Track 11: Cancer Informatics

The Cancer Informatics track explores the important technology and informatics trends and challenges of applying computational biology and clinical data to cancer research and care. Themes that will be covered in expert-led presentations include collaboration and network models, data access/management/integration strategies, visualization tools, and applications of biological interpretation to aid in research at the bench side or care at the bedside.

Final Agenda

Tuesday, April 16

7:00 am Workshop Registration Open and Morning Coffee


8:0011:30 Recommended Morning Pre-Conference Workshops*

W6. DNA Sequencing 101

12:304:00 pm Recommended Afternoon Pre-Conference Workshops*

W12. Data Science Driving Better Informed Decisions

* Separate registration required.

2:006:30 Main Conference Registration Open

4:00 PLENARY KEYNOTE SESSION
Amphitheater

5:007:00 Welcome Reception in the Exhibit Hall with Poster Viewing


Wednesday, April 17

7:30 am Registration Open and Morning Coffee

8:00 PLENARY KEYNOTE SESSION
Amphitheater

9:45 Coffee Break in the Exhibit Hall with Poster Viewing


TOOLS THAT BEST UTILIZE DATA TO DRIVE CLINICAL DECISION MAKING AND BIOLOGICAL KNOWLEDGE
Beacon Hill

10:50 Chairperson’s Remarks

Robert Zeigler. PhD, Director, Customer Solutions, L7 Informatics, Inc.

11:00 Making Clinical Data Available to Researchers at the Princess Máxima Center for Pediatric Oncology with tranSMART and cBioPortal

Patrick Kemmeren, PhD, Principal Investigator, Princess Máxima Center for Pediatric Oncology

The Princess Máxima Center for Pediatric Oncology (https://www.prinsesmaximacentrum.nl/en) is the centralized pediatric oncology center for all children with cancer in the Netherlands since 2018. As a new institute, the Princess Máxima Center has had the opportunity to set up their research IT infrastructure right from the start, with limited legacy software to take into account. By building a Central Subject Registry (CSR), the center’s researchers have full access to pseudonymized data from all relevant hospital data sources in a timely manner. At regular intervals the data from all hospital data sources are exported, transformed and pseudonymized, to be loaded in both the tranSMART and cBioPortal data warehouses, where the center's researchers can easily create their 'shopping list’ for patients and samples of interest. The oncology center even extended the Glowing Bear user interface to notify researchers by email when new patients of interest are available, to ensure no time is lost waiting for research data and samples.

11:30 CO-PRESENTATION: Building a Standards-Based Clinical Data Resource for Cancer: Challenges, Goals, and Progress

Eva Lepisto, Data Services Team Lead, Dana-Farber Cancer Institute

Oncology’s pioneering role in precision medicine has led to routine tumor sequencing; Dana-Farber has clinically sequenced more than 30,000 tumors. However, the incompleteness and inconsistency of clinical data from EHRs and other sources present significant challenges to building the patient-specific diagnosis, treatment and outcome data that are required to discover correlates to genomic data that inform diagnosis, prognosis, and personalized treatment. At DFCI, we are striving to improve the quality and coverage of clinical data for translational research and clinical decision support. In this presentation, we will describe the standards-based data model we have created for representing cancer patient phenotypes, along with a curation software platform we have developed to streamline abstraction of unstructured data into the standard data model and NLP approaches to populating the same model from clinical text.

Discngine 12:00 pm Discngine presents 3decision, a Collaborative Platform for Structural Knowledge Management

Eric Le Roux, CEO, Discngine

Peter Schmidtke, Scientific Project Manager, Discngine

Discngine develops innovative IT solutions for Life Science research. In 2018, It launched 3decision, a web application that combines a fully annotated & searchable protein structure database and a web-based user interface with state of-the-art structural analytical tools. The user interface is designed to give molecular modelers, medicinal chemists and structural biologists a common ground for structure-based drug discovery.

12:15 CASE STUDY: How a Top Pharmaceutical Company Supports Scientific Discovery with Contextualized Information Retrieval

Michael Iarrobino, Senior Product Manager, Copyright Clearance Center

A pharmaceutical company needed a better way to support scientific discovery and realize the value of its information assets. But, with siloed data, a lack of awareness of available licensed resources, and multiple discovery workflows it was taking researchers too long to find information and synthesize data to advance research. In this session, learn how the organization tackled these challenges.

