IDBS Translational and Biomarker Research Symposium

Abstract

Two trends are driving innovation and discovery in biological sciences: technologies that allow holistic surveys of genes, proteins, and metabolites and the growing realization that analysis and interpretation of the resulting requires an understanding of the complex phenotypic and environmental data regarding the samples from which they were derived. Further, the growing body of biological and biomedical information in the public domain provides outstanding opportunities for leveraging what we already "know" in a systematic way to understand the problems we are studying. Here, I will provide an overview of some of the methods we are using to investigate the complexities of human cancers and to explore how we can use biological data to begin to uncover the cellular networks and pathways that underlie human disease, building predictive models of those networks that may help to direct therapies.

Bio

John Quackenbush received his PhD in 1990 in theoretical physics from UCLA working on string theory models. Following two years as a postdoctoral fellow in physics, Dr. Quackenbush applied for and received a Special Emphasis Research Career Award from the National Center for Human Genome Research to work on the Human Genome Project. He spent two years at the Salk Institute working on developing physical maps of human chromosome 11 and two years at Stanford University working on new laboratory and computational strategies for sequencing the Human Genome. In 1997 he joined the faculty of The Institute for Genomic Research (TIGR) where his focus began to shift to post-genomic applications with an emphasis on microarray analysis. Using a combination of laboratory and computational approaches, Dr. Quackenbush and his group developed analytical methods based on integration of data across domains to learn biological meaning from high-dimensional data. In 2005, he was appointed Professor of Biostatistics and Computational Biology and Professor of Cancer Biology at the Dana-Farber Cancer Institute (DFCI) and Professor of Computational Biology and Bioinformatics at the Harvard School of Public Health. Since that time, his work has increasingly focused on the analysis of human cancer using systems-based approaches to understanding and modeling biological problems. In 2009 he launched the Center for Cancer Computational Biology (CCCB) at the DFCI which provides broad-based bioinformatics support to the local research community using a collaborative consulting model.

Abstract

Biomarker Data Mining (BDM) will lead to a better understanding of drug action, an improved ability to understand physiological responses, and better overview of interrelationships between research and clinical data. MedImmune just completed building a BDM platform to extract, transform, and load (ETL) data from various disparate storage locations and formats such as current databases and spreadsheets, and assemble and present correlated data for exploratory analyses. This talk presents how this flexible data model supports a scalable, industrial-strength scientific data pipeline.

Bio

Daniel Ingber is a Research Information Systems Sr. Manager at MedImmune LLC (Gaithersburg, MD) leading a team to build and support information systems for Research. Prior to MedImmune he was employed at Celera and subsequently at Applied Biosystems where he led a team of bioinformaticians responsible for maintaining the Variation Annotation database (SNPs, CNVs) and related genotyping products and activities. Daniel has been working in the Biotechnology Industry for the past eight years, supporting large-scale scientific data content pipelines. He has resided with his family in Washington D.C. for the past 20 years.

Abstract

Genome wide association studies have delivered on the promise of uncovering genetic determinants of complex disease, using high-throughput methods allowing large volumes of SNPs (105-106) to be genotyped in large cohort studies. The GWA approach serves the critical need for a comprehensive and unbiased strategy to identify causal genes related to complex disease and is rapidly replacing the more traditional candidate gene studies and microsatellite-based linkage mapping approaches that have dominated the gene discovery attempts for common diseases in previous years. As a consequence of employing this array-based technology, over the last three years dramatic discoveries of key variants involved in multiple complex diseases and related traits have been reported in the top scientific literature, including over 400 novel loci with multiple replications in over 80 disease areas by independent groups. In this talk, discoveries will be reviewed and large-scale database efforts discussed and their use in complex genetic disorders and genomics of drug response.

Bio

He is the Director of the Center for Applied Genomics (CAG) at the Children's Hospital of Philadelphia (CHOP), a high-throughput highly automated genotyping facility founded to identify the genetic causes of autism and other complex medical disorders in children with the objective of developing new therapies. The Center represents a $40 million commitment from CHOP to collect and genotype approximately 100,000 children over a 4 year period. Dr. Hakonarson has an extensive track record in human genetics and has developed an international reputation amongst his peers. He has served in several senior posts in the past, including as the Head of Inflammatory and Pharmacogenomics Research and the Vice President of Clinical Sciences and Development and CSO for the biopharmaceutical industry. Dr. Hakonarson has also been the principal and Co-principal investigator on several NIH sponsored grants, and he has published numerous high-impact papers in some of the most prestigious scientific medical journals, including Nature, Nature Genetics, The New England Journal of Medicine, the Journal of the American Medical Association, The Journal of Clinical Investigation, The American Journal of Human Genetics and the Proceedings of the National Academy of Sciences. With over ten years of experience in pioneering genomic research and genome-wide mapping and association studies, Dr. Hakonarson has intimate knowledge of the complexities of large-scale genomics projects and has put together the necessary infrastructure and workflow processes to unravel these complexities in his role as the Director of the Center for Applied Genomics at CHOP.

