BioData EU 2018 Agenda

 

 

Basel, 28 - 29 November 2018

Schedule

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Nov 2809:00
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Keynote opening address

Keynotes
Abel Archundia, Head of IT Bayer Pharma, Bayer
Nov 2809:40
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AI- the future of medicine

Keynotes
Bertrand Bodson, Chief Digital Officer, Novartis
Nov 2810:00
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How the NHS plans to implement precision medicine using AI

Keynotes
Nov 2811:40
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Round Tables

Keynotes
Round Table A: Biomarker discovery in the world of AI
Enrico Ferrero, Translational Bioinformatics Team Leader, GSK
Michael Scharfe, Data Architect, Novartis Institutes for Biomedical Research
Roberto Iacone, VP/CSO, Bright Peak
Suleiman Khan, Senior Reseracher, University of Helsinki
Round Table B: Using Electronic Medical Record (EMR) data to inform big pharma’s drug discovery, development, and marketing processes
Nicholas Kelley, Research Investigator, Genomics, Novartis Institutes
Round Table C: NTTDATA
Round Table D: Data Management and Democratisation
Torsten Schwede, Director of Data Coordination Centre of the Swiss Personalized Health Network, Swiss Institute of Bioinformatics
Olivier Roche, Global Data Quality Coordinator, Biology workflow team leader, Roche
Moritz Gilsdorf, Senior Scientific Software Engineer, Roche
Round Table E: Western Digital
Round Table F: Accelerating Innovation in Pharmaceuticals
Hamish Graham, Pfizer Healthcare Hub: London MD, Pfizer Ltd
Kate Merton, Head, JLABS NYC & Boston, Johnson & Johnson
Round Table G: Navigating Real World Data & Applied Analytics
Gabriel Eichler, Data & Analytics Workstream Lead - Kraft Precision Medicine Accelerator, Harvard Business School
Round Table H: Sequencing and collaboration
David Lloyd, Project Technical Coordinator, ELIXIR
Jan Nygaard Jensen, Scientific Director, Head of Bioinformatics Discovery, Novo Nordisk
Andrew Lowe, Senior Scientist, Novo Nordisk
Enrique Toledo, Senior Scientist, Novo Nordisk
Lena Hansson, Principal Scientist, Novo Nordisk
Round Table I: Using digital technologies in clinical trials
Atar Libovitch, Head of Business Solutions, Teva Pharmaceuticals Industries Ltd
Florian Hahne, Expert data integration and knowledge management, Novartis Pharma AG
Dirk Voelkel, Chief Technology Officer – Innovation and Analytics, G.E. Healthcare
Round Table J: Using RWD across borders
Eunice Jung, Associate Director of Value Based Medicine, Biogen
Round Table K: Examining developments on data privacy
Maria Chiara Atzori, Head Data Privacy Switzerland, Novartis
Nicola Orlandi, Head Data Privacy Pharma, Novartis
Round Table L: Emerging Investment Thesis – Engaging results from large scale investmen
Marc Sluijs, Advisor, Global Health Innovation Fund, Merck
Round Table M: Topic TBC
Jennifer Cham, Lead User Experience Designer, EMBL-EBI
Round Table N: Translational Oncology Informatics
Ronghua Chen, Head of Informatics Asia Pacific and Merck R&D China IT, MSD
Round Table O: Examining device-based data capture and analytics
Steffen Roellinger, SVP - Head Portfolio & Operations, Pharma R&D, Bayer
Round Table P: Blockchain and Health
Lars Greiffenberg, Director Information Research, Library Sciences and Academic Partnerships, Abbvie Germany
Round Table Q: Artificial Intelligence and Deep Learning in Healthcare and Life Sciences
Round Table R: Mark Logic
Round Table T: Sharing clinical data
Round Table U: TBC
James Thomas, Chief Technology Officer, Wellcome Trust
Round Table V: The Splicasome
Round Table W: Data Science at J&J
Joseph Lehar, VP Data Science, Oncology, J&J, Janssen Pharmaceuticals
Round Table X: Challenges affecting the Implementation of E-Health at Ministry of Health in Gambia
Musa Suso, Information, Communication Officer, Ministry Of Health & Social Welfare
Round Table Y: Title to be confirmed
Philip Nelson, Director, Software Engineering, Google Inc
Round Table Z: Data standards, ontologies and controlled vocabularies
Peter Groenen, Head Of Translational Science, Idorsia
Round Table ZA: Using signal tower methodology
Cassie Gregson, Principal Informatics Scientist, AstraZeneca
Round Table ZB: Developing data/analysis commons in translational medicine
Nov 2813:30
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Chairs Opening Remarks

Track 1- IT, DATA MANAGEMENT AND STORAGE
Jasmin Saric, Head of Digital Ideation and Scouting, BI X GmbH
Nov 2813:30
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Chairs Opening Remarks

Track 2- BIOINFORMATICS & GENOMIC TOOLS
Nov 2813:30
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Chairs Opening Remarks

Track 3- AI, AUTOMATION AND MACHINE LEARNING
Paul Strijbos, Digital Innovation Leader, F. Hoffmann-La Roche
Nov 2813:30
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Nov 2813:30
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Chairs Opening Remarks

Track 5- DATA INTEGRATION & INFRASTRUCTURE/ BIG DATA IN RARE DISEASES
Nov 2813:35
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How to make data accessible?

