Day 1 | Day 2
5:00-6:00 pm Early Conference Registration
8:00-8:30 Conference Registration and Morning Coffee
8:30-8:40 Welcoming Remarks from
Conference Director
Julia Boguslavsky, Cambridge Healthtech Institute
8:40-8:45 Chairperson’s Opening Remarks
8:45-9:10 Can We Apply Open-Source Alternatives for High-Content Screening Data Mining, Storage and Management?
Karol Kozak, Ph.D., Head, Computation Analysis, HCA/HTS Informatics, LMC-RISC, Institute for Biochemistry
With the growing use of high-content screening (HCS) and analysis in drug discovery and systems biology, informatics has come to the forefront as a critical technology to effectively utilize the massive volumes of high-content data and images being generated. Informatics technologies are required to transform HCS data and images into useful information and then into knowledge to drive decision making in an efficient and cost-effective manner. This presentation will focus on open source informatics tools and technologies for HCS, discuss some of the challenges of mining, storing and analysis the huge and growing volumes of HCS data, and provide insight to help toward implementing or selecting, and utilizing a high-content informatics solution to meet HCS unit’s needs.
9:10-9:35 The Open Microscopy Environment: Open Image Informatics for Biological Microscopy and HCAs
Christopher B. Allan, Software Developer, Open Microscopy Environment, Wellcome Trust Centre for Gene Regulation & Expression, College of Life Sciences, University of Dundee
We have developed an open-source software framework to address the needs for image data integration and interoperability known as the Open Microscopy Environment (OME). OME has three components – an open data model for biological imaging, standardized file formats and software libraries for data file conversion and software tools for image data management and analysis. The OME Data Model has recently been updated to more fully support fluorescence filter sets, the requirement for unique identifiers, including LSIDs, and screening experiments using multi-well plates. The OME-TIFF file format and the Bio-Formats file format library provide an easy-to-use set of tools for converting data from proprietary file formats. These resources enable access to data by different processing and visualization applications, and sharing of data between scientific collaborators. The Java-based OMERO platform includes server and client applications that combine an image metadata database, a binary image data repository and high performance visualization and analysis. The current release of OMERO includes interfaces for C/C++ and Python to support a wide variety of client applications and support for Matlab-based applications like Cellprofiler. For computational analysis of images, this standardized interface provides a single mechanism for accessing image data of all types -- regardless of the original file format. Moreover, a compute distribution facility is included, to support multi-cpu computing installations.
9:35-10:00 Integration of Multiple Readouts into the Z’ Factor for Assay Quality Assessment
Anne Kuemmel, Ph.D., Post Doctoral Researcher, Novartis Institutes for BioMedical Research
Methods that monitor the quality of a biological assay, i.e. its ability to discriminate between positive and negative controls, are essential for the development of robust assay protocols. In screening, the most commonly used parameter for monitoring assay quality is the Z’ factor, which is based on a single selected readout. Biological assays are, however, increasingly able to monitor multiple readouts. For example, novel multiparametric screening technologies like high-content screening (HCS) provide information rich data sets with multiple readouts on a compound’s effect. Still, assay quality is commonly assessed by the Z’ factor based on a single selected readout. We suggest an extension of the Z’ factor which integrates multiple readouts for assay quality assessment. Using linear projections, multiple readouts are condensed to a single parameter based on which the assay quality is monitored. We illustrate and evaluate this approach using simulated data and real world data from a high-content screen. The suggested approach is applicable during assay development, optimization of image analysis methods as well as during screening to monitor assay robustness. Furthermore, not only data sets from high-content imaging assays but also from other state-of-the-art multiparametric screening technologies, such as flow cytometry or transcript analysis, can be analyzed.
10:00-10:30 Networking Coffee Break
10:30-10:55 An Informatics Platform to Enable HCS of Large Chemical Libraries Using Multi-Stage qHTS
Dac-Trung Nguyen, Ph.D., Informatics Research Scientist, NIH Chemical Genomics Center, National Institutes of Health
Enabling phenotypic assays for high-throughput screening (HTS) using high-content screening (HCS) technologies is becoming indispensable for early stage drug discovery and chemical biology. Despite their wide adoption, the coupling and integration of HTS and HCS has not been achieved. Recently, our group developed a new coupling strategy, so-called “wells to cells”, between two complementary technologies: cytometry and microscopy. In this talk, we describe an in-house Informatics platform that enables the wells to cells paradigm. In particular, we address some of the implementation challenges (e.g., real-time HTS data analysis, definition of active samples, and decision making), highlight some key features based on some example validation assays, and discuss its future directions.