12:30 Session Break

12:40 Luncheon Presentation I: Keys to Success in Preclinical Informatics Development; All About That Data

Graeme Dennis, Commercial Director, Pre-Clinical Pharma, IDBS

In the R&D industry today, beleaguered system implementations are more common than anyone would prefer to admit.  Data harmonization tasks, expectation management, and risk mitigation opportunities can pass before their urgency is even fully appreciated. This 30-minute talk will explore the keys to success for developing a data-centric approach to R&D, which acknowledges the breadth of project workstreams.

Certara

1:10 Luncheon Presentation II: Certara Integral: Next Generation Data Repository

Kevin Trimm, Senior Director, Product Strategy & Services, Software, Certara

A successful drug development program relies on data being centralized in an accessible, understandable, mineable, traceable, and secure location for analysis and interpretation.  Provisioning data to scientists in an organized manner with high performance can be a challenge.  Certara Integral is a validated and 21 CFR Part 11 compliant software as a service data and model repository utilizing the CDISC data model and Amazon Web Services Infrastructure, providing an intuitive solution to this problem.

1:40 Session Break

REVOLUTIONIZING DRUG DEVELOPMENT WITH NEW DISEASE MODELS AND SIMULATION METHODS: CASE STUDIES OF COLLABORATIVE GLOBAL EFFORTS
Amphitheater

1:50 PANEL DISCUSSION: Revolutionizing Drug Development with New Disease Models and Simulation Methods: Case Studies of Collaborative Global Efforts

Chairperson and Moderator:

Anil Srivastava, President, Open Health Systems Laboratory

Panelists:

Jeffrey Buchsbaum, MD, PhD, AM, Medical Officer and Program Director, Radiation Research Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute/NIH

Rajendra Joshi, PhD, Associate Director and HOD Bioinformatics Group, Centre for Development of Advanced Computing (C-DAC), Pune University Campus

Tonglei Li, PhD, Allen Chao Chair and Professor of Department of Industrial and Physical Pharmacy, College of Pharmacy, Purdue University

3:25 Refreshment Break in the Exhibit Hall with Poster Viewing, Meet the Experts: Bio-IT World Editorial Team, and Book Signing with Joseph Kvedar, MD, Author, The Internet of Healthy Things℠ (Book will be available for purchase onsite)

BIOMARKER DETERMINATION IN A DIAGNOSTIC CONTEXT: ISSUES AND CHALLENGES WITH IDENTIFICATION, VALIDATION, DEVELOPMENT, AND IMPLEMENTATION OF TOOLS FOR CANCER SCREENING, DIAGNOSIS, AND TREATMENT
amphitheater

4:00 PANEL DISCUSSION: The Difference between Biomarkers and Diagnostics: It’s Bigger Than You Think

Moderator:

Michael N. Liebman, PhD, IPQ Analytics, LLC and Strategic Medicine, Inc.

Panelists:

Michael Montgomery, MD, Global Executive Director, Incyte Corporation

Jonathan Morris, MD, Vice President, Provider Solutions; Chief Medical Informatics Officer, Real World Insights, IQVIA

Jun Zhu, PhD, Professor, Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai

Biomarkers are used to evaluate cancer risk, detect end stage cancer and suggest optimal therapy for specific patients. Recent advances in -omics research continue to enable researchers to classify molecular fingerprints of specific cancers. Discovery and development of new cancer markers remains a major research focus to improve screening, diagnosis, and treatment but is hampered by the limited knowledge of the details of disease progression. This challenges the ability to identify markers that may be causal rather than correlative and impacts their use as true diagnostics. By example, literature analysis of 250,000 papers listing biomarkers in cancer yield less than 100 FDA approved diagnostics. Every experiment yields a biomarker; however, every experiment does not yield a diagnostic that can more accurately drive clinical action. How can we close this gap? It is critical to develop a better understanding of the disease process and how observations from genomics, proteomics, and metabolomics may impact that process in different ways. This interactive panel will explore experimental and analytic methods, issues and challenges impacting identification, validation, development and implementation in cancer, diagnosis and treatment.


5:30 Best of Show Awards Reception in the Exhibit Hall with Poster Viewing

Thursday, April 18

7:30 am Registration Open and Morning Coffee

8:00 PLENARY KEYNOTE SESSION & AWARDS PROGRAM
Amphitheater

9:45 Coffee Break in the Exhibit Hall and Poster Competition Winners Announced

VISUALIZING PRECISION ONCOLOGY
Back Bay

10:30 Chairperson’s Remarks

Carlos Rios, PhD, Senior Research Investigator, Computational Genomics - Translational Medicine, Bristol-Myers Squibb

10:40 Longitudinal and Context Visualization for Precision Oncology

Jeremy Goecks, PhD, Assistant Professor of Biomedical Engineering and Computational Biology, Oregon Health and Science University

The goal of precision oncology is to find effective treatments for each patient’s cancer based its molecular profile. Visualization plays a key role in precision oncology, helping to understand and integrate longitudinal and complex data analyses and then communicate results to physicians, patients, and other stakeholders. We will discuss our work applying visualization for precision oncology and identify opportunities and challenges for visualization in precision oncology going forward.

