AI ML 

AI/ML has vast transformation potentials for pharmaceuticals and healthcare. Here we will look into some of the leading examples and use cases so that you can learn how to integrate the technology across your organisation. 

 

AI ML, Wednesday 4 December 2019

08:00

Registration and Refreshments

09:00

Keynote [Reserved for Roche CEO]

09:20

Title Sponsor

Frank Lee
09:40

Getting your data and applications ready for precision medicine

  • Learn about key capabilities of the underlying reference architecture for high performance data and AI (HPDA) to manage the ocean of data and optimize your AI and big data pipelines for analysis.
  • Understand how to improve data quality through advanced metadata management using content-based and policy-driven data classification & tagging.
  • Discover how to support hybrid multicloud workload orchestration with end-to-end automation of workflows, leveraging containers and cloud using a self-service 'App Hub'.
  • Hear about use cases from the world's fastest genomics pipeline to the largest variant database and explore how your organization can improve speed, scalability, collaboration and ease of use and gain significant cost efficiencies
Georges Heiter
10:00

New Frontiers in Data Science – the role of automation in accelerating scientific discovery

10:40

Speed Networking

11:00

Morning refreshments

round tables
11:40

Roundtables

(click to see full list)
Accelerating operations and analytics with High Speed Data sharing across platforms and the world
Laurent Martin

Laurent Martin, Aspera Pre-Sales Engineer - EMEA, IBM Global Markets

Data collection & algorithmic training for biomedical tasks: utilisation and strategies
Anastasia Georgievskaya

Anastasia Georgievskaya, General Manager, Haut.AI

Data Lakes, Getting data ready for analytics, and Personalized Health Data
Christian Blumenroehr

Christian Blumenroehr, Principal Scientist, F. Hoffmann-La Roche

Data Privacy and Democratisation
Matthew Rooney

Matthew Rooney, Chief Clinical Information Officer, Heart of England NHS Foundation Trust

Dell EMC
Design thinking: Driving forwards innovation in pharmaceuticals
Hermann Tribukait

Hermann Tribukait, Founder & CEO, ChemOS Inc.

Diagnosis based on genetic information and public ontologies and databases, improving the diagnosis process of rare disease patients with Foundation29
Pablo Botas

Pablo Botas, Head of Science, Foundation 29

Digital transformation across pharma
Jessica Federer

Jessica Federer, Ex Chief Digital Officer, Bayer

How big data is effecting precision oncology
Andrej Benjak

Andrej Benjak, Bioinformatician, University of Bern

IMI - EDHEN + BD4BO- The pro’s and con’s of the different IMI projects approaches. IT and high tech aspects. Gaining insights into the technical approaches to working with Real World Data at scale. Central vs. Federated; Working to promote FAIR principles
Matthew Wiener

Matthew Wiener, Director, Informatics And Predictive Sciences, Celgene

Investment in AI and Healthcare in China
Vibhor Gupta

Vibhor Gupta, Director and Founder, Pangaea Data

Is bad User Experience (UX) hindering drug discovery? What are the challenges and opportunities for UX in life science software and digital transformation?
Ronald Johnston

Ronald Johnston, Director Of Product And E-Commerce, Merck Digital

Lessons learned in running an AI-enabled operation for precision medicine – privacy, policy, and technical challenges and how we overcame them
Florina Ciorba

Florina Ciorba, Professor Hpc, University Basel

NTT Data
Partnerships across Pharma and Tech – Deals, IP and Timelines
Miron Tokarski

Miron Tokarski, CEO, Genomtec

Phage Display AI and Genomics – Using next generation AI and phage display to generate new immunological targets
Christian Bender

Christian Bender, Data Scientist, Bayer

Reproducibility in Bioinformatics and Big Data Analytics: Myth or Reality?
Raffaele Calogero

Raffaele Calogero, Professor, University of Torino

Roche
Roche - All4IBD: a Digital Medicine Toolkit to transform care in Inflammatory Bowel Disease (IBD)
Sumanjit Sethi

Sumanjit Sethi, Digital Health Leader, Immunology, Infectious Diseases and Ophthalmology, F. Hoffmann-La Roche Ltd

Roche - Analytical challenges with multimodal patient data: deriving drug development insights from clinico-molecular data
Gunther Jansen

Gunther Jansen, Group Director, PHC Data Science Analytics, Roche

Takeda
There is no AI without IA: Building a solid Information Architecture for your AI and high performance Precision Medicine
Frank Lee

Frank Lee, PhD, Global Healthcare and Life Sciences Industry Leader, IBM Systems

Title TBC
Visualisation of good quality data and the pursuit of metrics to drive efficiencies in clinical trials
Paolo Piraino

Paolo Piraino, Head Of Genomics And Biomarker Statistics, Bayer

Western Digital
12:30

Networking Lunch

Nadeem Sarwar
AI ML
13:35

Developing a spin in AI and Drug Development Company

Nick Scott-Ram
AI ML
13:55

RWD and the NHS – accessing anonymised data for deeper research

Jonathan Dry
AI ML
14:15

Knowlage Graph Databases

Jonathan Dry, Director, Data Science And Bioinformatics, Early Oncology, AstraZeneca
14:35

Afternoon Refreshments

16:10

Afternoon Refreshments

Tom Chittenden
AI ML
16:55

Unconventional Machine Learning of Genome-wide Human Cancer Data

  • We evaluated several unconventional machine learning (ML) strategies on actual human tumor data and showed for the first time the efficacy of multiple annealing-based ML algorithms for classification of high-dimensional, multi-omics human cancer data from the Cancer Genome Atlas.
  • To assess algorithm performance, we compared these classifiers to a variety of standard ML methods and results indicate the feasibility of using annealing-based ML to provide comparable classification of human cancer types and associated molecular subtypes and superior performance with smaller training datasets.
  • Our results provide compelling empirical evidence for the potential future application of unconventional computing architectures in the biomedical sciences.
Robin Bramley
AI ML
17:35

