CRASH COURSE IN DATA ANALYTICS THURSDAY 13TH SEPTEMBER 2018Attend our post-conference Crash Course designed to give you hands on experience with industry standard big data sets and teach you how to write code in R! This Crash Course will equip you with the right tools and critical thinking you need to optimise your data strategy, and will also discuss real life examples of Machine Learning and A.I. technologies - specifically applied for Pharma R&D!

Leave This Crash Course With:A 360-degree view into the world of big data, data science

and machine learning

Knowledge of a broad range of technical and business big data analytics topics – this course caters to the interests of technical

experts as well as corporate IT executives

Hands-on experience with industry-standard big data and machine learning tools such as Hadoop, Spark, MongoDB, KDB+ and R

Experience of creating production-grade machine learning BI Dashboards using R and R Shiny with step-by-step instructions

Understanding of how to combine open-source big data, machine learning and BI Tools to create low-cost business analytics

applications

Tangible corporate strategies for successful Big Data and data science projects

Confidence to go beyond general-purpose analytics to develop cutting-edge big data applications using emerging technologies

Recommended Books:Published: Practical Big Data AnalyticsIn press: Hands-On Data Science with R

Nataraj has 19 + Years of industry leading experience in developing the vision, strategy and execution of cutting-edge analytics platforms for Big Data & Data Science. Formerly the senior architect for Purdue Pharma’s Award-Winning Analytics Platform, Nataraj has an excellent track record of developing Machine Learning & algorithmic use cases for Enterprise. Most recently he has published an acclaimed guide on the practical use of R, Python, Unix Tools for Machine Learning/AI and KDB+, Hadoop & Massively-Parallel Systems for Big Data.

12:30 – 13:30Networking and

Lunch Break - An excellent time to

interact with the author and submit specific needs

discussion ideas for the afternoon session!

16:30Certifications and

Networking

09:30 - 12:30 MORNING SESSION

Defining your Healthcare Data Strategy

Data Management, Data Governance and Data Analytics for Pharma R&D

Where is the data? The many sources of valuable patient &

physician level data in the public-domain for Pharma & Healthcare

Analysing data with Open Source Tools: Hadoop, Spark & other solutions

Writing code in R: Theory & Hands-On Practice using actual Physician, Patient-Level Data

from NHS & FDA

13:30 - 16:30 AFTERNOON SESSION

Real-World Use Cases with Real-World Data (RWE) in Healthcare & Pharma

Emerging Paradigms: IoT Connected Medical Devices, Immunotherapy &

Personalised Treatments

Success stories in utilizing Machine Learning & AI for Pharma R&D and

Market ResearchLeveraging Machine Learning and AI for

identifying actionable opportunities in your organization

Discussion on audience specific needs and next steps

09:00Welcome Coffee and Registration

WORKSHOP SESSION FACILITATED BY:

Nataraj Dasgupta, Author, Practical Big Data Analytics: Hands-on

techniques to implement enterprise analytics and machine learning

using Hadoop, Spark,NoSQL and R

MEET THE SPEAKER

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CONFERENCE DAY ONE TUESDAY 11TH SEPTEMBER 201808:30 Morning Registration and Coffee

09:00 PharmaIQ Welcome

09:05 Chairman’s Opening Remarks

09:20 Models of Prospective Curation in the Drug Research Industry Discuss drug industry data management - knowledge persistence and knowledge vigilance Apply ontologies and machine learning-based approaches to deliver a much needed change Make the process of data and knowledge acquisition more attractive

Samiul Hasan, Director Data Curation, GSK

10:00 CASE STUDY: Data Lake Validation in the AWS Cloud Discover how to build a platform base for analytics projects Integrate unstructured documents in order to achieve intelligent knowledge acquisition forms Develop your own machine learning platform culture

Daniel Caparros, IT Validation Process Strategy Lead, Merck Group

10:40 Morning Coffee Break

11:10 Parasite Counter: A Machine Learning Case from Vet Pharma Learn how to integrate machine learning into your data strategy Empower your research with machine learning technologies Develop a strategy to turn the insights you draw into actionable plans

Brunhilde Schölzke, Associate Director R&D IT, MSD Animal Health Innovation

11:50 Data Intelligence in Pharma R&D: Semantics meets Analytics Discover why, in complex scenarios, information is much more a “knowledge graph” than just a bunch of tables Learn how data intelligence is a coming together of “Semantics” (Ontologies) and analytics Understand how with semantic underpinning, the investigative analytic UI can automatically suggest connections in

dashboards and graph/link analysis

Giovanni Tummarello, CFO/Founder, Siren Solutions

12:30 Networking Lunch Break

13:30 Blockchain Use Cases in Pharma Ensure authenticity of health records and protocols on record sharing Eradicate fraudulent altering or modification of patient data and clinical trial data Empower research and accelerating collaboration across the board in order to ensure adoption

Pascal Bouquet, Global Head Technology and Architecture for Global Drug Development, Novartis

14:10 CASE STUDY: Applied A.I. in Clinical Development Analyse why AI should be implemented in clinical development Discover how to overcome key obstacles to deploy a production-level AI in drug discovery Examine examples of successful AI applications in drug discovery and patient stratification

Leonardo Rodrigues, Senior Director, AI & Machine Learning, BERG Heath

14:50 Afternoon Coffee Break

15:10 Toward a Company Wide Data Infrastructure Foster a productive culture of collaboration across departments Develop your own non-competitive way to stay ahead of the curve Implement a data strategy that factors in contractor obligations and market access

