Impact of AI on Clinical Development

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 Book Club - The Art of Explanation: How to Communicate with Clarity and Confidence

Develop your non-technical skills by reading The Art of Explanation by Ros Atkins and joining the Sept-Dec 2025 book club. You will be invited to join facilitated discussions of the concepts and ideas and apply skills from the book in-between sessions.

Open-Source Lunch Bites

Our monthly webinar will allow attendees to gain practical knowledge and skills in Open-Source coding and tools, with a focus on applications in the pharmaceutical industry. The sessions will provide starting points in a number of areas, correct any common misconceptions and provide valuable resources for further learning.

PSI Journal Club: Randomization

Date: Tuesday 9th September 2025 Join us to hear Sofia Weigle and Weng-Kee Wong present their recent work.

PSI Training Course: Pediatric Extrapolation

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.

PSI Career Young Virtual Event (Q3 2025)

This networking event is aimed at statisticians that are new to the pharmaceutical industry who wish to meet colleagues from different companies and backgrounds.

Pre-Clinical SIG Webinar: AI agents for drug discovery and development

AI agents are large language models equipped with tools that can autonomously tackle challenging tasks. This talk will explore how generative AI agents can enable biomedical discovery.

EFSPI/PSI Causal Inference SIG Webinar: Instrumental Variable Methods

The webinar is targeted at statisticians working in the pharmaceutical industry, and the objective is to 1) provide a basic understanding of IV methodology including how it relates to causal inference, and 2) present two inspirational pharma-relevant applications.

PSI Pre-Clinical Workshop - October 2025

The Pre-Clinical Special Interest Group (SIG) Workshop 2025 will take place over two half-days on 7 - 8 October in Verona, Italy, bringing together experts from industry, academia, and regulatory institutions to discuss key challenges and innovations in pre-clinical research.

PSI Training Course: Introduction to Machine Learning

Four sessions will include ML foundation (including an introduction, data exploration for ML and dimensionality reduction and feature selection), Supervised learning (including support vector machines and model evaluation and interpretation), model optimization and unsupervised learning (including clustering) and advanced topics (including neural networks, deep learning and large language models).

PSI/EFSPI Vaccines Statistics Workshop

The program will feature insightful sessions led by distinguished invited speakers, alongside a poster session showcasing the latest advancements in the field. Further details will be provided.

PSI Careers - MEDMathS: Medicine Empowered by Data, Maths and Statistics

Date: Wednesday 5th November 2025 A careers talk about medical statistics and how it plays a crucial role in developing new medicines

PSI Medical Statistics Student Careers Event 2025

Date: 19 November 2025 This event is aimed at students with an interest in the field of Medical Statistics, for example within pharmaceuticals, healthcare and/or medical research.

PSI Career Young Virtual Event (Q4 2025)

This networking event is aimed at statisticians that are new to the pharmaceutical industry who wish to meet colleagues from different companies and backgrounds.

Time	Agenda
09:00 - 09:30	Registration and Coffee
09:30 - 9:45	Welcome 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	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
16:00 – 16:45	Panel Discussion
16:45 – 17:00	Closing Remarks
17:00 – 18:00	Drinks Reception and Networking

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.

Time	Agenda
09:00 - 09:30	Registration and Coffee
09:30 - 9:45	Welcome 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	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
16:00 – 16:45	Panel Discussion
16:45 – 17:00	Closing Remarks
17:00 – 18:00	Drinks Reception and Networking

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.

Time	Agenda
09:00 - 09:30	Registration and Coffee
09:30 - 9:45	Welcome 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	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
16:00 – 16:45	Panel Discussion
16:45 – 17:00	Closing Remarks
17:00 – 18:00	Drinks Reception and Networking

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