Track 1- IT, DATA MANAGEMENT AND STORAGE
  • Pooling of internal and external data sources for clinical development
  • Overview on business use cases at Novartis, and underlying technology platform(s)
  • Critical enablers of the journey (e.g. agile governance, partner ecosystem, rapid data prototyping)
Achim Plueckebaum, Global Head Development IT, Novartis
Nov 2813:35
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The genetics of drug efficacy: opportunities and challenges

Track 2- BIOINFORMATICS & GENOMIC TOOLS
Matt Nelson, Head, Genetics, GSK
Nov 2813:35
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Ensemble Computational Intelligence Reveals Novel Molecular Signatures of Cancer Biology and Pan-Cancer Survival

Track 3- AI, AUTOMATION AND MACHINE LEARNING
  • Novel feature learning approaches that enhance quantitative assessment of annotated tissues from The Cancer Genome Atlas.
  • We demonstrate the utility of collapsing molecular signals, from five different -omics platforms, into integrated metagenes that are highly informative across roughly 8,200 tumors, encompassing 22 cancer types.
  • Our a priori biological-knowledge and data-driven network-based approaches improve performance and interpretability of both deep learning and probabilistic programming strategies, revealing novel network-driver genes underlying cancer type specific etiology and pan-cancer patient survival.
Nov 2813:35
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Getting meaning from Data: reading through the data

Track 4- BIG DATA IN ONCOLOGY
Nov 2813:35
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From data archiving to knowledge representation: Research infrastructure provision at EBI

Track 5- DATA INTEGRATION & INFRASTRUCTURE/ BIG DATA IN RARE DISEASES
Nov 2813:55
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Optimizing Big Data Workloads to Accelerate Drug Development

Track 1- IT, DATA MANAGEMENT AND STORAGE
  • Pharmaceutical companies are saddled with legacy systems containing heterogeneous and disparate data. Increasing the ability to share data requires rationalizing and connecting these systems.
  • IT-enabled portfolio management allows data-driven decisions to be made quickly and seamlessly.
  • Responsive, agile, and flexible platform that can leverage a cloud based approach
Nov 2813:55
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Techniques from Small Molecule Discovery

Track 2- BIOINFORMATICS & GENOMIC TOOLS
  • Data diversity, volume and complexity represent challenges for biologics drug discovery
  • Small molecule discovery utilizes advanced analytical techniques such as QSAR, matched-molecular pairs, etc., to predict relationships between structure and activity
  • This talk will discuss adaptation of these techniques to biologics discovery, highlighting successes and potential pitfalls
Nov 2813:55
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Using AI to support generation of RWE

Track 3- AI, AUTOMATION AND MACHINE LEARNING
Nov 2813:55
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Large-scale biomedical data integration using the IndivuType database

Track 4- BIG DATA IN ONCOLOGY
  • IndivuType is a large-scale multi-OMICS data resource based on specimens obtained from a world-wide network of clinical partner sites.
  • All specimens and data are processed according to global standard operating procedures and annotated with high-quality clinical data.
  • A powerful analysis toolbox makes the data accessible for drug target and biomarker discovery, study cohort design as well as basic and health care research.
Nov 2814:15
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Be Data Ready: the story of Sanofi’s translational data governance

Track 1- IT, DATA MANAGEMENT AND STORAGE
  • What is data governance ?
  • Understanding your data ecosystem: key drivers and enablers
  • The ‘How to’ implementation challenge: a mix of top-down and bottom-up approaches
  • Future vision and perspectives
Lucie Eckenberg-Friedlander, Translational data governance team leader, Sanofi
Nov 2814:15
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Developments Computational medicine

Track 2- BIOINFORMATICS & GENOMIC TOOLS
Shameer Khader, Program Director (Healthcare Data Science and Bioinformatics), Northwell Health
Nov 2814:15
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Title to be confirmed

Track 3- AI, AUTOMATION AND MACHINE LEARNING
Nov 2814:15
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Title to be confirmed

Track 4- BIG DATA IN ONCOLOGY
Eike Staub, Head of Oncology Bioinformatics, Merck Group
Nov 2814:15
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Liberating evidence from real world data in the 21st Century: what have we learned from IMI EMIF, and where will IMI EHDEN take us?