Maman Khaled, European HTA and Health Economics Manager, Otsuka Pharmaceutical Companies

DATA STRATEGY

DATA STRATEGY

MACHINE LEARNING

ADVANCED ANALYTICS

ADVANCED ANALYTICS

ARTIFICIAL INTELLIGENCE

BLOCKCHAIN

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CONFERENCE DAY ONE TUESDAY 11TH SEPTEMBER 201815:50 Data Quality-Defined Analytics Processes for Drug Development

Define your unique process and analytical variability quality challenges Advance your predictive modelling with lessons learned from the Centre for Process Analytics & Control Technology Discuss strategies to improve your data visualisation

Julian Morris, Technical Director, CPACT

16:30 PANEL DISCUSSION: Integrating Innovation into your R&D Strategy

What is the best strategy to begin integrating M.L., A.I. & Blockhain into your company?

Is it only R&D? Learning from collaboration externally and internally Where is the proof - ROI or buzz words? Pascal Bouquet, Global Head Technology and Architecture for Global Drug Development, NovartisDavid Whewell, Director of Architecture and Software Innovation, Merck Group

17:30 Chairman’s Closing Summary of Day One

17:45 Networking Drinks Reception

DATA MANAGEMENT

Good content that allows to dig deeper into the most relevant

topics & themes related to my job.

Head of Labware Centre of Excellence and R&D Lab Projects, GSK

This was interesting as it showed some real work examples and

also implementation.

Novo Nordisk

Very good conference, lot of

insights what other companies are doing.

Abbvie

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CONFERENCE DAY TWO WEDNESDAY 12TH SEPTEMBER 201808:30 Morning Registration and Coffee

09:00 Chairman’s Opening Remarks

09:15 The Value and Challenges of a Real World Data Strategy Learn the key elements of an effective RWD strategy Explore the roles of Stakeholders, Technology, Talent, & Partnerships Review various approaches for a RWD programme in pharma with a case study Discuss key case studies and challenges for RWD in pharma Analyse how value can be gained from a RWD programme

Larry A. Pickett, Former CIO & VP, Purdue Pharma, LP

09:55 CASE STUDY: Increasing Productivity by Utilising Real World Data Evidence Bring drugs to market faster by integrating RWD into your drug development process. Analyse the use of “synthetic control arms” of real world data to complement single-arm trials Increase your ROI with successful implementation of a RWD strategy

Matt Wiener, Director, Data Science, IKU in EMEA, Celgene

10:35 Morning Coffee Break

10:50 ROUNDTABLES: Gain Tangible Ideas on How to Solve Your Biggest Challenges

Find out what your peers are planning, share ideas and learn from others’ experiences in these open and informal discussions on how to solve:

11:30 CASE STUDY: How to Utilise Data Analytics to Advance Personalised Medicine Develop a holistic environment for insight into better patient health outcomes Grow industry-wide visibility on clinical practices Analyse new links between diseases and underlying symptoms; crucial in the chronic disease space

David Whewell, Director of Architecture and Software Innovation, Merck Group

12:10 Networking Lunch Break

13:10 Coordination and Optimisation of External Data Sources in the Drug Development Process Establish a data system framework to amalgamate external Electronic Health Information data Effectively integrate external EHI data into the drug developmental process Utilise a combination of data sources to effectively structure your developmental strategy

Mats Sundgren, Principal Scientist, AstraZeneca

13:50 The Post GDPR World of Data Security and Transparency Avoid heavy fines – make sure you understand contract obligations under GDPR Protect your data - cyber security in Pharma Define and understand country specific regulatory exemption and compliance

Tarun Samtani, Group Data Privacy Lead – GDPR, Vectura Group plc.

14:30 Afternoon Coffee Break

DATA STRATEGY

PRECISIONMEDICINE

COMPLIANCE

CLINICAL TRIAL OPTIMISATION

REAL WORLD DATA

Internal Collaboration:

keeping everyone in

the data loop

Collaboration with HCPs

Security and Blockchain

Patient & consumer?

Retaining the value story

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CONFERENCE DAY TWO WEDNESDAY 12TH SEPTEMBER 201815:10 CASE STUDY: Liberating Real World Evidence from Federated Networks in Europe – What Have We Learned and

Where are we Going? Analyse what we know now after 5 years of the IMI European Medical Information Framework (EMIF) Look towards the IMI2 European Health Data and Evidence Network (EHDEN): what are we aiming for in 2023? Investigate other federated initiatives and the EU health data ecosystemNigel Hughes, Scientific Director, Janssen

15:50 CASE STUDY: Coordination and Optimisation of External Data Sources in the Drug Development Process Integrate external Electronic Health Information data with your legacy data Draw actionable insight and feed data evidence into the drug developmental process Utilise a combination of data sources to effectively structure your developmental strategy

John Mulcahy, Founder, HealthGenuity

16:30 Chairman’s Closing Remarks

REAL WORLD DATA

DIGITAL HEALTH

Did you know that you also get access to our co-located SmartLabs Forum? Find out how to build the Lab of the Future!

Psst…

Forum

Well established panel of experts.

FDA

Excellent meeting, very good speakers and opportunity to network.

Janssen

A good place to hear about real use cases from other pharma.

Sanofi

Wide range of topics, very clear input relating to data in pharma, also, a real eye opener in relation to what we all need to be doing if we are to survive the data revolution.

Biogen

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