Erich Gombocz
Paolo Ciccarese

 


Keynote speakers


Dr. Erich Gombocz

Vice President, Chief Scientific Officer
IO Informatics
Berkeley, CA, USA

Dr. Erich Gombocz has over 30 years of experience in Life Science research, laboratory automation and data management in scientific and distributed systems environments. Over a decade at the Federal Institute of Food Analysis & Research, Vienna, Austria, leading the early development of computational analysis and automation procedures in a complex distributed environment Erich’s contributions were pivotal during the Chernobyl crisis in 1986, where Austria's early warning system delivered real-time information critical to international decision-making. Erich’s post-doctoral research at the National Institute of Health (NIH) (1985, 1988), on techniques and computer models for separations, led him to build an automated real-time instrument and to found venture-backed Lab Intelligence, Inc. in 1989. With over 30 years programming skills in instrument control, user interface, database design, scientific analysis, on-line laboratory automation and as developer of innovative software algorithms and architecture, he co-founded IO Informatics in 2003 with a focus on semantic data integration and knowledge management in life sciences to apply systems biology approaches to pharmaceutical and clinical decision-making. Dr. Gombocz has published over 60 scientific publications and holds more than 40 biotechnology- and software-related US and international patents. Considered an international expert in separation science and bioinformatics, he serves on the editorial board of several scientific journals. His activities in World Wide Web Consortium (W3C) HCLS Special Interest Groups, at the National Center for Biomedical Ontology (NCBO), the Pistoia Alliance Standards Initiative and as Chair of the Working Group for Best Practices in Data Sharing are a testimony to his role as a pioneer at the forefront of technology.



Changing the Model in Pharma and Healthcare – Can we afford to wait any longer?


Innovation in healthcare delivery and Pharma requires rethinking old problems, retooling with new methodologies and revisiting the process models that are foundations of our existing knowledge discovery and clinical practice. The continuing proliferation of ubiquitous sensor data, mobile devices and the advent of 3D printing of drugs, together with a social mind shift in data ownership are clear indicators that Data is the new money. And yet, data integration remains one of the core challenges to innovation despite real-time availability of ‘big data’.

Increasingly persistent, semantic data integration continues to be adopted and recognized for its dynamic data models and formalisms which make it possible to infer from and reason over interconnected contextualized ‘big data’, creating actionable knowledge faster and at lower cost.

While such technical advances underpin the successful strategies to drive clinical decision support and positive patient outcomes or accelerate drug design, there are equally profound initiatives leveraging the impact of social media and the willingness of patients to share their own data. Together these are the drivers that are opening the doors to new patient-centric, precision-medicine healthcare models.

In light of this, and the astronomically rising costs in research and healthcare, we have arrived at a critical turning point where it is now well within our reach to change how drugs are developed, how trials are performed and how patients are treated - moreover, we can do this with huge benefits for otherwise unsustainable industries. Using comparative effectiveness and side effect analyses for every patient, and by basing treatments on solid prognoses and therapy decision support, we can and must change discovery and healthcare into a data driven and patient centric paradigm. This will change the playing field definitively and the socio-economic benefits will be enormous.

With several examples I will show that not only is this possible today, but that such approaches already have traction; (i) in Pharma for assessing the impact of excipient choice on drug stability and efficacy, pre-clinical toxicity assessment, and providing integral systems views on drug safety, (ii) in Government for the FDA’s cross species biomarker initiative to reduce animal testing and (iii) in Health Care for organ transplant rejection assessment and COPD.

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Dr. Paolo Ciccarese

Assistant in Neuroscience at Massachusetts General Hospital
Instructor in Neurology at Harvard Medical School
Co-chair of the W3C Open Annotation Community Group

After researching in the field of clinical information systems and clinical decision support, Paolo’s current main focus consists in enabling personal and community-driven scientific knowledge acquisition, curation and sharing. Neuroscience is the main area of interest, but the same methods and tools are also applied to other disciplines. Paolo co-developed the SWAN platform [1] focusing on scientific discourse representation in Alzheimer's Disease research and is now exploring the use of Annotation of digital resources for supporting the knowledge creation process. Paolo is the author of the Annotation Ontology [2], an RDF model for exchanging annotation. He currently co-chairs the W3C Open Annotation Community Group [3] with the purpose of working towards a common, RDF-based, specification for annotating digital resources. Paolo is the architect of the Domeo Annotation Toolkit [4, 5] an extensible web application enabling users to visually create and share ontology-based stand-off annotation on HTML documents. Paolo is also the architect of the CATCH (Common Annotation, Tagging, and Citation) at Harvard project a unified public open API that will enable storing, searching, discovering, sharing and analyzing scholarly annotations produced on four digital media types - text, image, audio and video - across existing pedagogical and research tools at Harvard.

[1] http://www.ncbi.nlm.nih.gov/pubmed/18583197
[2] http://www.jbiomedsem.com/content/2/S2/S4
[3] http://www.w3.org/community/openannotation/
[4] http://www.jbiomedsem.com/content/3/S1/S1
[5] http://annotationframework.org/



Open Annotation


Despite the Linked Open Data wave, all data sources in biomedicine and even more in other fields are naturally “silos” at some level, That is, their cardinality and topicality is limited, and their organizational schema embodies a point of view or a particular set of principles which will not be universally applicable. A full conversion and integration of all the available data sources is going to take time and is not always necessary and/or convenient. At the same time, the Web’s original “integration by untyped links” is intractable for machine processing without “scraping”, which is fragile and cumbersome.

Annotation is a fundamental activity in clinical and biomedical research as well as scholarship in general. Through annotation we can associate a commentary or formal judgment (textual comment, revision, citation, classification, or other related object) to targets such as text, images, video and database records. Annotation can be created for personal use, as in note-taking and personal classification of documents and document content. Or it can be addressed to an audience beyond its creator, as in shared commentary on documents, reviewing, citation, and tagging.

This talk will discuss annotation as a form of “micro-integration”, in which typed, versioned and provenance links are assigned between text and schema, text and data or data and data. I will show how annotation can help with immediate data integration needs and long terms integration efforts. I will introduce the Open Annotation standard and will list efforts using annotation and directing to transform content into smart and connected data.

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