BioData World West 2017 agenda - day 2

 

BioData USA West: Day 2

09:00

Making the journey from Big Data to Smart Data

  • Big data: Current technical and organization capacity (where are we now)
  • From big data to smart data (where we are going and why is it important to get it right)
  • Changing the world one step at a time.
 
09:20

Big Data and genomics in space

  • The GeneLab initiative - An Open Access Multi-Omics database of living samples flown in space: from microbes to plants, to mammals
  • Not everyone knows bioinformatics: Strategies to democratize omics data to reach the science community and public at large
  • When users become bot: The emergence of new knowledge of life adaptation in space
 
09:40

Advancing precision medicine through collaboration and big data

  • Accessing data by download is an untenable model in the large-scale genomics era
  • Data deposited in databases that do not update the alignment and/or calling as technology advances quickly becomes stale and unusable.
  • The NCI Genomics Data Commons tries to solve those issues by being a constantly updated database that will allow users to do queries online without the need to download the bulk of the raw data.
 
 
10:00

Exhibition Viewing and morning refreshments

 
 

Genomics and Health

 

Precision Medicine

 

Artificial Intelligence

 
 
Artificial Intelligence
10:40

Deep learning in medicine: an introduction and applications to next-generation sequencing and disease diagnostics

  • We review the history and taxonomy of machine learning and artificial intelligence
  • We will introduce deep learning, covering both what it is and why its so exciting.
  • We will then discuss in detail two concrete applications to life sciences problems:
  • Calling SNP and indel variants in next-generation sequencing data
  • Detection of diabetic retinopathy from fundus images of the eye
 
 
Genomics and Health
11:20

Understanding the non-coding genome

  • How much new information do we expect from the non-coding human genome
  • Why is exome sequencing not enough?
  • Where are the pathogenic variants in the non-coding genome?
 
Precision Medicine
11:20

Big Data, Genomics and Personalised Medicine: Future paths for the AHA

  • AHA launches MY RESEARCH LEGACY - AN OPPORTUNITY FOR ALL INDIVIDUALS TO ENGAGE IN LIFE LONG LEARNING TO IMPROVE THEIR OWN HEALTH AND THE HEALTH OF THOSE AROUND THEM, through biosensors, technology and community. “the Individual”
  • AHA strategic partners and the “tech platform” underneath My Research Legacy
  • The data from My Research Legacy - driving towards solutions for millions of patients
 
 
Genomics and Health
11:40

Using big data and AI to drive clinical drug development: deep subtyping of disease; continuous knowledge integration

  • Integrating multimodal genomic and clinical data (public and proprietary) to build dynamic data-driven maps for hundreds of disease conditions
  • Deep molecular and immune-infiltrate characterization of disease subtypes based on thousands of patient samples
  • Biologically-guided machine learning to predict response to single agents and drug combinations
 
Precision Medicine
11:40

Emerging Opportunities for Genomic Big Data Analytics in the Plecosystem Economy

  • Critical opportunities for blockchain in Cancer Genomics: Micro-credit Accounting for data donors, institutional data users, ontology annotators, somatic read annotators, decision support algorithms etc.
  • Emerging methods for early detection of onset and recurrence: The specificity/sensitivity dilemma
  • Critical need for biomarkers across the plecosystem that help disambiguate isolated genomic data.
 
Artificial Intelligence
11:40

Building the Genomic Infrastructure that Powers Personalized Medicine

  • Utilizing FPGAs in the cloud for highly efficient, optimized and low-cost data analysis
  • Creating a true sample to answer platform
  • Aggregating omics data for machine learning and AI
 
 
12:00

Lunch/Networking

 
 
Genomics and Health
13:20

Realizing the transformative potential of genomics in healthcare

  • Multimodality genomics for translational purposes
  • Graphical molecular network analysis for identification of novel disease biology
  • Diagnosis and clinical care of patients with inherited cardiovascular disease
 
Precision Medicine
13:20

The Big data hype: A national strategy for next generation genome health research, case Finland

  • Is big data smoke and mirrors or does it really have a place in modern healthcare
  • Breaking from the conscious and understanding data sets that are beyond comprehension without big data.
  • Seeing the big data picture and treatment of diseases that have not been understood until the big data revolution in healthcare.
 
