N of 1 trials are trials in which individual patients are repeatedly treated with experimental and control treatments in a deliberate and designed manner using principles of control, randomisation and replication. Their uses include personalising treatment and increasing efficiency by reducing the number of patients it is necessary to study.
In chronic diseases, sets of n-of-1 trials (in which a limited number of patients follow an n-of-1 protocol) have great potential as phase IV trials for understanding components of variation but may also constitute possible Phase III programmes for rare diseases. They can also be used as phase II studies for proof of concept and dose-finding. However, they are often poorly analysed and, indeed, much of the published advice is poor.
This course will present the latest thinking on n-of-1 trials and cover not only their analysis through SAS®, R® GenStat® and meta-analysis packages but also approaches to design. They will also be critically examined as to their potential use in a) establishing average effects of treatment b) studying the extent to which such effects vary from patient to patient and c) optimising treatment for individual patients.
Course leader
This course will be given by Professor Stephen Senn, of the Luxembourg Institute of Health, who is well- known for his work on the design and analysis of clinical trials and the application of statistics in drug development.
Topics covered
Uses of n-of-1 trials and purposes of analysis
Showing the treatment can work
Understanding variation in effect
Predicting effects
Design
Randomisation in cycles
Randomisation in patient blocks
Graphical presentation of results
Trellis plots
Dot plots
Causal analysis
Analysis of variance
Block structure and the Wilkinson & Roger notation
Main effect models
Allowing for interaction
Summary measures approaches
Mixed models
Estimation
Best linear unbiased predictors (shrunk estimates)
N of 1 trials are trials in which individual patients are repeatedly treated with experimental and control treatments in a deliberate and designed manner using principles of control, randomisation and replication. Their uses include personalising treatment and increasing efficiency by reducing the number of patients it is necessary to study.
In chronic diseases, sets of n-of-1 trials (in which a limited number of patients follow an n-of-1 protocol) have great potential as phase IV trials for understanding components of variation but may also constitute possible Phase III programmes for rare diseases. They can also be used as phase II studies for proof of concept and dose-finding. However, they are often poorly analysed and, indeed, much of the published advice is poor.
This course will present the latest thinking on n-of-1 trials and cover not only their analysis through SAS®, R® GenStat® and meta-analysis packages but also approaches to design. They will also be critically examined as to their potential use in a) establishing average effects of treatment b) studying the extent to which such effects vary from patient to patient and c) optimising treatment for individual patients.
Course leader
This course will be given by Professor Stephen Senn, of the Luxembourg Institute of Health, who is well- known for his work on the design and analysis of clinical trials and the application of statistics in drug development.
Topics covered
Uses of n-of-1 trials and purposes of analysis
Showing the treatment can work
Understanding variation in effect
Predicting effects
Design
Randomisation in cycles
Randomisation in patient blocks
Graphical presentation of results
Trellis plots
Dot plots
Causal analysis
Analysis of variance
Block structure and the Wilkinson & Roger notation
Main effect models
Allowing for interaction
Summary measures approaches
Mixed models
Estimation
Best linear unbiased predictors (shrunk estimates)
N of 1 trials are trials in which individual patients are repeatedly treated with experimental and control treatments in a deliberate and designed manner using principles of control, randomisation and replication. Their uses include personalising treatment and increasing efficiency by reducing the number of patients it is necessary to study.
In chronic diseases, sets of n-of-1 trials (in which a limited number of patients follow an n-of-1 protocol) have great potential as phase IV trials for understanding components of variation but may also constitute possible Phase III programmes for rare diseases. They can also be used as phase II studies for proof of concept and dose-finding. However, they are often poorly analysed and, indeed, much of the published advice is poor.
This course will present the latest thinking on n-of-1 trials and cover not only their analysis through SAS®, R® GenStat® and meta-analysis packages but also approaches to design. They will also be critically examined as to their potential use in a) establishing average effects of treatment b) studying the extent to which such effects vary from patient to patient and c) optimising treatment for individual patients.
Course leader
This course will be given by Professor Stephen Senn, of the Luxembourg Institute of Health, who is well- known for his work on the design and analysis of clinical trials and the application of statistics in drug development.
Topics covered
Uses of n-of-1 trials and purposes of analysis
Showing the treatment can work
Understanding variation in effect
Predicting effects
Design
Randomisation in cycles
Randomisation in patient blocks
Graphical presentation of results
Trellis plots
Dot plots
Causal analysis
Analysis of variance
Block structure and the Wilkinson & Roger notation
Main effect models
Allowing for interaction
Summary measures approaches
Mixed models
Estimation
Best linear unbiased predictors (shrunk estimates)
N of 1 trials are trials in which individual patients are repeatedly treated with experimental and control treatments in a deliberate and designed manner using principles of control, randomisation and replication. Their uses include personalising treatment and increasing efficiency by reducing the number of patients it is necessary to study.