Track 5- DATA INTEGRATION & INFRASTRUCTURE/ BIG DATA IN RARE DISEASES
  • Insights from the IMI European Medical Information Framework project 2013-2018
  • What is proposed for the IMI European Health Data and Evidence Network 2018-2023
  • Building sustainable infrastructure via federated networks, common data models and data ecosystems
Nov 2815:15
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Chairs Opening Remarks

Track 1- IT, DATA MANAGEMENT AND STORAGE
Nov 2815:15
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Chairs Opening Remarks

Track 3- AI, AUTOMATION AND MACHINE LEARNING
Steve Guise, CIO Roche - Pharmaceuticals Division, Roche
Nov 2815:15
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Chairs Opening Remarks

Track 5- DATA INTEGRATION & INFRASTRUCTURE/ BIG DATA IN RARE DISEASES
Derek Marren, Director Of Research IT, Biology Systems And Data Integration, Eli Lilly And Company
Nov 2815:20
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Best practices to developing genomic data lakes: Experiences from the Mayo Clinic

Track 1- IT, DATA MANAGEMENT AND STORAGE
Steven Hart, Associate Director of Bioinformatics, Clinical Genome Sequencing Laboratory (CGSL), Mayo Clinic
Nov 2815:20
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The use of RWD and machine learning in reverse translation

Track 2- BIOINFORMATICS & GENOMIC TOOLS
  • Reverse translation is gaining more importance in drug discovery to support application of human data for target-indication prioritization and patient selection
  • Real world data can provide additional source of information to help selecting the right target for the right indication
  • Machine learning applied to real world data can provide enhanced characterization of diseases and patient trajectories supporting more robust reverse translation
Sàndor Szalma, Senior Director, Biomedical Informatics, Takeda
Nov 2815:20
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Chairs Opening RemarksReal-world data integration: a Roche story

Track 3- AI, AUTOMATION AND MACHINE LEARNING
Etzard Stolte, Global Head of Knowledge Management PTD, Roche
Nov 2815:20
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Nov 2815:20
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Towards FAIR data: ELIXIR

Track 5- DATA INTEGRATION & INFRASTRUCTURE/ BIG DATA IN RARE DISEASES
Nov 2815:40
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Industrial internet platforms and applications for life sciences

Track 1- IT, DATA MANAGEMENT AND STORAGE
Dirk Voelkel, Chief Technology Officer – Innovation and Analytics, G.E. Healthcare
Nov 2815:40
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Role of AI in bioinformatics and Drug Discovery

Track 2- BIOINFORMATICS & GENOMIC TOOLS
  • Is AI/ML transforming bioinformatics?
  • Do we have the right data?
  • Examples of using Advanced Analytics
Philippe Sanseau, Head Computational Biology and Stats, GSK
Nov 2815:40
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The role of automation in clinical operations

Track 3- AI, AUTOMATION AND MACHINE LEARNING
Joachim Luithle, Vice President and Head of Clinical Development Operations, Bayer
Nov 2815:40
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A look at the HARMONY Alliance: the role of big data for hematology

Track 4- BIG DATA IN ONCOLOGY
Michel Van Speybroeck, Director of Data Sciences, Janssen (J&J)
Nov 2815:40
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Developing the AZ Data Architecture

Track 5- DATA INTEGRATION & INFRASTRUCTURE/ BIG DATA IN RARE DISEASES
Justin Lecher, Scientific Computing/HPC Architect, AstraZeneca
Nov 2816:00
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Managing genomic, medical and clinical trial data with integrated solutions to support analytics and machine learning

Track 3- AI, AUTOMATION AND MACHINE LEARNING
Rebecca Laborde, Lead Product Strategist for Healthcare and Master Principal Scientist for Precision Medicine at Oracle Healthcare, Oracle Health Sciences
Nov 2816:20
Conference pass

Cross Pharma HPC Collaboration to Improve Pharma Research and Scientific Outcomes

Track 1- IT, DATA MANAGEMENT AND STORAGE
  • A decade of successful pre-competitive xPharma HPC collaboration http://www.hpcxpharma.org/
  • Classic HPC platforms for R&D
  • Future-ready data and HPC platforms for clinical and commercial Big Data Mining
Nov 2816:20
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Driving value into immunotherapy through AI based response prediction

Track 2- BIOINFORMATICS & GENOMIC TOOLS
Olivier Elemento, Director, Laboratory of Cancer Systems Biology, Englander Institute for Precision Medicine Institute for Computational Biomed, Weill Cornell Medicine
Nov 2816:20
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The Benefits of Bayesian AI

Track 3- AI, AUTOMATION AND MACHINE LEARNING
  • Real-world AI systems need to account for uncertainty and reason probabilistically
  • Bayesian methods provide a principled approach to dealing with uncertainty
  • Recent developments in this area will be discussed
Stanley Lazic, Associate Director, Statistics & Machine Learning, AstraZeneca
Nov 2816:20
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DataBox Project- How to empower patients with their own data and adhere to GDPR

