Track 6 assembles thought leaders who will present case studies using computational resources and tools that take data from multiple –omics sources, including microbiomics and metabolomics, and align it with clinical action. Turning big data into
smart data can lead to real time assistance in disease prevention, prognosis, diagnostics, and therapeutics. With the ever-increasing volume of information generated for curing or treating diseases and cancers, bioinformatics technologies, tools and
techniques play a critical role in turning data into actionable knowledge to meet unstated and unmet medical needs.
Tuesday, May 23
7:00 am Workshop Registration and Morning Coffee
8:00 – 11:30 Recommended Morning Pre-Conference Workshops*
(W4) Data Visualization to Accelerate Biological Discovery
12:30 – 4:00 pm Recommended Afternoon Pre-Conference Workshops*
(W13) Proteogenomics: Integration of Genomics and Proteomics Data
* Separate registration required.
2:00 – 6:00 Main Conference Registration Open
4:00 PLENARY KEYNOTE SESSION
xxxxxxxxxxxxxxxxxxxxClick here for detailed informationxxxxxxxxxxxxxxxxxxxxxxxxx
5:00 – 7:00 Welcome Reception in the Exhibit Hall with Poster Viewing
Wednesday, May 24
7:00 am Registration Open and Morning Coffee
8:00 PLENARY KEYNOTE SESSION
9:50 Coffee Break in the Exhibit Hall with Poster Viewing
10:50 Chairperson’s Remarks
Kevin Merlo, BioSafety Development Engineer, Dassault Systemes, BIOVIA
11:00 Innovative Data Integration Applicable for Therapeutic Protein Development 2.0
Wolfgang Paul, Group Leader and Senior Scientist, Large Molecule Research, Roche
Therapeutic proteins are registered including sequence, structural and functional data and information. Millions of data points are captured during the development of Roche’s innovative therapeutic proteins in data warehouse used by DAMAS (data
acquisition, management and analyses system). Fast access and visualization of relevant process and analytical data drive scientific discussion and decision making. Analyzing the stored big data is key towards process development of therapeutic proteins
11:30 Informatics – A Silver Bullet for Pharmaceutical Sciences?
William Loging, Ph.D., Associate Professor of Genomics & Head, Production Bioinformatics, Genetics and Genomics Sciences, Icahn School of Medicine at Mount Sinai
The Pharmaceutical Sciences field is in constant search for the next big innovative push that will increase the success rate of drug programs. The fields of computational chemistry, structural bioinformatics – just to name a few – have changed
the way drug researchers look for and identify novel drug candidates. Utilizing more than 15 years of Pharmaceutical experience, and using real world examples of high provide drug projects, this talk will provide practical steps for the merger of
informatics and the strategic approaches needed for drug discovery success.
12:00 pm Big Data-Driven Bioinformatics
Frank Lee, Ph.D., Healthcare Life Sciences Industry Leader, Software Defined Infrastructure, IBM Systems, IBM
IBM will discuss the IBM Reference Architecture for Genomics, its new features, and case studies: hybrid cloud with integrated workload and data management for high performance genomics analytics; container technologies for migrating and sharing application
and data; and application portal and metadata engine for global access to and searching of distributed resources. A demo of a hybrid cloud-based bioinformatics solution will follow.
12:30 Session Break
Luncheon Presentation I: Towards the Use of Bioassays as Predictors of Adverse Events in Clinical Trials
Matthew Clark, Ph.D., Consultant Research & Development Solutions, Elsevier
To reduce clinical trial failures we have studied a method of using inexpensive bioassays to predict adverse event risks in clinical trials. We used data from FDA submissions and bioactivities from journals and patents to create 2x2 contingency tables
for each target/event combination. The relationships were then studied with pathway analysis to understand the models.
1:10 Luncheon Presentation II: Informatics in the Fast Lane
Shooki Grasiani, Senior Manager, Global Marketing and Product Management, Specialty Products, Product Marketing, Abbott Informatics
In order to survive in a rapidly evolving and competitive environment, organizations must accelerate innovation and adopt agile solutions which remove barriers to innovation. In this session, Shooki will cover strategies and tactics around the reality
check of the laboratory informatics’ promise, the shifts in the laboratory informatics macro-environment and technological trends that will reshape the laboratory informatics landscape.
