Breakout Discussions
Tuesday, March 12,
2019 • 5:00 - 6:00 pm • Exhibit Hall
These interactive discussion groups are open to all attendees, speakers, sponsors, & exhibitors. Participants choose a specific breakout discussion group to join. Each group has a moderator to ensure focused discussions around key issues within the
topic. This format allows participants to meet potential collaborators, share examples from their work, vet ideas with peers, and be part of a group problem-solving endeavor. The discussions provide an informal exchange of ideas and are not meant
to be a corporate or specific product discussion. The list of topics below span Tri-Con’s three Channels: Molecular Dx & Digital Health, Liquid Biopsy & Immuno-Oncology, and Bio-IT World West.
Table 1
Data-Driven Diagnostics
Bryan Cobb, Partner Lead, Diagnostics Information Solutions, Roche Mark Nunes, MD, Division Chief, Medical Genetics, Kaiser Permanente
- Advanced analytics for integrative diagnostics
- Advanced analytics and AI for genomics applications
- The Learning Healthcare System/RWD to enable precision medicine
Table 2
Payers and Regulators: Recent Developments
Wade M. Aubry, MD, Associate Clinical Professor of Medicine and Core Faculty, PRL-IHPS, UCSF, Former BCBS
and Medicare Medical Director
Alberto Gutierrez,
PhD, Partner, NDA Partners LLC; Former Director, Office of In Vitro Diagnostics and Radiological Health, FDA
Table 3
Whole Genome Sequencing as a Diagnostic Test
Phil Febbo, MD, CMO, Senior Vice President, Clinical Genomics, Illumina
- What are the logistical challenges to clinical whole genome sequencing?
- In what settings is there already clinical utility?
- How can we get to a
better annotated whole genome and more utility?
Table 4
Utilizing Whole Slide Imaging and Image Analysis in the Histology Laboratory for Quality Assurance and Improvement
Elizabeth A. Chlipala, BS, HTL(ASCP)QIHC, Laboratory Manager, Premier Laboratory, LLC
- The importance of standardization and quality process improvement in histotechnology and its significance to the success of implementing a digital pathology solution
- Utilization of digital pathology technology to improve overall efficiency and quality of the histology preparations
- Utilization of digital pathology technology to document the accuracy and precision of a histology process
Table 5
Digital Pathology Interoperability Priorities
Raj C. Dash, MD, Professor and Vice Chair, Pathology IT, Duke University Health System; Medical Director, Laboratory Information Systems
- Describe the needs of your organization as a consumer of or contributor to a larger digital pathology environment
- Discuss the current level of interoperability among current market offerings in Digital Pathology
- Help prioritize the efforts of standard setting and interoperability initiatives for Digital Pathology
Table 6
Digital Pathology Applications for Predictive Biomarkers
Ehab A. ElGabry, MD, Senior Director, Pathology & Companion Diagnostics, Pharma Services Medical Director, Ventana Medical Systems, Inc., A Member of the Roche Group
- Multiplexing
- Digital training and electronic learning modules
- Clinical scoring algorithms development
Table 7
Practical Considerations when Implementing Digital Pathology
Douglas J. Hartman, MD, Associate Professor of Pathology and Director, Division of Pathology Informatics, University of Pittsburgh Medical Center, Ventana Medical Systems, Inc., A Member of the Roche Group
- Presenting digital pathology to different stakeholders in your institution
- Establishing a return on investment for digital pathology
- Unique capabilities that can only be offered thru digital pathology
Table 8
Pathology AI: The Promise and the Problems
Michael C. Montalto,
PhD, Vice President, Pathology and Clinical Biomarker Laboratories, Translational Medicine, Bristol- Myers Squibb
- Application of AI to pathology in translational medicine
- Pathology AI based companion and complementary diagnostics
- Barriers to adoption of pathology AI in clinical practice
Table 9
The Future of Vertical and Lateral Flow Diagnostic Devices
Shawn Mulvaney,
PhD, Section Head, Surface Nanoscience and Sensor Technology Section, Chemistry, US Naval Research Laboratory
- Overcoming the limitations in sensitivity
- Making these devices quantitative
- POC to hospital lab? Just how far up the healthcare ladder will VFI/LFI devices reach?