Track 4- BIG DATA IN ONCOLOGY
Christof Von Kalle, Professor Division of Translational Oncology, N.C.T. and D.K.F.Z.
Nov 2816:20
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DataBox Project- How to empower patients with their own data and adhere to GDPR

Track 4- BIG DATA IN ONCOLOGY
Christof Von Kalle, Professor Division of Translational Oncology, N.C.T. and D.K.F.Z.
Nov 2816:20
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Six simple steps to achieve data integration

Track 5- DATA INTEGRATION & INFRASTRUCTURE/ BIG DATA IN RARE DISEASES
Alexander Krupp, Head of Computational Life Science IT Pharmaceuticals, Bayer
Nov 2817:05
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Integrating health into your digital life

Track 1- IT, DATA MANAGEMENT AND STORAGE
  • As Healthcare providers, we need to recognize that people who use our services already have a footprint in the digital world, with services, devices and applications which they are comfortable using. Instituting change in this is likely to lead to disengaged users, with fewer beneficial outcomes.
  • The last 20 years have brought with them a tremendous pace of innovation in many industries, and created whole new industries through technology itself. In many cases, these changes have instilled behavior shifts and expectations in users - it is important as healthcare revolutionizes itself to learn from these, to not reinvent the wheel, and accelerate our movement by exploiting benefits and opportunities from other industries.
  • Obtaining meaningful insight on patients is based on a simple reward/effort ratio. In order to minimize the effort of data collection, this must be seamless, transparent and simple from the person’s perspective – integrating with passive monitoring systems and zero-UI systems make data collection easy, while the value of providing actionable, timely and relevant insight to a patient will keep them engaged with the platform and feel like it provides them with value.
David Whewell, Director of Architecture and Software Innovation, Merck
Nov 2817:05
Conference pass

Insights from MedImmune: Tertiary analysis of genomics data

Track 2- BIOINFORMATICS & GENOMIC TOOLS
  • Developing a cohort explorer for comparison of genotype and phenotype
  • Overview of Astrazeneca/MedImmune strategy for using genomics in drug discovery
  • Partnership with DNAnexus
David Fenstermacher, VP, R&D Bioinformatics, MedImmune Inc
Nov 2817:05
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How digital technologies enable precision medicine

Track 3- AI, AUTOMATION AND MACHINE LEARNING
Martin Erkens, Head of pRED Informatics, Roche Diagnostics
Nov 2817:05
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The digital Clinical Trial – potential future hybrid trial models

Track 4- BIG DATA IN ONCOLOGY
  • Digital Clinical Trial Models
  • Current digitalECMT work
  • Examples of a range of trail types
Donal Landers, Senior Director of Physician, AstraZeneca
Nov 2817:05
Conference pass

Predictive modeling for rare diseases

Track 5- DATA INTEGRATION & INFRASTRUCTURE/ BIG DATA IN RARE DISEASES
Mathew Pletcher, Head of Rare Disease Discovery, Roche
Nov 2817:25
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Simplifying data analysis and management for life science workflows

Track 1- IT, DATA MANAGEMENT AND STORAGE
Vast amounts of data are the ingredients for Deep Learning and Genomics. Managing, accessing and analyzing this data which typically goes into the Petabytes can be a challenge. This presentation explains DellEMC’s solution for Life Sciences that includes all the necessary components out of one hand. It is not only easily deployed and managed in a data center but allows bio scientists to focus on their work without being IT experts.
Nov 2817:25
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Enabling multidimensional translational data management and analysis for biomarkers discovery and patients stratification

Track 4- BIG DATA IN ONCOLOGY
  • in translational medicine, predictive and prognostic quantitative biomarkers have been growing in size, complexity and diversity
  • translational scientists need to be empowered to explore and analyze complex translational datasets
  • PerkinElmer Signals™ Translational empowers domain experts through Spotfire, a rich visual environment, connected to the Cloud
Nov 2817:25
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Seeding Discovery for Rare Disease Therapeutic Development through Epilepsy

Track 5- DATA INTEGRATION & INFRASTRUCTURE/ BIG DATA IN RARE DISEASES
  • Only 5% of Rare Diseases have therapies due in part to the lack of understanding rare disease biology
  • DNA sequencing of Epilepsy patients can aid in treatment clinical decision support and identify new causal genes, gene variants and gene-gene interactions
  • Creation of Deep, Rich, Standardized Genotype to Phenotype Global Data Sets to determine functional biology contributing to epilepsy and the rare diseases represented can result in identification of new molecular targets and seed novel therapeutic development programs within and across rare diseases of similar biology
Nov 2817:45
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Ensuring patient centricity within the digital world

Track 1- IT, DATA MANAGEMENT AND STORAGE
  • Keeping data focussed on unmet patient need.
  • Using digital channels to engage HCPs
  • Gathering patient insights for strategic decisions
Tim Cave, VP-Head Strategic Planning and Digital Practices, Global Medical Affairs, GSK
Nov 2817:45
Conference pass