In chronic diseases, sets of n-of-1 trials (in which a limited number of patients follow an n-of-1 protocol) have great potential as phase IV trials for understanding components of variation but may also constitute possible Phase III programmes for rare diseases. They can also be used as phase II studies for proof of concept and dose-finding. However, they are often poorly analysed and, indeed, much of the published advice is poor.
This course will present the latest thinking on n-of-1 trials and cover not only their analysis through SAS®, R® GenStat® and meta-analysis packages but also approaches to design. They will also be critically examined as to their potential use in a) establishing average effects of treatment b) studying the extent to which such effects vary from patient to patient and c) optimising treatment for individual patients.
Course leader
This course will be given by Professor Stephen Senn, of the Luxembourg Institute of Health, who is well- known for his work on the design and analysis of clinical trials and the application of statistics in drug development.
Topics covered
Uses of n-of-1 trials and purposes of analysis
Showing the treatment can work
Understanding variation in effect
Predicting effects
Design
Randomisation in cycles
Randomisation in patient blocks
Graphical presentation of results
Trellis plots
Dot plots
Causal analysis
Analysis of variance
Block structure and the Wilkinson & Roger notation
Main effect models
Allowing for interaction
Summary measures approaches
Mixed models
Estimation
Best linear unbiased predictors (shrunk estimates)
N of 1 trials are trials in which individual patients are repeatedly treated with experimental and control treatments in a deliberate and designed manner using principles of control, randomisation and replication. Their uses include personalising treatment and increasing efficiency by reducing the number of patients it is necessary to study.
In chronic diseases, sets of n-of-1 trials (in which a limited number of patients follow an n-of-1 protocol) have great potential as phase IV trials for understanding components of variation but may also constitute possible Phase III programmes for rare diseases. They can also be used as phase II studies for proof of concept and dose-finding. However, they are often poorly analysed and, indeed, much of the published advice is poor.
This course will present the latest thinking on n-of-1 trials and cover not only their analysis through SAS®, R® GenStat® and meta-analysis packages but also approaches to design. They will also be critically examined as to their potential use in a) establishing average effects of treatment b) studying the extent to which such effects vary from patient to patient and c) optimising treatment for individual patients.
Course leader
This course will be given by Professor Stephen Senn, of the Luxembourg Institute of Health, who is well- known for his work on the design and analysis of clinical trials and the application of statistics in drug development.
Topics covered
Uses of n-of-1 trials and purposes of analysis
Showing the treatment can work
Understanding variation in effect
Predicting effects
Design
Randomisation in cycles
Randomisation in patient blocks
Graphical presentation of results
Trellis plots
Dot plots
Causal analysis
Analysis of variance
Block structure and the Wilkinson & Roger notation
Main effect models
Allowing for interaction
Summary measures approaches
Mixed models
Estimation
Best linear unbiased predictors (shrunk estimates)
N of 1 trials are trials in which individual patients are repeatedly treated with experimental and control treatments in a deliberate and designed manner using principles of control, randomisation and replication. Their uses include personalising treatment and increasing efficiency by reducing the number of patients it is necessary to study.
In chronic diseases, sets of n-of-1 trials (in which a limited number of patients follow an n-of-1 protocol) have great potential as phase IV trials for understanding components of variation but may also constitute possible Phase III programmes for rare diseases. They can also be used as phase II studies for proof of concept and dose-finding. However, they are often poorly analysed and, indeed, much of the published advice is poor.
This course will present the latest thinking on n-of-1 trials and cover not only their analysis through SAS®, R® GenStat® and meta-analysis packages but also approaches to design. They will also be critically examined as to their potential use in a) establishing average effects of treatment b) studying the extent to which such effects vary from patient to patient and c) optimising treatment for individual patients.
Course leader
This course will be given by Professor Stephen Senn, of the Luxembourg Institute of Health, who is well- known for his work on the design and analysis of clinical trials and the application of statistics in drug development.
Topics covered
Uses of n-of-1 trials and purposes of analysis
Showing the treatment can work
Understanding variation in effect
Predicting effects
Design
Randomisation in cycles
Randomisation in patient blocks
Graphical presentation of results
Trellis plots
Dot plots
Causal analysis
Analysis of variance
Block structure and the Wilkinson & Roger notation
Main effect models
Allowing for interaction
Summary measures approaches
Mixed models
Estimation
Best linear unbiased predictors (shrunk estimates)
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.
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.
PSI Webinar: Methodology and first results of the iRISE (improving Reproducibility In SciencE) consortium
This 1-hour webinar will be an opportunity to hear about the methodology and first results of the iRISE consortium. iRISE is working towards a better understanding of reproducibility and the interventions that work to improve it. At the end of the presentation there will also be the opportunity to ask questions.
One-day Event: Change Management for Moving to R/Open-Source
This one-day event focuses on the comprehensive management of transitioning to R/Open-Source, addressing the challenges and providing actionable insights. Attendees will participate in sessions covering essential topics such as training best practices, creating strategic plans, making the case to senior management, and managing both statistical and programming aspects of the transition.
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.
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.
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.
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.