10:55-11:20 Bioimage Informatics for the Automated Analysis of in vivo Gene Expression
Uwe Ohler, Ph.D., Assistant Professor, Institute for Genome Sciences & Policy, Duke University
To measure 4d gene expression in living plant roots, we have developed a high-throughput confocal microscopy platform which allows us to track and monitor several dozen plants under controlled environmental conditions. This allows us to extract high-resolution gene expression levels from different plants with different GFP reporter constructs simultaneously. We will focus on the software and computational aspects of this platform: detecting growing roots, tracking them over time, and obtaining tissue-specific gene expression levels.
11:20-11:45 Networking Break
Sponsored by
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11:45-12:15 pm Speed and Applications Flexibility for High-Content Screening:
The MDS Complete Solution for HCS
Michael Sjaastad, Ph.D., Director, Marketing, Cellular Imaging, MDS Analytical Technologies
Speed and application flexibility allow high-content screeners and researchers to process more compounds while maintaining the data quality and content achieved using traditional microscopes. MDS Analytical Technologies offers the Complete Imaging Solution for HCS to seamlessly acquire, analyze and identify compounds for hit selection. Three choices in instrumentation provide a range of image resolution and speed for all HCS assay needs. Turnkey application modules enable researchers to examine hundreds of specific assays while proprietary parallel processing software accelerates image analysis many fold. We will present examples of how the highly versatile MDS Complete solution are utilized for HTS confocal imaging campaigns, object based image screens at 5 minutes per 1536 well plate, and large organism screening of Zebrafish.
Sponsored by
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12:15-12:30 Scalable Data Management and Analysis in High-Content Screens – Leveraging Rich Biological Outcomes with Extreme Efficiency
Oliver Leven, Ph.D., Head, Genedata Screener Professional Services, Genedata AG
High-Content Screening has evolved to a mature technology, with manifold applications in Target and Systems Biology, Lead Discovery, Lead Optimization, and in vitro Toxicology. However, its routine application on a broad scale still faces significant hurdles in terms of managing data volume and complexity, achieving analysis efficiency and traceable result interpretation. We will show how scientists get past these hurdles, routinely analyzing large High-Content Screens in a scalable, fast and thorough fashion and realizing the full potential of their rich biological data in a production environment. We will also discuss single-cell analysis as an emerging theme in higher throughput experimentation.
12:30-12:45 Managing the HCA Data Mountain
Abhay Kini, Ph.D. Global Product Marketing Manager, IN Cell Software, GE Healthcare
IN Cell Miner is a software environment enabling management, visualization and integration of HCA data. Built on Documentum®, the enterprise content management system, IN Cell Miner simplifies integration of data across multiple platforms within drug discovery and facilitates management of HCA data with functional annotations. IN Cell Miner allows the small laboratory or enterprise customer to seamlessly integrate analytic tools with HCS/HCA workflows for easy visualization and analysis permitting the realization of the full potential of their HCA data.
12:45-1:00 Beyond Basic HCS Data Management: Learning, Modeling, and Advanced Data Analysis using Pipeline Pilot
Kurt Scudder, Solutions Scientist, AccelrysAccelrys’ Pipeline Pilot has found a place in the labs of many HCA practitioners, taking advantage of the image analysis, statistics, and plate data handling collections in the product. The toolbox approach allows developers and users to envision a way to analyze or visualize data, then rapidly construct one or more protocols to enable that vision. This approach complements and extends the HCS instrument vendors’ data management and analysis software. Accelrys has facilitated this by building into Pipeline Pilot connectivity to the data management systems from most major HCA vendors such as Cellomics, GE Healthcare, BD Bioscience, PE, Molecular Devices, and Beckman-Coulter. This capability can now be combined with the learning and advanced data modeling capabilities in Pipeline Pilot to move beyond simple HCS analysis and data management into more detailed examination of images and extracted data, and examination of the data for latent patterns or characteristics which can give new insights. All of this can be done while remaining within the Pipeline Pilot environment. Examples of the application of advanced data modeling with images and image objects will be presented.
1:00-2:00 Lunch on your own
2:00-2:05 Chairperson’s Opening Remarks
2:05-2:30 Improved Methods for Learning Cell Shape Models and Sub-cellular Patterns from High-Throughput Microscopy
Robert F. Murphy, Ph.D., Professor, Departments of Biological Sciences and Biomedical Engineering, Carnegie Mellon University
Automated learning of predictive models directly from images is an approach to extracting more information from high-content imaging. We have previously developed approaches to learning generative models of nuclear shape, cell shape, and protein sub-cellular locations, and have now extended them significantly. First, we have developed an approach to modeling cell, nuclear and organelle shape that does not require representation of shapes by features. The models can be used to summarize results or predict patterns under new conditions. Second, we have demonstrated how to perform indirect estimation of model parameters to capture the state of microtubule polymerization (or degree of network formation for other proteins) without requiring high-resolution or specialized imaging. Thus, the approach is suitable for high-content analysis systems.