Bioinformatics as a Service: A National Resource to Support Biomedical Research in Qatar

Track 2- BIOINFORMATICS & GENOMIC TOOLS
Mohamed-Ramzi Temanni, Technical Manager - Bioinformatics, Sidra Medicine
Nov 2817:45
Conference pass

Lab Data Automation - establishing an automation layer for transferring and exchanging lab data

Track 3- AI, AUTOMATION AND MACHINE LEARNING
Ralph Haffner, Head of Research Informatics, Roche
Nov 2817:45
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Harnessing the Complexity of Cancer

Track 4- BIG DATA IN ONCOLOGY
Nov 2817:45
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Decentralised, Disruptive Digital trials- Utilizing next generation phenotypic sensors

Track 5- DATA INTEGRATION & INFRASTRUCTURE/ BIG DATA IN RARE DISEASES
Michelle Krishnan, Translational Medicine Leader in Rare Diseases, Roche
Nov 2818:05
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Bioinformatics as a Service: A National Resource to Support Biomedical Research in QatarMassively parallel single-cell CRISPR sequencing in organoid models

Track 2- BIOINFORMATICS & GENOMIC TOOLS
  • Genetic epidemiology and CRISPR screens both still struggle to make highly predictive comments about drug target modifiers (i.e. precision medicine) .
  • Using liver organoid models, while integrating single-cell sequencing with CRISPR, we are dissecting out the cross-talk between metabolic pathways to understand target interactions.
  • The pipeline and novel methods underlying such genetic screens and the types of results bing generated will be presented.
Nov 2818:05
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Exploring the Depths: A New Era of Screening Assays Using Deep Learning

Track 3- AI, AUTOMATION AND MACHINE LEARNING
Nov 2818:05
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Computational approaches to I/O in drug development at AstraZeneca

Track 4- BIG DATA IN ONCOLOGY
Ben Sidders, UK Team Leader of Oncology Bioinformatics, AstraZeneca
Nov 2818:05
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The rare Disease play book- Developing an Orphan Disease Knowlage Base at Alexion

Track 5- DATA INTEGRATION & INFRASTRUCTURE/ BIG DATA IN RARE DISEASES
Sebastien Lefebvre, Senior Director Data Analytics & Decision Support, Alexion Pharmaceuticals
John Reynders, Vice President, R&D Strategy, Program Management and Data Sciences, Alexion Pharmaceuticals

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Nov 2909:00
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Transforming R&D productivity: How can we better turn science into medicine?

Keynotes
  • The future treatment for many of today’s diseases lies in discovering new biology to develop novel therapies. The advent of the genomics revolution brings with it an expanding list of pathways and targets to pursue – and with it, new drug discovery challenges
  • Validating drug targets by understanding and challenging scientific hypotheses has never been more important
  • Combining new technologies, focusing on medical understanding, challenging scientific hypotheses and driving strategic partnerships, we are making real progress in our ability to define and prosecute innovative treatment approaches for a variety of complex diseases
Nov 2909:40
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New plans for the digital architecture across the NHS

Keynotes
Indra Joshi, Digital Health and AI Clinical Lead, NHS England
Harpreet Sood, Associate Chief Clinical Information Officer, NHS England
Nov 2911:00
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Chairs Opening Remarks

Track 6- ANALYTICS PLATFORMS AND DATA SETS/ CLOUD PLATFORMS/ SOFTWARE & APPLICATIONS
Nov 2911:00
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Chairs Opening Remarks

Track 8- DATA MANAGEMENT AND GENOMICS IN CLINICAL TRIALS
Nov 2911:00
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Chairs Opening Remarks

Track 5- AI, AUTOMATION AND MACHINE LEARNING
Florian Lipsmeier, Principal Data Scientist; pRED Informatics, Roche
Nov 2911:05
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Using analytics tools to leverage data

Track 6- ANALYTICS PLATFORMS AND DATA SETS/ CLOUD PLATFORMS/ SOFTWARE & APPLICATIONS
Mark Baillie, Associate Director, Statistical methodology and consulting, Novartis
Nov 2911:05
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Lab of the future: automated and autonomous lab

Track 7- NEXT GEN SEQUENCING / REAL WORLD EVIDENCE
Darryl Davis, Head of Biophysical Research & Analytics, Janssen
Nov 2911:05
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Leveraging Genetics, Genomics and Proteomics for Translational Research

Track 8- DATA MANAGEMENT AND GENOMICS IN CLINICAL TRIALS
Philippe Marc, Global Head of Integrated Data Sciences, Novartis Institutes for Biomedical Research
Nov 2911:05
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Machine learning models for ADME optimisation

Track 5- AI, AUTOMATION AND MACHINE LEARNING
Nov 2911:25
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GENALICE

