Impact of AI on Clinical Development

How to find us: UCB, 208 Bath Road, Slough, SL1 3WE

In association with PSI, UCB and Cytel are delighted to invite you to join a symposium, educating on Artificial Intelligence (AI) approaches and their impact on clinical development.

With so many recent advances in AI, it is important both for statisticians to keep up to date with the most recent methods and be involved in guiding their application to the most pressing statistical challenges. This one-day event will cover cutting edge examples of how data science and statistical sciences are intersecting, and where attendees can fit into that space. Come to learn and discuss why different approaches matter when looking at clinical development data.

Here's 5 reasons why you can't afford to miss it:

Hear from the experts leading the way in AI: We have exciting speakers from the University of Oxford, PSI, Roche, Cytel and UCB

2 Observe real case studies: Learn from current Industry challenges and successes

3 Statistical mind shift: Appreciate the importance of different approaches when looking at the data and augment existing methods

4 Making machine learning more accessible: Technology showcase of latest tools

5 Network with your peers: Exchange insights and help shape the new paradigm




09:00 - 09:30

Registration and Coffee

09:30 - 9:45

Karim Malki, Head, Predictive Analytics, UCB

09:45 - 10:45

Understanding activity patterns through wearable devices and AI algorithms
Chris Holmes, Professor of Biostatistics in Genomics in the Nuffield Department of Clinical Medicine and the Department of Statistics, University of Oxford

10:45 - 11:30

Why statisticians should be driving machine learning and AI projects
Dr Moira Verbelen, Principal Statistician, UCB

11:30 - 11:45


11:45 – 12:30

The need for data science in the new clinical development paradigm
Francis Kendall, Senior Director, Biostatistics and Programming, Cytel

12:30 - 13:30

Lunch and Networking

13:30 - 14:15

Technology Showcase
Dr Bhushan Bonde, Head of IT - NewMeds Innovation Development, UCB

14:15 - 15:00

Predicting Crohn's disease risk in asymptomatic relatives
Dr Ken Hanscombe, Research Associate at King’s College London

15:00 - 15:15

Coffee Break

15:15 - 16:00

Roche's experience developing Advanced Analytics Communities both internally and externally
Chris Harbron, Expert Statistical Scientist, Roche

16:00 – 16:45

Panel Discussion

16:45 – 17:00

Closing Remarks

17:00 – 18:00

Drinks Reception and Networking

Please click here to register, please email PSI@mci-group.com to advise of any dietary requirements ASAP. 


£60 + VAT
Registration deadline is Friday 6th September 2019




Technology Showcase

Abstract: This will be a technical demonstration highlighting some of the latest technology available for performing machine learning and other high intensity computational tasks, including a demonstration of Intel’s portable neural compute stick and a look at how new advances, such as quantum computing, will change the technological landscape.

Chris Holmes (University of Oxford)

Understanding activity patterns through wearable devices and AI algorithms

 New measurement technologies such as wearable devices coupled with AI algorithms, that can learn from large scale streaming data, have the potential for improved evaluation and monitoring of treatment interventions. In this talk we review the prospect for AI to better characterise population activity variation through wearable tech including an analysis of accelerometer data from 100,000 participants in UK BioBank.

Frances Kendall (Cytel)

The need for Data Science in the New Clinical Development Paradigm

Abstract: This talk will set the stage on why Data Science is needed to support a New Clinical Development paradigm and what are the drivers of change. It will then put forward an idea on what that Paradigm could look like with examples of work that demonstrate this direction.

Moira Verbelen (UCB)

Why statisticians should be driving machine learning and AI projects

Advancements in computer science have popularised the widespread use of machine learning and AI. Although methods were mainly developed by computer and data scientists, they are rooted in statistical science. Statisticians are ideally placed to guide the implementation of these ‘new’ approaches in pharma. In-depth understanding of statistical concepts and model fitting are essential skills required to avoid pitfalls such as poor algorithm design, overfitting and incorrect interpretation of results. These considerations and the ensuing value of statisticians’ involvement are even more important in clinical development, where datasets tend to be smaller than those typically used for AI.

Ken Hanscombe (King’s College London)


Predicting Crohn's disease risk in asymptomatic relatives

An application of elastic net and random forest classifiers to Crohn’s disease (CD) risk in asymptomatic first-degree relatives (FDRs) of CD patients, using multiple environmental and genetic predictors.

Chris Harbron (Roche)

Roche's experience developing Advanced Analytics Communities both internally and externally

 Roche has been successful in building an internal advanced analytics community consisting of over 750 data scientists from across the global Roche organization as well as establishing a number of external advanced analytics partnerships.  This talk will discuss how Roche have approached this effort as well highlighting some of the successes and challenges, including crowd sourcing the internal community to tackle key scientific research questions using machine learning.  

Upcoming Events

Latest Jobs