Artificial Intelligence
13:20

Big data on a network: Massive integration of domain knowledge to inform drug repurposing

  • Resources spent on drug development are exorbitant. In parallel, the probabilities of a lead compound making it to clinic are minuscule.
  • Developing a framework to integrate millions of experimental and clinical results in the form of a heterogeneous network, in which drugs, diseases, genes, etc are connected by mining a vast space of the entire domain knowledge.
  • Using Machine learning to compute the probability that any given drug would interfere with mechanisms of a disease of interest (as a proxy for a potential therapeutic)
 
 
Genomics and Health
13:40

10 Simple Rules for Sharing Human Genome Data

These 10 Simple Rules have been developed from our combined experiences with the Repositive platform, working with human genomic data, data repositories and data users. We do not claim that these rules will eliminate every possible risk of data misuse. Rather, we hope that these will help scientists to increase the reusability of their human genomic data, whilst also ensuring that the privacy of their subjects is maintained according to their consent frameworks. Many of the principles presented are also applicable to other types of clinical research data, where participant privacy is a concern.
 
Precision Medicine
13:40

Advancing discoveries in cardiovascular precision medicine through big data

  • AHA launches the Precision Medicine Platform
  • Partnership with Amazon Web Services
  • New approach to open data and tools and turn the attention to a community effort to accelerate solutions that positively impact the lives of those with cardiovascular disease and stroke.
 
Artificial Intelligence
13:40

Leveraging Wearables in Clinical Trials

  • Learn how sensors and wearables are helping Pharmaceutical organizations foster creative, quality clinical trials using sensors and other wearable devices.
  • Learn how mobile devices can assist in the tracking and reporting of accurate clinical data
  • Discuss how technologies are now improving the clinical trial process and reduce costs and improve accuracy of clinical data in an expeditious manner
 
 
Genomics and Health
14:00

Big data in the clinic – entering a new legal environment

  • Discussing the rapidly evolving legal and regulatory environment big data will encounter as it is integrated into clinical practice
  • Describing the potential legal landmines, and techniques to avoid them
  • Introducing risk management practices to minimize risk and maximize value
 
Precision Medicine
14:00

Novel sequencing-based assays as biomarkers of disease

  • Prediction of novel biomarkers using big data
  • Genomic technologies to identify the genetic etiology and underlying mechanisms of human disease in order to define precision therapies for diseased individuals
  • Predictive genomic signatures of response to therapy, and novel sequencing-based assays as biomarkers of disease
 
Artificial Intelligence
14:00

When small data = big data, or the magic of transfer learning.

  • Sharing and connecting deep learning algorithms algorithms to create conditions for a cross-fertilization between powerful artificial intelligence systems?
  • Transfer learning to foster collaborative AI
  • How to bring big-data-trained deep learning algorithms into the world of medical data
  • How collaborative AI can bring new business models to create value with data
 
 
Genomics and Health
14:20

Design and implementation of healthcare enterprise big data platforms

  • Developing and managing a comprehensive enterprise data strategy
  • Modern data governance strategies
  • Understanding the HPC landscape in healthcare and pharmaceutical development
 
Precision Medicine
14:20

Metagenomic next-generation sequencing for pathogen detection

  • Unbiased detection of pathogen nucleic acid from patient samples can be achieved through metagenomic next-generation sequencing (mNGS).
  • Broad-based organism detection requires new approaches to validation and results interpretation.
  • This talk will discuss the precision diagnosis of infectious disease for meningitis/encephalitis using mNGS.
 
Artificial Intelligence
14:20

Blockchain, AI and pharmaceutical development

The presentation will focus on where this potentially transformative platform for Pharmaceutical R&D could make the most direct benefit …to patients

  • How complexity could be simplified
  • Enabling trust
  • Allowing scale and security
 
 
14:40

Afternoon refreshments and exhibition viewing

 
 
Genomics and Health
15:20

Developing Inova’s IT infrastructure to support the collection, storage, visualization and distribution of genomic, clinical and laboratory data

  • How to get the most value of large datasets quickly.
  • Key infrastructure tools and lessons learned.
  • Talent and resources needed to support research data services and analytics
 
Precision Medicine
15:20

Discovering drivers of immune response to cancer discovered through 'big data' analysis

  • Mutations in cancer not only drive the growth of tumors (driver mutations), but also help tumors to control host immune system (immunity driver mutations)
  • TCGA data analysis yields over 100 genetic regions that affect the immune response to cancer.
  • This discovery opens new direction for cancer immunology research and understanding individual responses to cancer immunotherapy
 