Track 7- NEXT GEN SEQUENCING / REAL WORLD EVIDENCE
Bas Tolhuis, Function Manager Bioinformatics, GENALICE
Nov 2911:25
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Predicting clinical trial success with Artificial Intelligence

Track 5- AI, AUTOMATION AND MACHINE LEARNING
Nov 2911:45
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Machine Learning meets the Human Genome

Track 6- ANALYTICS PLATFORMS AND DATA SETS/ CLOUD PLATFORMS/ SOFTWARE & APPLICATIONS
Slave Petrovski, Vice-president and Head of Genome Analytics, AstraZeneca
Nov 2911:45
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A comprehensive analysis of a RNA-seq dataset at the gene-, isoform- and exon-levels to discover disease progressive biomarkers during diabetic nephropathy

Track 7- NEXT GEN SEQUENCING / REAL WORLD EVIDENCE
  • Introduction to ZSF1, a preclinical model for type 2 diabetic nephropathy
  • Why RNA-seq data should be additionally analyzed at the isoform and exon levels
Shanrong Zhao, Director, Computational Biology and Bioinformatics,Worldwide R&D, Pfizer
Nov 2911:45
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Use case: Federated EHR research technology to support clinical trial protocol optimisation: Evidence from EHR4CR and the InSite platform

Track 8- DATA MANAGEMENT AND GENOMICS IN CLINICAL TRIALS
  • The new federated EHR technology approach – the case of EHR4CR project and deployment program inEurope
  • Utilise a combination of data sources to effectively structure your developmental strategy
  • Outlook on performing Pragmatic Clinical Trials & Conclusions
Mats Sundgren, Director, Health Informatics, AstraZeneca
Nov 2911:45
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Presentation

Track 5- AI, AUTOMATION AND MACHINE LEARNING
Tom Rush, ATOM Chief Scientific Officer & Interim Co-Lead, Senior Director and Head of Biology Automation, GSK
Nov 2912:05
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Round Tables

Keynotes
Round Table A: AI for Drug Discovery - Investment Landscape
Dmitry Kaminskiy, Co-founder, Senior Partner, Deep Knowledge Ventures
Round Table B: Patient advocacy within clinical trials
Mimi Choon-Quinones, Former Vice-Director, Clinical Operations EEMEA, Roche
Round Table C: GDPR
Alix Leboucq Zollinger, Genomics Data Analyst, Nestle Institute of Health Sciences
Jerome Carayol, Data Analyst, Nestle Institute of Health Sciences
Greg Lefebvre, Genomic Data Science Team Lead, Nestle Institute of Health Sciences
Round Table D: Analytics for Regulatory and Safety RWE and Epidemiology
Round Table E: Digital Endopoints and Validation
Ieuan Clay, Group Lead Digital Endpoints, Novartis
John Batchelor, Senior Outcomes Measurement Scientist, Roche
Round Table F: AI in Ageing Research and Longevity
Kristen Fortney, Chief Executive Officer, Bioage Labs
Tina Woods, Founder, Collider Health
Round Table G: ONTOFORCE
Round Table H: Diagnostics & Data
Sebastien Lefebvre, Senior Director Data Analytics & Decision Support, Alexion Pharmaceuticals
Round Table I: Human Protein Atlas: Big data for human biology and precision medicine
Cecilia Lindskog, Director Tissue Atlas, Human Protein Atlas, Uppsala University
Round Table J: Databiology
Round Table K: Digital Substudies- Big Data in Drug Discovery
Lena Granovsky, Director, Analytics and Big Data, Teva Pharmaceuticals
Round Table L: Applied Health Science Research to Improve Clinical Outcomes
Round Table M: Decentralized Trial Settings
Scott Askin, Digital Solutions Director, Digital Development, Portfolio, Strategy & Innovation (PS&I), Novartis Pharma
Round Table N: Empowering the Person in a Health System: Evidence for Effectiveness
Indra Joshi, Digital Health and AI Clinical Lead, NHS England
Round Table O: Datalake architecture for R&D
David Ficenec, Global Head of Architecture, R and D Information Systems and Information Technology, Takeda Pharmaceuticals U.S.A. Inc
Round Table P: Developing data sharing across the Wellcome Trust
Nicola Perrin, Head, Data for Science and Health priority, Wellcome Trust
Round Table Q: Using AI in Drug Development
Edward Painter, Founder & CEI, A2A Pharmaceuticsls
Round Table R: Computing at the Exascale – Developing large scale genomics and heath record architecture
Jeremy Cohen, Senior Program Manager, Oak Ridge National Laboratory
Edmon Begoli, Chief Data Architect, Oak Ridge National Laboratory
Round Table S: Title to be confirmed
Audrey Kauffmann, Oncology Bioinformatics Site Head, Novartis
Round Table T: Securing budget for organising data so its findable and usable
Round Table V: Everything you need to know about the Spliceosome
Round Table W: Digital Healthcare: When is healthcare going to be digitalised
Jasmin Saric, Head of Digital Ideation and Scouting, BI X GmbH
Round Table X: Challenges in Data Curation and Quality
Nov 2914:05
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Chairs Opening Remarks

