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:
1 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
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
Break
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
£60 + VAT
Registration deadline is Friday 6th September 2019
Abstracts
UCB
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
Abstract: 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
Abstract: 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
Abstract: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
Abstract: 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.
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:
1 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
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
Break
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
£60 + VAT
Registration deadline is Friday 6th September 2019
Abstracts
UCB
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
Abstract: 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
Abstract: 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
Abstract: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
Abstract: 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.
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:
1 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
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
Break
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
£60 + VAT
Registration deadline is Friday 6th September 2019
Abstracts
UCB
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
Abstract: 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
Abstract: 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
Abstract: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
Abstract: 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.
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:
1 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
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
Break
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
£60 + VAT
Registration deadline is Friday 6th September 2019
Abstracts
UCB
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
Abstract: 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
Abstract: 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
Abstract: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
Abstract: 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.
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:
1 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
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
Break
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
£60 + VAT
Registration deadline is Friday 6th September 2019
Abstracts
UCB
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
Abstract: 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
Abstract: 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
Abstract: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
Abstract: 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.
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:
1 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
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
Break
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
£60 + VAT
Registration deadline is Friday 6th September 2019
Abstracts
UCB
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
Abstract: 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
Abstract: 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
Abstract: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
Abstract: 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
PSI Book Club: Change: How organisations achieve hard-to-imagine results in uncertain and volatile times
Organizations have to adapt to the transforming landscape of our industry to ensure they continue to be successful in the future. Many of us are feeling the impact of organizational change. By reading John P Kotter’s book we can understand about organizational change and learn how to thrive, rather than just survive, through change.
Change, by John P Kotter (and his team), is a summary of all that he has learned over his decades of research and leading change. His book describes why many current approaches to change are inadequate and explains why new solutions need to give people a voice and a role in a new, change-embracing organization.
Develop your understanding of organisational change and become empowered to be part of your organisation’s change, by reading Change by John P Kotter and joining the Sept-Dec 2025 book club. You will be invited to join facilitated discussions of the concepts and ideas and apply knowledge from the book in-between sessions.
Joint PSI/EFSPI Visualisation SIG 'Wonderful Wednesday' Webinars
Our monthly webinar explores examples of innovative data visualisations relevant to our day to day work. Each month a new dataset is provided from a clinical trial or other relevant example, and participants are invited to submit a graphic that communicates interesting and relevant characteristics of the data.
PSI Training Course: Propensity Scores: Practical Application in Non-randomised Studies
The course will introduce the topic of propensity scores and the use of external data. Covering the topics of matching and weighting as well as more advance topics of high dimension propensity scores, multi-valued treatments, double robustness and time-varying scenarios. There will be the opportunity to participate in some hands on practical exercises in R.
Our monthly webinar series allows attendees to gain practical knowledge and skills in open-source coding and tools, with a focus on applications in the pharmaceutical industry.
Making Estimands Work - Practical Approaches with Implementation in Data Standards
This event will discuss the impact of the estimand framework on data flow and data handling for analysis datasets (ADaM). What are the considerations to produce data sets suitable for estimation of estimands and traceability of the occurrence of intercurrent events. This webinar will include tips for best practice, based on the White paper Implementation of ICH E9(R1) Estimands Framework using Data Standards.
PSI/EFSPI Biomarker SIG Webinar: Statistical Methods for ctDNA Data
This webinar will describe what ctDNA is and what the key challenges are for analysing it. We will then summarise and review methods that were published over the last few years for analysing ctDNA data.
The morning will be dedicated to networking opportunities, helping attendees build connections with peers and professionals. In the afternoon, participants can attend a series of talks and workshops, including a career panel featuring speakers from both academia and industry, offering insights into various career paths. There will also be a statistical workshop, as well as the opportunity to learn about and debate some of the hot topics in the world of medical statistics. To wrap up the day, we’re exploring interest in an informal after-work networking event for those keen to continue the conversation.
Joint PSI/EFSPI, Phuse, ASA Safety Working Group Webinar Series: Overview of safety analysis and implementation process of safety surveillance in ongoing studies
The session will have three speakers and a discussant. This session will be the first in a series of webinars around safety in clinical trials. The series is co-organized by PSI, ASA-Biopharm safety working group and PHUSE.
This two-afternoon virtual course provides a practical introduction to adaptive clinical trials, focusing on the concepts, applications, and regulatory principles outlined in ICH E20 through real-world examples and case studies.
PSI Vaccines SIG Webinar: Statistical Immune Correlate Analysis of Hemagglutination Inhibition Titers for an mRNA-based Influenza Vaccine
This 1-hour webinar is designed for statisticians with an interest in vaccine development, to learn about the recent application of statistical immune correlate analysis in vaccine development. Specifically, an application of such analyses to evaluate hemagglutination inhibition titers for an influenza vaccine
PSI Careers - MEDMathS: Medicine Empowered by Data, Maths and Statistics
Date: Wednesday 4th November 2026
A careers talk about medical statistics and how it plays a crucial role in developing new medicines. Learn about the field of medical statistics and how it plays a crucial role in developing groundbreaking new medicines, vaccines and healthcare products.
Date: 18 November 2026
This is an excellent opportunity for students to find out more about the field of medical statistics, talk to people from different organisations and make contacts for the future. All students currently studying for a mathematics or statistics-related BSc, MSc or PhD are invited to attend, and we welcome interest from exhibitors too.
Aligning Estimation with the Clinical Question of Interest
This webinar will focus on aligning estimation to estimands. How do different strategies for handling intercurrent events and missing data handling influence the choice of estimation method, with illustration using a case study.
This networking event is aimed at statisticians that are new to the pharmaceutical industry who wish to meet colleagues from different companies and backgrounds.
PSI Careers Coaching Series: Peer Support Initiative
This 10-month peer support programme is aimed at professionals with five or more years of experience who are seeking structured development and connection with peers at a similar career stage. Through 5 bi-monthly topics, participants will engage in coach-led presentations, small-group discussions, and regular progress reviews focused on achieving tangible outcomes.
In this vital role you will generate evidence to meet Health Technology Assessment (HTA) requirements, while ensuring that the analyses performed meet required standards and are robust and valid.
Bristol Myers Squibb - Director, Statistical Methodology and Innovation
Lead the development of innovative statistical methods, provides expert consulting, oversees tools and software, and mentors team members while collaborating cross-functionally to address complex drug development challenges.
Phastar – Associate Director, Statistics – Real World Evidence (RWE)
As an Associate Director, Statistics (RWE) you will focus on supporting one of our key pharmaceutical clients within our FSP function. This will be a hands-on technical role, with oversight responsibilities and cross-functional exposure.
Phastar – Principal Statistician – Real World Evidence (RWE)
We are seeking an experienced Statistician to join our FSP team to support one of our fantastic and well-known global pharmaceutical clients, at Principal level.
We are seeking an experienced Statistician to join our FSP team to support one of our fantastic and well-known global pharmaceutical clients, at either Senior or Principal levels.
This position is deal for a statistician who values ownership, collaboration, and using data to enable confident development decisions and to support regulatory submissions.
