Bio-IT World 2020 features three Data tracks focusing on Storage and High-Speed Data Transfer Solutions, Managing Workflows with Data and Metadata, and Data Analytic Tools and Technologies. Click on each track to view its full agenda. Can't decide on
a single track? Bio-IT World encourages track hopping to help attendees maximize their on-site experience.
CONFERENCE PROGRAMS
The Data Storage and Transport track presents in-depth case studies from leading life science organizations who are implementing solutions to address data storage and transfer problems and challenges. These include where
to store data (cloud, local, mixture), what is the optimal configuration regarding price vs. access, estimating data storage costs and making financial models, understanding and planning for costs in the cloud, what to do with large third-party
databases (inter-pharma collaborations, genomic/expression datasets), what to do with imaging collaboration that produces 100 TB, "rehydrating" a data archive (from tape) for re-analysis, determining if you're storing the right stuff, figuring
out the best way to deliver data products to customers/collaborators, and more. How are you developing technologies to deal with influx of digital data from digital health devices?
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With the increased demand in computing power from life science researchers and scientists tackling big data issues, storage and infrastructure must be able to scale to handle billions of data points and files efficiently. The problem is administration
of data to ensure information can be integrated, accessed, shared, linked, analyzed, and maintained to best effect across the organization. The Data and Metadata Management track will explore how to manage workflows
with data and metadata without rerunning everything, but with the ability to handle data updates and new versions of the software. We will also explore how to associate the processed data and features with the raw data for analysis purposes.
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The practice of data science requires the use of data analytics tools and technologies like Python, R, SQL, and Tensorflow and approaches like graph databases and column stores to help data professionals gain extra insights and value from data. The Data Science and Analytics Technologies track
will explore popular analytics tools, technologies, languages, and approaches to managing highly complex data that data scientists are using. Most importantly, presentations will explore what problems data science and analytics technologies are
solving within the field, specific methods that are being applied, how to assess the value add against cost, and how to set up team structure within the organization. How do you involve the end-user in defining the requirements necessary to make
the results of these analytics easily actionable?
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RECOMMENDED WORKSHOPS*
Workshop 1 – Data Management for Biologics: Registration and Beyond
The research IT systems that are used to support biologics pharma and biotech organizations are maturing to go beyond registration and support assay data collection, analytics and decision support. Additionally, new software providers are bringing forward
innovative solutions to address structured data capture and automation. In this workshop we bring together some of the pharma, biotech’s, and software providers who will share their approaches to registration and management of biologics data.
Detailed Agenda
Workshop 2 – A Crash Course in AI: 0-60 in Three
Have you ever been curious to apply machine learning to large amounts of data but were not sure of the concepts to use? Have you ever wondered how to get started on AI? Well, you have come to the right place! This workshop will help you learn AI like
never (our instructors guarantee it!). The workshop is a crash course on AI where you will learn the fundamentals and applications of AI/ML in Pharma. Come join us, learn, and network! Detailed Agenda
Workshop 3 – Introduction to Data Visualization for Biomedical Applications
In biology and other data-driven research areas, data visualization has become an integral part of the analysis toolkit. Data visualization approaches serve as the primary interface between analysts and the data. While great data visualization approaches
can accelerate new discoveries, poor data visualization approaches can mislead and slow down progress. Participants of this introductory course will acquire the skills necessary to identify appropriate visualization methods for a given problem and
learn about the state of the art in biological data visualization. This is an introductory course to the principles of data visualization. Detailed Agenda
Workshop 10 – Data Science Driving Better Informed Decisions
This workshop will highlight how data science is succeeding in helping Pharma organizations make data driven decisions to gain efficiencies and let companies grow their research programs effectively. Attendees will learn how to bridge the worlds of data
scientists and bench researchers and see how novel tools and applications can impact their research. Detailed Agenda
Workshop 13 - Structuring Data for Drug Development and Regulatory Submissions: The Role of Standards and Ontology
The potential of emerging technologies like Artificial Intelligence, Robotic Process Automation, Quantum Computing, Blockchain/Distributed Ledger Technology, Internet of Things and more to fundamentally change business models and the way business is conducted
cannot be understated. In an overtly buzzword crazy session (buzzword bingo cards will be provided), we’ll work through real practical ways to define, derive, and deliver value from emergent technologies.
Detailed Agenda
*Separate registration required.
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