Track 6- ANALYTICS PLATFORMS AND DATA SETS/ CLOUD PLATFORMS/ SOFTWARE & APPLICATIONS
Nov 2914:05
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Chairs Opening Remarks

Track 8- DATA MANAGEMENT AND GENOMICS IN CLINICAL TRIALS
Mimi Choon-Quinones, Former Vice-Director, Clinical Operations EEMEA, Roche
Nov 2914:05
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Chairs Opening Remarks

Track 5- AI, AUTOMATION AND MACHINE LEARNING
Lena Granovsky, Director, Analytics and Big Data, Teva Pharmaceuticals
Nov 2914:10
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Applied Technology and Innovation

Track 6- ANALYTICS PLATFORMS AND DATA SETS/ CLOUD PLATFORMS/ SOFTWARE & APPLICATIONS
Ian Pepper, CTO, Head Strategy and Integration Architecture, Novartis
Nov 2914:10
Conference pass

Different whole genome sequencing strategies to study HPVs role in cancer development.

Track 7- NEXT GEN SEQUENCING / REAL WORLD EVIDENCE
  • How HPV is involved in the development of different cancers
  • Strengths and weaknesses of different whole genome sequencing strategies to study HPV integrations in cancer
  • Time vs Money where should you invest?
David Smith, Professor, Mayo Clinic
Nov 2914:10
Conference pass

Application of ML to lupus nephritis and extrarenal lupus clinical dataset - lesson learned and main takeaways

Track 8- DATA MANAGEMENT AND GENOMICS IN CLINICAL TRIALS
  • We adapted Eureqa software (Nutonian) to screen baseline and time-varying clinical and laboratory parameters for associations with outcome using pooled data from recent trials in lupus nephritis (LN) and extrarenal lupus (ERL)
  • In LN, Eureqa confirmed known associations with outcome but also several trivial associations. Eureqa did not identify meaningful associations between clinical variables and outcome in ERL trials
  • Eureqa is a potentially exciting tool to assist with discovery of novel associations in clinical data and hypothesis generation
Marco Prunotto, Senior Clinical Development Scientist, F. Hoffmann-La Roche AG
Nov 2914:10
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The Swiss personalised healthcare network

Track 9- ROCHE CURATED SESSIONS/ PRECISION MEDICINE
Torsten Schwede, Professor For Bioinformatics, Sib Swiss Institute Of Bioinformatics & University Of Basel
Nov 2914:10
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Empowering the person: Evidence for Effectiveness

Track 5- AI, AUTOMATION AND MACHINE LEARNING
Indra Joshi, Digital Health and AI Clinical Lead, NHS England
Nov 2914:30
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Using AI for drug target discovery

Track 7- NEXT GEN SEQUENCING / REAL WORLD EVIDENCE
  • Case studies over the last five years
  • Precision Medicine based clinical trials
  • RWE in practice
Nov 2914:50
Conference pass

Decision making platforms and data quality at pRED

Track 6- ANALYTICS PLATFORMS AND DATA SETS/ CLOUD PLATFORMS/ SOFTWARE & APPLICATIONS
Jorg Degen, Project Leader, Pharma Research and Early Development Informatics, Roche Diagnostics International
Nov 2914:50
Conference pass

Omics and pathway analysis for disease understanding in pain

Track 7- NEXT GEN SEQUENCING / REAL WORLD EVIDENCE
  • Pain as a disease
  • Interpretation of Omics data and Pathways
  • Pain Landscapes and Disease Understanding
Nov 2914:50
Conference pass

Surfing the Tsunami Opportunities and Challenges of Digital in Clinical at Abbvie

Track 8- DATA MANAGEMENT AND GENOMICS IN CLINICAL TRIALS
Nov 2914:50
Conference pass

Precision and recall oncology: combining multiple gene alterations for improved identification of drug-sensitive tumours

Track 9- ROCHE CURATED SESSIONS/ PRECISION MEDICINE
  • A small proportion of tumours present strong gene-drug response associations that can be used as predictive biomarkers of drug response.
  • Combining multiple gene alterations of the tumours via Machine Learning (ML) often results in better discrimination than that provided by the corresponding single-gene marker.
  • ML multi-gene predictors generally retrieve a much higher proportion of treatment-sensitive tumours (i.e. they have a higher recall). This suggests that substantially more patients could eventually benefit from effective drug selection by applying this ML methodology to existing clinical pharmacogenomics data sets
Pedro Ballester, Group Leader, INSERM
Nov 2914:50
Conference pass

Exabyte computing: How the world’s most powerful supercomputer is being put to use in life sciences