11:10 Sharing and Visualizing Cancer Genomics Datasets Using cBioPortal

Carlos Rios, PhD, Senior Research Investigator, Computational Genomics - Translational Medicine, Bristol-Myers Squibb

BMS has been using cBioPortal for visualizing cancer genomics datasets since early 2016, supported by The Hyve, an open source bioinformatics company based in the Netherlands. The cBioPortal server runs on Amazon AWS and is tied to the company’s Active Directory for authentication and uses Keycloak for authorization. Data can be loaded through a pipeline that takes input files from Amazon S3. For BMS, cBioPortal was extended with support for rich metadata and canvasXpress integration.

11:40 OncoThreads: Exploratory Visualization of Longitudinal Cancer Genomics Data

Theresa Anisja Harbig, MS, Research Associate, Visiting Graduate Student, Biomedical Informatics, Gehlenborg Lab, Harvard Medical School

New immuno-profiling assays and liquid biopsies have enabled researchers to study tumor development over time and to explore the effect of different therapies on cancer.  To support exploration of such datasets, we developed OncoThreads, a tool for the visualization of longitudinal cancer genomics data in patient cohorts (http://oncothreads.gehlenborglab.org/). The tool is based on alignment of patient timelines into blocks, which can show data associated with patient samples or events such as drug administration.  We demonstrate how the design of OncoThreads enables researchers to find temporal patterns in longitudinal cancer genomics data, such as effects of treatments on mutation patterns

12:10 pm Enjoy Lunch on Your Own (Lunch Available for Purchase in the Exhibit Hall)

1:20 Dessert Refreshment Break in the Exhibit Hall with Poster Viewing

methods and models to better utilize data for risk assessment, diagnosis and treatment
Harborview 3

1:55 Chairperson’s Remarks

Yuval Itan, PhD, Assistant Professor, Department of Genetics and Genomic Sciences; Member, Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai

2:00 Pinpointing Transcript-Damaging Disease-Causing Variants as a Major Step towards RNA Therapeutics

Sahar Gelfman, PhD, Associate Research Scientist, Columbia University Medical Center

Since its publication in 2017, the Transcript-inferred Pathogenicity (TraP) model has become a major resource for genetic diagnostics, identifying pathogenic non-coding variants, and helping to change the common conception that pathogenic genetic variation is caused solely by coding mutations. TraP has been incorporated in diagnostic pipelines in tens of research institutes worldwide. TraP is also available as a website for single queries (www.trap-score.org), providing successful diagnosis of genetic disorders and affecting treatment decisions.

2:30 AI Assisted Rapid Clinical Whole Genome Sequencing for Critical Care

Ray Veeraraghavan, PhD, Director of IT & Informatics, Rady Children's Institute for Genomic Medicine

3:00 Deciphering the Complex Heterogeneity of Cancer

Patrice M. Milos, PhD, Co-Founder/President and CEO, Medley Genomics, Inc.

Medley Genomics provides a software platform that uses patent-pending algorithms and advanced data analytics to describe a patient’s diverse tumor cell mixture. This enables creation of unique molecular diagnostic fingerprints for improving patient diagnosis, monitoring and treatment of cancer, and helps to improve novel oncology therapies and therapeutic combinations including individual cancer vaccine development.

3:30 Estimating Genotypic Heterogeneity Underlying Human Disease

Yuval Itan, PhD, Assistant Professor, Department of Genetics and Genomic Sciences; Member, Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai

Whole exome and whole genome sequencing provide hundreds of thousands of genetic variants per patient, of them only very few are pathogenic. Current computational methods are inefficient in differentiating pathogenic mutations from neutral genetic variants that are predicted to be damaging and cannot predict the functional outcome of mutations. We will present deep learning approaches and machine learning methods in the role of detecting pathogenic mutations. Visualization tools for better utilizing NGS data will be presented to understand human disease genomics.

4:00 Conference Adjourns

Platinum Sponsors:

accenture

Dell EMC

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IBM_Blue

IDBS

Lucidworks

Microsoft

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