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 Introduction to Industry Training (ITIT) Course - 2025/2026
An introductory course giving an overview of the pharmaceutical industry and the drug development process as a whole, aimed at those with 1-3 years' experience. It comprises of six 2-day sessions covering a range of topics including Research and Development, Toxicology, Data Management and the Role of a CRO, Clinical Trials, Reimbursement, and Marketing.
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.
Who is this event intended for? Statisticians with an interest understanding dose-finding in oncology.
What is the benefit of attending? Learn about the state of oncology dose finding, particularly in light of current FDA guidance.
PSI Book Club Webinar: Atomic Habits - The Science of Getting Your Act Together
The book club’s usual focus is to read and discuss professional development books. In this short format event you can more easily develop you career without the commitment of reading the whole book - simply listen to the 1-hour long podcast before joining the interactive session on 21 May.
PSI Webinar: Methods and tools integrating clinical trial evidence with historical or real-world data, Bayesian borrowing, and causal inference
This webinar is organised by the RWD SIG and the Historical Data SIG. We will review recent methods, applications, and tools of integrating subject-level-data from clinical trial with external data using Bayesian methods and/or causal inference methods.
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 Webinar: Applying the Estimand Framework to Clinical Pharmacology Trials with a Case Study in Bioequivalance
This will be a 45 minute webinar which will explain the topic presented in the published paper, ‘Applying the Estimand Framework to Clinical Pharmacology Trials with a Case Study in Bioequivalance’. There will be 15 minutes for a panel Q&A with some of the authors following the presentation.
One-day Event: Change Management for Moving to R/Open-Source
This will be a 45 minute webinar which will explain the topic presented in the published paper, ‘Applying the Estimand Framework to Clinical Pharmacology Trials with a Case Study in Bioequivalance’. There will be 15 minutes for a panel Q&A with some of the authors following the presentation.
This course is aimed at biostatisticians with no or some pediatric drug development experience who are interested to further their understanding. We will give you an introduction to the pediatric drug development landscape. This will include identifying the key regulations and processes governing pediatric development, a discussion on the needs and challenges when conducting pediatric research and a focus on the ways to overcome these challenges from a statistical perspective.
This networking event is aimed at statisticians that are new to the pharmaceutical industry who wish to meet colleagues from different companies and backgrounds.
This networking event is aimed at statisticians that are new to the pharmaceutical industry who wish to meet colleagues from different companies and backgrounds.
This is an exciting, new opportunity for an experienced Statistician looking to take the next step in their career. Offered as a remote or hybrid position aligned with our site in Harrogate, North Yorkshire.
The BioMarin internship programme will enable students to gain valuable experience and knowledge of the processes and systems within BioMarin, whilst gaining an insight into the pharmaceutical/biotech industry.
We use cookies to collect and analyse information on site performance and usage, to provide social media features and to enhance and customise content and advertisements.
Cookies used on the site are categorized and below you can read about each category and allow or deny some or all of them. When categories than have been previously allowed are disabled, all cookies assigned to that category will be removed from your browser.
Additionally you can see a list of cookies assigned to each category and detailed information in the cookie declaration.
Some cookies are required to provide core functionality. The website won't function properly without these cookies and they are enabled by default and cannot be disabled.
Amazon Web Services offers a broad set of global cloud-based products including compute, storage, databases, analytics, networking, mobile, developer tools, management tools, IoT, security, and enterprise applications.
Microsoft Azure is a cloud computing platform offering a wide range of services, including virtual machines, databases, and AI tools.
ARRAffinity
ARRAffinitySameSite
Preferences
Preference cookies enables the web site to remember information to customize how the web site looks or behaves for each user. This may include storing selected currency, region, language or color theme.
Analytical cookies
Analytical cookies help us improve our website by collecting and reporting information on its usage.
Vimeo, Inc. is an American video hosting, sharing, services provider, and broadcaster. Vimeo focuses on the delivery of high-definition video across a range of devices.
Cookies used on the site are categorized and below you can read about each category and allow or deny some or all of them. When categories than have been previously allowed are disabled, all cookies assigned to that category will be removed from your browser.
Additionally you can see a list of cookies assigned to each category and detailed information in the cookie declaration.
Some cookies are required to provide core functionality. The website won't function properly without these cookies and they are enabled by default and cannot be disabled.
Necessary cookies
Name
Hostname
Vendor
Expiry
ARRAffinity
.psiweb.org
Session
This cookie is set by websites run on the Windows Azure cloud platform. It is used for load balancing to make sure the visitor page requests are routed to the same server in any browsing session.
ARRAffinitySameSite
.psiweb.org
Session
Used to distribute traffic to the website on several servers in order to optimize response times.
__cf_bm
.vimeo.com
Cloudflare, Inc.
1 hour
The __cf_bm cookie supports Cloudflare Bot Management by managing incoming traffic that matches criteria associated with bots. The cookie does not collect any personal data, and any information collected is subject to one-way encryption.
_cfuvid
.vimeo.com
Session
Used by Cloudflare WAF to distinguish individual users who share the same IP address and apply rate limits
__cf_bm
.glueup.com
Cloudflare, Inc.
1 hour
The __cf_bm cookie supports Cloudflare Bot Management by managing incoming traffic that matches criteria associated with bots. The cookie does not collect any personal data, and any information collected is subject to one-way encryption.
AWSALBTGCORS
psi.glueup.com
7 days
AWS Classic Load Balancer Cookie: Load Balancing Cookie: Used to map the session to the instance. Same value as AWSELB.
PHPSESSID
psi.glueup.com
Session
Cookie generated by applications based on the PHP language. This is a general purpose identifier used to maintain user session variables. It is normally a random generated number, how it is used can be specific to the site, but a good example is maintaining a logged-in status for a user between pages.
Used by CookieHub to store information about whether visitors have given or declined the use of cookie categories used on the site.
Preferences
Preference cookies enables the web site to remember information to customize how the web site looks or behaves for each user. This may include storing selected currency, region, language or color theme.
Preferences
Name
Hostname
Vendor
Expiry
vuid
.vimeo.com
400 days
These cookies are used by the Vimeo video player on websites.
AWSALBCORS
psi.glueup.com
7 days
Amazon Web Services cookie. This cookie enables us to allocate server traffic to make the user experience as smooth as possible. A so-called load balancer is used to determine which server currently has the best availability. The information generated cannot identify you as an individual.
Analytical cookies
Analytical cookies help us improve our website by collecting and reporting information on its usage.