Table 10
AI and ML in Pathology Practice
Hooman H. Rashidi, MD, FASCP, Professor and Vice Chair, GME, Director of Residency Program; Director, Flow Cytometry & Immunology, Department of Pathology and Laboratory Medicine, University of California, Davis School of Medicine
- Data types
- Types of ML platforms
- Validation of ML platforms in pathology
Table 11
Home-Based Diagnostic Testing
Paul Yager,
PhD, Professor, Bioengineering, University of Washington
- Ongoing changes in US domestic healthcare
- POC NAAT Testing
- New opportunities for home testing
Table 12
The Future of Pharmacy-Based Point-of-Care Testing
Donald Klepser,
PhD, MBA, Associate Professor
and Vice Chair, Pharmacy Practice, University of Nebraska Medical Center
- Opportunities and challenges in pharmacy-based POCT
- Training and certification needs
- Current regulations
Table 13
Overcoming Barriers to More Accurate and Scalable Genetic Variant Classification
Julie M. Eggington, MS,
PhD, Co-Founder and CEO, Center for Genomic Interpretation (CGI)
- Identify the real barriers that may be holding back the industry
- Discuss current solutions and how they might be improved
- Imagine the continued evolution of paradigms
NEW CANCELATION: Table 14
Best Practices for Clinical Validation of Bioinformatics Pipeline
Somak Roy, MD, Director, Molecular Informatics, Genetics Services, & MGP fellowship, Molecular and Genomic Pathology, University of Pittsburgh Medical Center
Applicability of the guidelines in the context of distributive NGS testing modelCan in silico datasets be used for bioinformatics pipeline validation?Guidelines in the context of clinical laboratory accreditation checklist (CAP) for NGS bioinformatics
Table 15
Bioinformatics Quality at Clinical Scale
Elaine P.S. Gee,
PhD, Founder & President, BigHead Analytics Group; Principal Algorithm Development Engineer, Sensor R&D, Diabetes R&D, Medtronic
- Scaling bioinformatics pipelines while maintaining quality
- Designing validations for distributed
compute systems
- Regulatory technology for clinical bioinformatics
Table 16
Digital Health Platforms Incorporating Diverse Data Sources
NEW: Kuan-Fu Ding,
PhD, Chief Science Officer, Sapiens Data Science, Inc.
- What are the most important data sources?
- How can in silico algorithm validation be used to accelerate progress?
- How (and when) will medicine transition
to from pattern recognition to quantitative data science for clinical decision support?
- How will consumers be involved in
use of quantitative data science use on their individual health journeys?
Table 17
Around the Globe Strategies for Diagnostics and Clinical Biomarkers
Marielena Mata,
PhD, Director and Diagnostic Lead, Companion Diagnostics, Pfizer
Mark Curran,
PhD, Vice President, Immunology, Head, Companion Diagnostics, Janssen R&D LLC
- Preparing for the implementation of the new EU regulatory framework for CDx
- Challenges with single site PMAs and worldwide implementation
- Similarities and differences in regulatory requirements across the world. How to plan Dx global strategy and satisfy all requirements
Table 18
Evolutionary Biomarkers: New Ways to Work with Pharma Companies
Alex Vadas,
PhD, L.E.K. Consulting
Table 19
Genomic Diagnostics in Solid Tumors: Current Practices and Future Developments
Larissa V. Furtado, MD, Medical Director, Molecular Oncology, ARUP Laboratories, Associate Professor of Pathology, University of Utah School of Medicine
Recognize the indications, specimen requirements, applications, and limitations of
next generation sequencing (NGS)‐based test for solid tumor testingDemonstrate familiarity with NGS clinical implementation and interpretive principles of NGS‐ based test for solid tumor testingBecome familiar with future trends in personalized solid tumor managementTable 20
Hidden Challenges in Building and Analyzing Biological Networks
Kimberly Glass,
PhD, Assistant Professor of Medicine, Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School
- The role of networks in understanding biological systems and diseases
- Methods for constructing biological networks
- The strengths and limitations of different types of biological networks
- The types of questions that can be answered using biological networks
Table 21
Implementing Molecular Tumor Board in The Community Setting
Timothy Cannon, MD, Gastrointestinal Malignancies, Clinical Director, Inova Schar Cancer Institute Molecular Tumor Board; Assistant Professor, Virginia Commonwealth University
- How a molecular tumor board changes treatment paradigms
- Molecular tumor board.
Cost effective?
- Addressing physician concerns that targeted therapy is overhyped and under‐delivers
- Patient perception of molecular tumor board and targeted therapy in general
Table 22
Roadblocks to Functional Precision Medicine
Christopher Kemp,
PhD, Full Member, Human Biology, Fred Hutchinson Cancer Research Center
- How to obtain off label drugs
- How to routinely save live cancer biopsies
- How to design N=1 or drug combination clinical trials
Table 23
Frontiers in Wearable Sensors, Ambient Sensing and Big Data Analytics
Peter G. Jacobs,
PhD, Assistant Professor, Department of Biomedical Engineering, Artificial Intelligence for Medical Systems (AIMS) Lab, Oregon Health & Science University
- What are the new sensors in development/coming soon expected to impact health?