Abstract

Long lists of un-annotated proteins and genes are not a sufficient end point for 'omics analysis, they need to be annotated with data from many public and proprietary sources. IDBS provide solutions to not only automate the discovery and subsequent annotation of biomarker results, but to capture each step of the experimental set up, data capture, and analysis in a compliant manner.

Bio

As Director of Translational Medicine, Jonathan Sheldon is responsible for all translational research and related activities across IDBS including the recently acquired InforSense business of which he was Chief Scientific Officer.

Prior to InforSense/IDBS, Jonathan was Chief Technology Officer for Confirmant Ltd where he was responsible for developing the company's proteomics products and services. Previously he established the first bioinformatics group and was Head of Bioinformatics for 5 years at Roche Welwyn, UK participating in a number of global initiatives within the company. Dr. Sheldon holds a PhD in Molecular Biology/Biochemistry from the University of Cambridge.

Abstract

The Lung Genomics Research Consortium (LGRC), launched in October of 2009 with funding from the American Recovery and Reinvestment Act, is a large scale, multi-institutional project with the overall goal of establishing a genetic, molecular, and quantitative phenotyping warehouse and analysis portal to enhance the understanding of lung disorders. The portal will enable investigators in the lung research community to develop and test hypotheses to understand the etiology, pathogenesis, and clinical manifestation of chronic lung diseases based on almost 1300 well characterized samples from patients with disorders such as COPD/emphysema and pulmonary fibrosis.

A central component of the proposed portal is an interface that will enable researchers to explore the detailed clinical/phenotypic characteristics of the study population and to define specific cohorts that can be used in the downstream analysis of the generated molecular data. With a primary audience of biologists and clinicians, it is essential that such an interface be intuitive and easy to use with little or no training. Furthermore, with an ambitious program and a compressed time schedule, rapid implementation time is a key factor for success and is the responsibility of the Center for Cancer Computational Biology at Dana-Farber Cancer Institute.

After evaluating available technologies we selected the IDBS ClinicalSense product to fill this need, and in the first 6 months of the project have made tremendous progress in developing our portal. While achieving our primary objectives, this early success has also enabled us to leverage the tool in unintended ways as well, and we are now deploying the portal to the consortium to aid in sample selection and experiment design for early pilot studies. This talk will focus on the practical aspects of designing and implementing a sophisticated clinical analysis portal in the context of a translational research project

Bio

Mick Correll is the Associate Director of the Center for Cancer Computational Biology (CCCB) at the Dana-Farber Cancer Institute. Before joining the CCCB, he worked in industry where he focused on the design, management, and implementation of informatics solutions for the pharmaceutical, biotech, and healthcare industries, most recently as the Director of Healthcare Product Management at InforSense LLC. Mick was a Bioinformatician at Lion Bioscience Research Inc, where he was the principle architect of a globally distributed gene annotation and analysis platform. Mick also served as the Head of Professional Services for Lion Bioscience Inc in North America. He holds a BS in Computer Science and a BA in Molecular, Cellular, and Developmental Biology from the University of Colorado at Boulder.

Abstract

The recent healthcare reform act and stimulus spending has focused attention on "meaningful use" of electronic health records, making it a precondition to receiving Federal funds for healthcare IT. But a lot will depend on how healthcare institutions actually achieve meaningful use. Alongside the indisputable demographic trends, rapidly changing medical science will be one of the largest determinants of cost in the long run. While new drugs, therapies, and technologies could drive up costs, they could also provide entirely new avenues for cost containment through early detection of disease, better diagnostics, and more effective approaches to managing chronic diseases. The overall outcome over the next two decades will be determined by the velocity and productivity of basic and translational research. Hence, the next generation of healthcare IT infrastructure must help break down the silos between care delivery, translational medicine, and basic research. The tools to enable this while preserving patient privacy, managing consent, and controlling IT costs, are finally within reach. We will examine an architecture for achieving this.

Bio

Kris Joshi is Vice President for Healthcare Product Strategy for Oracle Corporation's Health Sciences Global Business Unit. He leads the business unit's strategic planning and execution in the Healthcare industry. In a prior role at Oracle, he led strategy and operations across healthcare and life sciences, focusing on inorganic growth opportunities. He helped form the health sciences business unit, and successfully led two acquisitions for Oracle in the life sciences space. He implemented a unique Operational Excellence program across all functions in the health sciences business unit to deliver breakaway performance and growth.

Prior to joining Oracle, Kris served in senior strategy roles in IBM's Global Sales and Distribution organization. He helped develop IBM's emerging markets strategy, and created innovative business models for leveraging technology in healthcare for developing economies. Prior to that, Kris was with McKinsey and Co, where he served Fortune 500 clients in Banking, Media, Healthcare and Life Sciences industries on strategy issues.

Kris has a long-standing interest in helping bridge the gap between the non-profit and for-profit worlds through entrepreneurship and innovative business models. Most recently, he is involved in a collaborative effort with the Division of Global Health and Human Rights at Massachusetts General Hospital to implement a sustainable model for health education in Africa.

Kris holds a Bachelor's degree in Mathematics from Caltech, and a Ph.D. in Physics from MIT.