Track 5- AI, AUTOMATION AND MACHINE LEARNING
Edmon Begoli, Chief Data Architect, Oak Ridge National Laboratory
Nov 2915:40
Conference pass

Achieving an integrated approach to software and applications

Track 6- ANALYTICS PLATFORMS AND DATA SETS/ CLOUD PLATFORMS/ SOFTWARE & APPLICATIONS
Jan Kuentzer, Head of Data Science Application Services, Roche Pharmaceutical Research and Early Development, Roche Innovation Center Munich
Nov 2915:40
Conference pass

RWE at Novartis- Changing the value proposition

Track 7- NEXT GEN SEQUENCING / REAL WORLD EVIDENCE
Nov 2915:40
Conference pass

Modeling and simulation for clinical sciences in the cloud under GxP

Track 8- DATA MANAGEMENT AND GENOMICS IN CLINICAL TRIALS
Jobst Loeffler, It Project Manager For Research & Development, Bayer Corp
Nov 2915:40
Conference pass

The Genomics of Rare Diseases at Boston Children’s Hospital

Track 9- ROCHE CURATED SESSIONS/ PRECISION MEDICINE
  • The importance of phenotyping, transparency, and patient engagement
  • The delicate balance of data sharing, discovery, and translation to the clinic
  • Case studies of big data projects at a tertiary children’s hospital
  • Collaborations with Industry to make rare disease discoveries
Nov 2915:40
Conference pass

Federated learning: leveraging the power of private data

Track 5- AI, AUTOMATION AND MACHINE LEARNING
  • Federated learning approach allows to build powerfull models from separated datasets
  • This techniques enables to build efficients models without compromising the privacy of individual datasets
  • Examples of applications in medicine
Mikhail Zaslavskiy, Chief Research Officer, Owkin
Nov 2916:00
Conference pass

Predicting Cardiac Drug Toxicity through AI- Chemotherapy vs Cardiac toxicity

Track 9- ROCHE CURATED SESSIONS/ PRECISION MEDICINE
Polina Mamoshina, Sr Research Scientist, Insilico Medicine, Inc
Nov 2916:00
Conference pass

NURITAS

Track 5- AI, AUTOMATION AND MACHINE LEARNING
Nov 2916:20
Conference pass

How to Infuse the Human Perspective to Digital Health?"

Track 6- ANALYTICS PLATFORMS AND DATA SETS/ CLOUD PLATFORMS/ SOFTWARE & APPLICATIONS
  • Most paradigms of the digital health revolution, such as digital therapeutics, precision medicine, outcome-based health systems, and self-care are critically dependent on changing behavioural aspects of patients
  • Impactful digital health initiatives are therefore best co-developed with patients in a human-centric manner
  • Patients can participate in product and service development at scale through a novel service platform for patient engagement, specifically trained resources, and a network of relevant partners
Oliver Gassner, Head Digital Health Intelligence | EMEA, Bayer
Nov 2916:20
Conference pass

Accelerating Advances in Cancer Therapy through RWD

Track 7- NEXT GEN SEQUENCING / REAL WORLD EVIDENCE
Nov 2916:20
Conference pass

Putting data to work in drug discovery - building an AI-enhanced future

Track 8- DATA MANAGEMENT AND GENOMICS IN CLINICAL TRIALS
Data, information and knowledge management is a critical foundation for building an AI-enhanced future for drug discovery. I will show examples of our work, and in particular discuss how technology interfaces with culture in this area”
Ian Barrett, Associate Director - Quantitative Biology, AstraZeneca
Nov 2916:20
Conference pass

Scaling up trustworthy data access for personalised care and research

Track 9- ROCHE CURATED SESSIONS/ PRECISION MEDICINE
  • Real World Evidence decision making and Precision Medicine need greater access to big health data: clinical data, genomic biomarkers, wellness and lifestyle.
  • Trustworthy data sharing is vital to scaling up data access: trust in privacy protection, trust in the quality of the data and trust in how data are used.
  • Stakeholders and efforts need to collaborate, especially with patients, to develop a portfolio of equitable and acceptable models that can be promoted globally.
Nov 2916:20
Conference pass

From data lakes to actionable data

Track 5- AI, AUTOMATION AND MACHINE LEARNING
  • We can now build large collection of data spanning proprietary and public datasets (e.g.: -omics, RWE)
  • Leveraging these resources requires a data checking, cleansing and preparation process. This is an expensive process, that often needs to repeat for different investigations.
  • To which extent can we automate or semi-automate data curation processes?
  • We report on experiences and ideas in the use of rules, machine learning and AI systems to automate data curation process.
  • We discuss limitations, value and perspective developments.
last published: 18/Sep/18 12:55 GMT

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Contact us

To sponsor or exhibit contact:
Alistair Wilmot
+44 (0)207 092 1174

alistair.wilmot@terrapinn.com


To speak:
Chris Shanks
+44 (0)207 092 1151

chris.shanks@terrapinn.com