrastructure, and image acquisition software features and workflow. The level of instruction is geared to those new to HCS and to those interested in learning what’s inside the “black box.” An understanding of the key components will enable you to optimize for the quality and throughput of HCS experiments.
09:00 – 10:00 AM, Room 30D, New Technologies, David Andrews, University of Toronto
09:00 – 10:00 AM, Room 30E, Phenotypic Screening, Myles Fennel, Sloan Kettering Cancer Center and Paul Selzer, Novartis
Abstract: For this course we are going to use the definition of phenotypic screening in which a substance is used to alter a measurable trait in a cell or organism. This differs from when we screen against a purified protein, or even the activity of a single target within a high-content screen, either endogenous or overexpressed. Hit selection and assay quality measures used in traditional screening (such as Z’) may be difficult to apply to phenotypic endpoints that rely on multiple measures. Positive controls might not be readily available or interesting leads having a phenotype that differs from controls. We will use examples from our groups and literature with advice and best practices for designing, implementing and selecting hits from phenotypic high-content screens. From a strategic perspective we will discuss key success factors of historic phenotypic drug discovery projects. For this course we are going to use the definition of phenotypic screening in which a substance is used to alter a measurable trait in a cell or organism. This differs from when we screen against a purified protein, or even the activity of a single target within a high-content screen, either endogenous or overexpressed. Hit selection and assay quality measures used in traditional screening (such as Z’) may be difficult to apply to phenotypic endpoints that rely on multiple measures. Positive controls might not be readily available or interesting leads having a phenotype that differs from controls. We will use examples from our groups and literature with advice and best practices for designing, implementing and selecting hits from phenotypic high-content screens. From a strategic perspective we will discuss key success factors of historic phenotypic drug discovery projects.
10:00 – 11:30 AM, Coffee Break
10:15 – 11:15 AM, Room 30C, Introduction: Assay Types and Assay Development, Joe Trask, Perkin Elmer
10:15 – 11:15 AM, Room 30D, Systems Biology, Data Mining, and the Search for the Incredibly Important Novel Phenotype: A Guide for Novices to Help Participate in the Conversation, Steve Haney, Eli Lilly and Company
Abstract: HCS is a very ‘feature-rich’ approach to cell biology. These features enable complex methods for data analysis that reduce these features to a few experimentally tractable observations. How do all these data get reduced to key trends? How are these processes evaluated for significance and at what point does over-fitting become a distraction? This course will introduce the most common methods of data reduction and analysis, approaches for defining significance and conclude with a set of case studies from the literature. The course will be pitched to scientists who are not currently practicing in these data-mining approaches, but see themselves as consumers of such information and want to be better prepared to engage in conversations and experiment planning based on these methods.
10:15 – 11:15 AM, Room 30E, Kinetic Imaging of Cancer, Leslie Griner, Novartis
Abstract: The disease of cancer is complex and heterogeneous requiring many different lines of concurrent therapy. This ranges from surgery, to radiation, and ultimately always involves combination therapies in the form of small molecules, immuno-oncology approaches and treatment with biologics. To address this heterogeneity major efforts are underway within oncology drug discovery to find novel targets which could result in more durable and deeper responses. The evolution of novel targets also presents the need for more complex and relevant assays in which to study targets from the immune system, microenvironment and regulatory networks of transcription/translation. For years, the use of biochemical assays has enabled experimental determination of compound on-rates and off-rates that underline the affinity of a certain target with the limitation of studying systems using a highly reductionist approach. The evolution of high content imaging (HCI), however, is one method where these complex systems can be studied in a more physiologic context with the goal of understanding the function of the target, and more importantly how we can interrupt aberrant signaling in the cancer cell. Complexed with HCI is the ability to study things in real time using live imaging or in conjunction with signaling kinetics over multiple time points. This course will provide some real world examples of high content kinetic assays being employed today to elucidate these complex and novel drug targets.
11:15 – 11:30 AM, Coffee Break
11:30 – 12:30 PM, Room 30C, Introduction: Image and Data Analysis, Mark Bray, Novartis
Abstract: This introduction will acquaint attendees with the concepts, methods, software and workflows behind automated image analysis. We will introduce the researcher to the basic principles behind determining which pixels in an image below to each cell and/or cellular compartments and measuring properties of interest, with the intent of providing a fuller understanding of the rich information available for discerning phenotypes of interest. No prior knowledge is assumed, though attending the companion introductory sessions is recommended.
11:30 – 12:30 PM, Room 30D, Single Cell Cytometry: Introduction to Flow Cytometry and How Flow and Image Cytometry are Related, David Gebhard, Pfizer
Abstract: Flow cytometry is a legacy technology for single cell analysis that shares many of the same underlying fundamental principles with quantitative image analysis. Flow cytometry and quantitative image analysis are both used to derive high content data from single cells. This course will review the concepts and fundamentals of flow cytometry, terms, operations and processes, and will compare and contrast flow and image cytometry to help the attendees better understand how flow and image cytometry can complement and inform each other.
11:30 – 12:30 PM, Room 30E, CRISPR Technology, Sam Hasson, Pfizer
Abstract: Imaging based assays for cellular phenotypes are central to high content screening and analysis. Due to the need to segment and measure specific cellular features, overexpression of fluorescently tagged proteins has been a staple of high content assay design. While antibodies are useful for measuring endogenous protein levels and localization, relatively few reagents exist that work well for immunofluorescence applications. This course will focus on the synergy that exists between the rapidly expanding genome editing toolbox (such as CRISPR/Cas9) and high content applications to measure cellular phenomena at the endogenous level. In addition to covering case studies that exemplify this synergy, practical workflows will be discussed for innovative assay design.
12:45 – 2:30, Special Lunch Time Sessions
- Room 30C, Assay Quality Measures and Validation, Bartek Rajwa, Purdue University; Data Analysis, Allen Goodman, Broad Institute
Abstract: This workshop will review and interpret the screening measures of assay quality such as Z' (Z-prime) and Sw (assay window) and will demonstrate how they are related to well-established and broadly-used statistical techniques for reporting effect sizes (Cohen's d, Hedges g). The speaker will discuss the origins of the familiar HT/HC assay quality indices, their strengths and applicability, but also limitations and shortcomings. The talk will demonstrate the connection between the effect size metrics, commonly used statistics (such as Student t, and Hotelling T2), and performance measures employed in machine-learning (sensitivity, specificity, predictive values, F1 score, and AUC).
Although the presentation will mostly focus on the practical problem of assay quality quantification, it will also touch upon other important aspects of data analysis in phenotypic screening. It will reintroduce the important yet often misunderstood concepts of significance, replication, statistical power, fixed and random effects, and meta-analysis, and link those exotic-sounding terms to the everyday praxis of assay design, optimization, and use.
The intended audience includes the screening practitioners working with all the types of HT or HC screens (bulk assays, image-based system, and flow cytometry instruments).
- Room 30D, 3D HCS Drug Discovery: Essentials for Imaging and Analysis of Tumor Organoids, Dan LaBarbera, University of Colorado ; Carrie Lovitt, Griffith University
Abstract: This seminar will highlight 3D cell culture model principles essential for HCS drug discovery including assay design, throughput, and imaging and analysis. Examples of applications will include profiling the activity of therapeutics utilizing scaffold-based and scaffold-free tumor organoid model systems.