Biomedical semantic indexing with MeSH

In this session, we’ll present a novel neural network architecture that consists of a network-of-networks endowed with an attention mechanism for the purpose of biomedical semantic indexing based on MeSH. This network learns both the appropriate labels for each document and the relationship between the labels for a given text. We’ll share results up to depth three of the MeSH hierarchy. Tagging at the third level of the hierarchy allows for more specific metadata, yet due to the hierarchical nature these tags can still be included in broader category searches.The session will alsocover text pre-processing, hierarchy representation, feature descriptors, and model evaluation. For the latter, in addition to micro- and macro F1, we consider metrics that distinguish between accuracy and precision; a distinction that is of practical importance when evaluating results for hierarchical classification.State-of-the-art classification performance gives greater confidence in automatic tagging
Brigitte Fuhr
AI ML
17:55

GPS for chemical space - Digital assistants to support molecule design

Nils Weskamp, Principal Scientist Computational Chemistry, Boehringer Ingelheim Pharma GmbH & Co. KG
18:15

Drinks Reception

last published: 22/Oct/19 09:35

AI ML, Thursday 5 December 2019

08:30

Presentation [Reserved Novartis CEO]

10:00

Western Digital

11:05

Networking break

round tables
11:45

Roundtables

(Click to see full list)
Analytical challenges with multimodal patient data: deriving drug development insights from clinico-molecular data
Gunter Jansen

Gunter Jansen, Group Director, PHC Data Science Analytics, Roche

Data privacy sharing and analytics how technology can help
Andrew Roddam

Andrew Roddam, Vice President And Global Head Epidemiology, GSK

DELL
Developing a Spin in Bioinformatics Company
Nadeem Sarwar

Nadeem Sarwar, Founder And President, Eisai

Digital Biomarkers as endpoints in clinical trials: an opportunity for Personalised Healthcare
Christian Gossens

Christian Gossens, Digital Biomarker Informatics; Global Area Head; pRED Informatics, Roche

Digital transformation in pharma
Jessica Federer

Jessica Federer, Ex Chief Digital Officer, Bayer

Digital Transformation of Health Care
Markus Mäkelä

Markus Mäkelä, Co-Founder, PredictCare LLC

Educating data scientists for the pharmaceutical industry
Jake Chen

Jake Chen, Chief Bioinformatics Officer, University of Alabama at Birmingham

IBM
IMI - The need for data communities in Europe, and why should you care? Looking ahead to an integrated European research meeting the need for RWD in a global environment.
Kiliana Suzart-Woischnik

Kiliana Suzart-Woischnik, Epidemiology Director, Bayer

Learnings and results from large-scale investments in data across the pharmaceutical R&D chain
Greg Temesi

Greg Temesi, Director, R&D It - Product Strategy, Merck

Point of Care Diagnostics
Miron Tokarski

Miron Tokarski, CEO, Genomtec

Roche - All4IBD: a Digital Medicine Toolkit to transform care in Inflammatory Bowel Disease (IBD)
Sumanjit Sethi

Sumanjit Sethi, Digital Health Leader, Immunology, Infectious Diseases and Ophthalmology, F. Hoffmann-La Roche Ltd

Stop talking about the principles, start showing what FAIR really means - Gaps in IT capabilities to support FAIR data and services
Martin Romacker

Martin Romacker, Data And Information Architect, Roche

Wearable data and challenges around it that involve data ingestion, technology required for computation, data preprocessing and transformation and advanced analytics methods
Stephan Cichos

Stephan Cichos, Principal Data Manager, Bayer

Western Digital
Colm Carroll
12:30

IMI Lunchtime Panel- It is now or never! Connecting data communities with clinical research communities

How do we link research interests at scale and across data permeable borders in Europe? Building at scale communities; Expanding the FAIR principles in the EU; Understanding the quid pro quo between data partners and researchers.
  • Building at scale communities
  • Expanding the FAIR principles in the EU
  • Understanding the quid pro quo between data partners and researcher
Colm Carroll, Scientific Project Manager, Innovative Medicines Initiative
12:30

Lunch

AI ML
13:35

CytoReason

AI ML
13:55

Linguamatics

Christian Bender
AI ML
14:15

Using machine learning to select tool antibody candidates based on phage display pool sequencing data - an alternative to conventional screening?

14:35

Afternoon Refreshments

AI ML
15:05

Chair's remarks

Basker Gummadi
AI ML
15:10

Combining Blockchain, Machine learning and Process Automation to Optimize the Future of Clinical Development

AI ML
15:30

Numerate

16:30

Afternoon Refreshments

Satu Nahkuri
AI ML
17:05

Vision and Showcase of Machine Learning at Roche

Misti Ushio
AI ML
17:25

BiowireTM II : Generating Human-relevant Data Sets from Tissue Engineering Platforms

  • TARA generates proprietary human relevant data sets to enable predictive algorithm development.
  • The BiowireTM II tissue platform produces engineered heart tissue, with unprecedented functionality, that can predict human drug response.
  • These data sets can help bridge the translation gap between human as existing models.
Friedrich Rippmann
AI ML
17:45

Achieving operational benefit and embracing novel opportunities in AI for early drug discovery

18:05

Close of Conference

last published: 22/Oct/19 09:35

 

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