1:40 Session Break
1:50 Chairperson’s Remarks
Rich Lysakowski, Ph.D., Professor of Bioinformatics and Data Science; Principal Software Engineer and IT Applications Specialist, Network Technology Academy Institute
1:55 PANEL DISCUSSION: Linking and Finding Information Using the IUPAC InChI Standard for Chemical Structures
Steve Heller, Ph.D., Project Director, InChI Trust; Scientific Information Consultant (Moderator)
Evan Bolton, Ph.D., Lead Scientist, National Center for Biotechnology Information (NCBI), National Library of Medicine (NLM), and National Institutes of Health (NIH)
Keith T. Taylor, BSc, Ph.D., MRSC, Principal, Ladera Consultancy
Tyler Peryea, Informatics Scientist, National Center for Advancing Translational Sciences (NCATS)
Lawrence Callahan, Ph.D., Chemist, Substance Registration System, Office of Critical Path Programs, Food and Drug Administration (FDA)
This session will highlight on-going efforts to strengthen and expand the non-proprietary IUPAC International Chemical Identifier (InChI) standard for chemical structures and its hashed-form, the InChIKey. Information standards are critical to enable
effective communication of scientific content. Funding to maintain InChI comes from most major publishers and database providers as well as governmental agencies (NIH, FDA and NIST). The InChI is an open-source, widely adopted standard found in
most chemical information containing databases, including those from Chemical Abstracts, Reaxys, ChEMBL, OpenPHACTS, PubChem, DrugBank, PDB, Sigma-Aldrich, and many others, such as internal Pharma corporate databases. InChI is an addition to a
database, not a replacement. With the implementation of the ISO identification of medicinal products (IDMP) and the related ISO 11238 standards, adding and having an InChI will allow for an easier, effective, and more complete search for information
on a particular drug.
2:55 Integrated Informatics for Biologics Discovery
Robert Brown, Ph.D., Vice President, Product Marketing, Dotmatics
A presentation looking at the challenge of supporting biologics discovery and current solutions. Highlighting the value of an integrated informatics solution. It will also include an example biologics discovery workflow using Bio ELN, Biological Registration
and Vortex Bioinformatics.
3:25 Refreshment Break in the Exhibit Hall with Poster Viewing
4:00 Building Disease Networks Using Text Mining and Machine Learning Techniques
Kamal Rawal, Ph.D., Assistant Professor, Biotech and Bioinformatics, Jaypee Institute of Information Technology
Obesity is a global epidemic affecting over 1.5 billion people and is one of the risk factors for several diseases such as type 2 diabetes mellitus and hypertension. We have constructed a comprehensive map of the molecules reported to be implicated
in obesity. Using text mining & deep curation strategies combined with omics data, we have explained the therapeutics and side effects of several drugs (i.e., orlistat) at network level.
4:20 Big Data and Systems Biology: From Genome to Phenome (and Everything in Between)
Dan Jacobson, Ph.D., Computational Biologist, Oak Ridge National Laboratory
4:40 Novel Feature Selection Strategies for Enhanced Predictive Modeling and Deep Learning in the Biosciences
Tom Chittenden, Ph.D., D.Phil., Lecturer and Senior Biostatistics and Mathematical Biology Consultant, Harvard Medical School
We have built a robust AI approach that precisely assesses pathogenicity for all genomic missense variants. Coupled with our advanced deepCODE mathematical statistics feature selection strategy for constructing deep learning models, we are able to
quantitatively integrate a priori pathway-based biological knowledge with multiple types of high-throughput omics data.
of Predictive Analytics and CBDD for Indication Prioritization
Marina Bessarabova, Ph.D., Senior Director, Discovery and Translational Science, Life Sciences Professional Services, Clarivate Analytics (Formerly the IP & Science Business of Thomson Reuters)
Elia Stupka, Ph.D., Director, Genomics and Computational
Biology, Boehringer Ingelheim
Systems biology is a powerful approach to drug development. CBDD is a precompetitive consortium between Clarivate Analytics, Novartis, Pfizer, Sanofi, Janssen, Regeneron, UCB, Roche, Takeda, Biogen, Boehringer Ingelheim, Bristol-Myers Squibb, Merck,
and Eli Lilly, focused on implementation of advanced systems biology methods. Clarivate Analytics will present CBDD scope and Boehringer Ingelheim will present application of CBDD developments for indication prioritization.