- What new techniques in ambient sensing techniques are being developed and how are they displacing or augmenting wearables?
- How are big data sets including electronic health records, public donated data sets, and genomic data sets impacting new healthcare solutions?
- How is machine learning leveraging the intersection of ubiquitous sensing and big data sets?
Table 24
Parallel Analysis of Circulating Biomarkers in Immunotherapy
Genevieve Boland, MD,
PhD, Director, Melanoma Surgery Program, Massachusetts General Hospital; Director, Surgical Oncology Research Laboratories, Massachusetts General Hospital; Assistant Professor, Harvard Medical School; Associate Member, Broad Institute
- Clinical application of blood-based biomarkers in melanoma
- Unmet clinical needs in blood-based biomarkers
- Microvesicle applications in immunotherapy
Table 25
Clinical Utility and Impact of Liquid Biopsy
Rajan Kulkarni, MD,
PhD, Assistant Professor, Medicine and Radiation Oncology, David Geffen School of Medicine, UCLA
- Necessary features of technologies/tests for clinical utility
- Tumor information that is of clinical relevance
- Necessity for standardization
Table 26
The Importance and Challenge in CTC Culture
Yong-Jie Lu, MBBS, MD,
PhD, Professor, Centre for Molecular Oncology, Barts Cancer Institute, Queen Mary University of London
- Why is CTC culture important?
- What is the challenge?
- Does it worth to try it?
- Alternative ways to avoid it?
- How can we
success with CTC culture? The researcher, technology development and the funding supporter/policy marker.
- Openness on collaboration for the benefit of all
Table 28
Isolation and Analysis of CTCs
Min Yu, MD,
PhD, Assistant Professor, Stem Cell Biology and Regenerative Medicine Member, Norris Comprehensive Cancer Center, Keck School of Medicine, University of Southern California
- Downstream analysis of circulating tumor cells
- Technologies for CTC isolation
- Experimental mouse models for metastasis analysis
- Using CTCs as
liquid biopsy
Table 29
Precision Medicine in IO
George Green,
PhD, Head, Pharmacodiagnostics, Bristol-Myers Squibb
- How can we better identify clinically relevant combination therapies upfront?
- Are there ways to improve patient selection for IO therapy?
- What are common challenges with IO therapy in the real-world setting?
Table 30
Emerging Technologies for IO Biomarkers
Benoit Destenaves, PharmD, Director, Precision Medicine Lead, Precision Medicine and Genomics, Innovative Medicines and Early Development, AstraZeneca
Table 31
Target Identification from Omic Data
Zhongming Zhao,
PhD, Professor and Director, Center for Precision Health, School of Biomedical Informatics, University of Texas Health Science Center at Houston
- Target identification and validation using genomics and genetics
- Using clinical transcriptomics-based generation of disease signatures, and their application in drug discovery
- Clinical trial-derived data for discovery
Table 32
Machine Learning for
Data Driven Drug Discovery
Renee Deehan Kenney, Vice President, Computational Biology, PatientsLikeMe
Pankaj Agarwal,
PhD, FRSB, Senior Fellow & Senior Director, Computational Biology, RD Target Sciences, GSK
- What are the biggest challenges we are facing in the application of machine-learning to omics data?
- How are researchers applying prior knowledge to solve this problem?
- How are researchers applying purely data-driven approaches to select features?
Table 33
Practical Machine Learning in Industry
Patryk Laurent,
PhD, Director of Emerging Technology, Office of the CTO, DMGT plc
- Accessibility of machine learning hardware, software, and expertise
- How to assess if machine learning will succeed or fail on your problem
- Workflows for data scientists: what works, what remains a challenge
Table 34
Exploring the Power of Quantum Computing for Science and Discovery
Ahmed Abdeen Hamed,
PhD, Applied Computer Scientist, Quantum Computing, Merck & Co.
- Current scientific needs
- State of the art quantum computing
- Applications and computation
Table 35
Diversity and Inclusion in Bio-IT
Tanya Cashorali, CEO, Founder, TCB Analytics
Lisa Dahm,
PhD, Director, Enterprise Data & Analytics, UC Irvine Health Information Services; Associate Director, Center for Biomedical Informatics, Institute for Clinical and Translational Sciences; Director, UC Health Data Warehouse, Center for
Data Driven Insight, UC Health, University of California, Irvine
Chris Dwan, Senior Technologist
and Independent Life Sciences Consultant
Ruchi Munshi, Product Manager, Data Sciences Platform, The Broad Institute
- Useful practices for people at all levels and roles in an organization
- Today’s major challenges
- Measurable goals and aspirations
- Role models and resources