2:30-2:55 Quantifying Challenging Phenotypes in Images
Anne Carpenter, Ph.D., Director, Imaging Platform, Broad Institute of Harvard & Massachusetts Institute of Technology
Many challenging image-based phenotypes have recently become quantifiable due to advances in image analysis and machine learning algorithms. Our recent work in the area has enabled high-content analysis of phenotypes relevant to multiple basic biological processes and clinically relevant diseases. The variety of phenotypes that can be accurately quantified using software continues to grow.
2:55-3:20 Nuclear and Chromatin Dynamics in Stem Cells by Analytical Confocal Time-Lapse Imaging
Paul Sammak, Ph.D., Research Associate Professor, Ob/Gyn, University of Pittsburgh
Chromatin dynamics and organization influence gene expression patterns and developmental pathways during stem cell maturation. Chromatin plasticity can be observed by confocal time-lapse imaging of the histone GFP-H2B and measured quantitatively by novel image analysis algorithms for noising images and measuring heterogeneous nuclear texture in concentric layers. New statistical methods allow us to quantitatively measure changes in nuclear organization and dynamics and show how heterochromatin formation occurs only after pluripotent cells differentiate.
3:20-3:45 Networking Refreshment Break
3:45-4:10 Image-Based Systems Biology for Drug Repositioning and Combination Studies
Stephen T.C. Wong, Ph.D., John S. Dunn Foundation Distinguished Chair, Professor; Director, Bioinformatics and Biomedical Engineering Program; Director, Cellular and Tissue Microscopy Core, Methodist Hospital, Weill Cornell Medical College
This talk presents a novel approach to image-based systems biology for drug repositioning and combination, with examples in cancer drug repositioning and combination. We’ll systematically integrate systems biology methods and high-content screening to decipher multiple targets in the pathways of brain metastases of triple negative tumors and to rationally reposition FDA approved drugs for the brain metastasis of triple negative tumors. Central nervous system (CNS) metastases is the most common type of brain malignancy, and breast cancer is the second most common type of malignancy to cause CNS metastases. Recent studies conclude that triple negative tumors are not only significantly less likely to develop bone or liver metastasis or have involvement of non-regional lymph nodes, but are more likely to develop brain metastasis. Our aim for investigating repositioned small molecule drugs with CNS penetration and de novo combination of the chemotherapeutic agents for the systematic treatment of brain metastasis of triple negative breast cancer promises to generate results that can be quickly translated into clinics. We’ll describe computational tools we’re using and developing involving high-content analysis, network-based analysis, and animal imaging to evaluate optimal drug combinations for breast cancer.
4:10-4:35 Advances in Novel High-Content and Live-Cell Imaging: Integration with in vivo Imaging and Proteomics to Improve Clinical Predictability
Neil Carragher, Ph.D., Senior Scientist, Advanced Science & Technology Laboratory, AstraZeneca
We describe the application of a suite of novel kinetic and high-content in vitro assays designed to generate as much mechanistic information as possible on candidate therapeutics. Multivariate analytical techniques have been used to characterize, cross-reference and understand phenotypic responses. Fluorescent imaging technologies also offer the potential to leverage mechanistic information from in vivo models. The predictability of complex in vitro models can be calibrated by comparison with functional in vivo imaging approaches. Integration of the above approaches with proteomic and genomic data sets and in silico methods may enhance the clinical predictability of the drug discovery process.
4:35-5:00 High-Content Approaches to Understanding the Genetic and Physiological Interactions in Hepatic Insulin Resistance and Diabetes
Steven Haney, Ph.D., Associate Fellow, Biological Profiling, Pfizer Biotherapeutics and Bioinnovation Center
Hepatic insulin resistance is a hallmark of the prediabetic state and of type 2 diabetes. Our capacity to understand insulin resistance is necessary for developing therapeutics that can treat diabetes and the stresses associated with it. We have developed a platform for the study of factors that contribute to the diabetic state of the liver that incorporates a robust primary hepatocyte cell culture system, RNAi screening and high-content analysis. This platform is being used to examine both the genetic and the physiological factors that have been suggested as causes of diabetes.
5:00-6:00 Grand Opening Reception in the Exhibit Hall
For more information, please contact:
Julia Boguslavsky, Executive Director, Conferences
Cambridge Healthtech Institute
E-mail: juliab@healthtech.com
For sponsorship information, please contact:
Katelin Fitzgerald, Manager, Business Development
Cambridge Healthtech Institute
Phone: 781-972-5458; E-mail: kfitzgerald@healthtech.com