5:30 – 6:30 15th Anniversary Celebration in the Exhibit Hall with Poster Viewing and Best of Show Awards
Thursday, May 25
7:00 am Registration Open and Morning Coffee
8:00 PLENARY KEYNOTE SESSION & AWARDS PROGRAM
8:05 Benjamin Franklin Awards and Laureate Presentation
8:35 Best Practices Awards Program
8:50 Plenary Keynote
9:45 Coffee Break in the Exhibit Hall and Poster Competition Winners Announced
10:30 Chairperson’s Remarks
Bino John, Ph.D., Computational Biology Group Leader, Dow AgroSciences LLC
10:40 How Biotech and Big Data Are Changing Agro Industry
Bino John, Ph.D., Computational Biology Group Leader, Dow AgroSciences LLC
More than 70% of the increase in food production in the next 50 years is expected to come from technological advances. Indeed, recent advances in genomics and phenomics are beginning to transform the Agro-industry, whereby creating new opportunities
for informatics disciplines. While informatics needs in managing, analyzing, and visualizing big data share commonalties between Agro and the biomedical communities, Agro companies face unprecedented challenges in big biological data, generally
larger than their peers in the biomedical community.
11:10 Offering Outcomes: How Digital Farming Data Is Enabling New Business Models
Chris Paterson, Lead, Digital Farming North America, Bayer Crop Science
11:40 Building the Next-Generation R&D IT Infrastructure for Small Molecule Discovery
Paimun Amini, Chemistry IT Lead, R&D IT, Monsanto Company
Barrett Foat, Ph.D., Data Science Team Lead, Agricultural Productivity Innovations, Monsanto
The Pharma boom in the 90s & 2000s led to the emergence of a rich ecosystem of software companies focused on delivering the IT needs for small molecule discovery. Today, cloud data storage, IoT, and the growth of predictive analytics present new
opportunities for the evolution of the R&D pipeline. New technologies allow for integrated software and hardware solutions that optimize productivity while removing the risk of technical debt.
12:10 pm Session Break
12:20 Luncheon Presentation: CLC Genomics Cloud Engine: Enterprise NGS Made Easy
Jacob Nikolajsen, Cloud Architect, QIAGEN
Reaping the benefits of cloud computing takes more than just moving servers and data online. Ensuring a secure solution and a smooth transition to the cloud is far from trivial, in particular if results are expected to be identical to an on-premise solution. QIAGEN CLC product line is the leading solution for NGS analysis, proven to minimize cost per analysis on Intel CPUs.
1:20 Dessert Refreshment Break in the Exhibit Hall with Poster Viewing
1:55 Chairperson’s Remarks
Michael N. Liebman, Ph.D., Managing Director, IPQ Analytics, LLC and Strategic Medicine, Inc.
2:00 Distinguishing between Precision Medicine and Accurate Medicine: Application to Heart Failure Patients and Clinical Practice
Michael N. Liebman, Ph.D., IPQ Analytics, LLC and Strategic Medicine, Inc.
Increasingly, patient stratification based on genomic analysis is being considered in disease management. Critically, the need to understand real world medical practice and real world patient complexities extends far beyond the genome of the patient.
We have shown examples of this complexity in heart disease and how this impacts development of clinical guidelines, trial design, and development of new patient management approaches.
2:30 CARPEDIEM - Comorbidity and Risk Profiles Evaluation in Diabetes and Heart Morbidities
Sabrina Molinaro, Psy.D., Ph.D., Head, Department of Epidemiology and Health Services, Institute of Clinical Physiology, National Research Council of Italy
Our project uniquely develops a patient record that includes clinical and individual factors (EHR-driven phenotyping) that will be validated through the comparison of existing standards for building new risk algorithms. An understanding of the
current limitations and biases of risk profiling in heart disease and diabetes and how an extended, integrated database and automatic rule-based classification system can be used to improve patient management.
3:00 PANEL DISCUSSION: Precision Medicine vs. Accurate Medicine: The Need to Understand Real World Medicine and Real World Patients
Michael N. Liebman, Ph.D., IPQ Analytics, LLC and Strategic Medicine, Inc. (Moderator)
Charles Barr, M.D., MPH, Group Medical Director and Head, Evidence Science and Innovation, Genentech
Jonathan Morris, M.D., Vice President, Provider Solutions and Chief Medical Informatics Officer, Real World Insights, QuintilesIMS
Nandabalan, Ph.D., President, CSO and Co-Founder, BioXcel
Hal Wolf, Director, National Leader of Information and Digital Health Strategy, The Chartis Group
4:00 Conference Adjourns