Artificial Intelligence
15:20

AI assistance for data science via probabilistic programming

  • Demand for data science is rapidly growing. However, many commercial and scientific data sources present fundamental inferential challenges.
  • This talk will describe BayesDB, a probabilistic programming platform for AI-assisted data science that has been developed over the last 10 years.
  • Novice BayesDB users can answer data analysis questions in seconds or minutes with a level of rigor that otherwise requires hours or days of work by someone with advanced training in statistics plus good statistical judgment.
  • BayesDB also provides advanced probabilistic programming capabilities that enable experts to integrate causal domain knowledge and black-box machine learning with hierarchical Bayes.
  • Examples will be drawn from collaborations with philanthropic organizations such as the Bill & Melinda Gates Foundation
 
 
Genomics and Health
15:50

Combining genomic, structural, and clinical data to discover new insights in hypertrophic cardiomyopathy

  • We develop a new method to integrate structural features into tests of disease burden, especially in rare inherited diseases.
  • We use data from over 100,000 exomes and 2,900 rare disease patients to find structural regions of cardiac myosin enriched for mutations in disease patients.
  • We identify domains and surfaces of the myosin gene (MYH7) that are associated with clinical phenotypes and outcomes.
  • We demonstrate that combining data from different fields can identify novel correlations
 
Precision Medicine
15:50

Driving next generation diagnostics and precision medicine into the clinic

  • Translational aspects of targeted therapy and molecular diagnostics.
  • New software that will support next-generation sequencing panels to identify more targeted treatments for tumor types
  • Effective management of large volumes of genetic data through a scalable system
 
Artificial Intelligence
15:50

Deep Learning for Identification of Drug Targets in the Pharmacoepigenome of the Human CNS

  • Deep learning applications in pharmacogenomics
  • Computational methods for accurate prediction of CNS pharmacodynamic networks
  • Mapping human CNS pharmacodynamic networks in space and time based on the 4D Nucleome Project (NIH)
 
 
Genomics and Health
16:10

IT infrastructure to speed the delivery of Precision medicine into the clinic

  • Developing an efficient network architecture to empower research
  • New requirements for the big data era
  • Customized working environments
 
Precision Medicine
16:10

Genomics and cardiovascular clinical trials

  • Genomics for cardiovascular drug discovery
  • Genomic studies of clinical trials
  • Precision medicine of the CETP-inhibitor dalcetrapib
 
Artificial Intelligence
16:10

Predictive analytics for mortality risk estimation

  • Machine learning techniques for survival analysis
  • Joint modeling of longitudinal risk factors and survival data
  • Biomarker-based mortality risk scores
  • Statistical methodologies for studying longitudinal dynamics of aging
 
 
Genomics and Health
16:30

Genomics and Health: Transferring the power of HPC & NGS to the clinic

  • Moving research to the clinic when working with mental health disorders
  • The delicate balance of data sharing, discovery, and translation to the clinic
  • Closing the loop- the transition back to focusing on the patient.
  • Case studies of big data projects at a children’s hospital
 
Precision Medicine
16:30

Finding a needle in a haystack: new approaches to discover disease-causing mutations in patients’ genomes

  • Prioritizing disease-causing candidate genes and mutations.
  • Detecting genotypic heterogeneity underlying phenotypic homogeneity.
  • Filtering out Next Generation Sequencing false positives noise.
 
Artificial Intelligence
16:30

Automated Genome-Based Prediction tool for Pathogens for the prediction of complex virulence and antibiotic resistance phenotypes using high throughput sequencing data

  • Detection of antibiotic resistance phenotypes using high throughput sequencing data.
  • Machine learning algorithms to determine the diverse features (change in virulence genes, recombination, horizontal gene transfer, patient diagnostics).
  • Pathogenic Potential and Countermeasures Targets
 
 
Genomics and Health
16:50

Cannabis Strains and regulation

  • Understanding the current issues with regulation in cannabis
  • Producing and monitoring cannabis using databases and block chain
  • Big Data and Cannabis
Kevin McKernan, Chief Scientific Officer, Courtagen Life Sciences/Medicinal Genomics, Courtagen Life Sciences Inc
 
 

 

End of conference