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)
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.
Topic: R Package Basics.
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. This month’s session, “R Package Basics,” will introduce the fundamentals of working with R packages—covering how to install, load, and manage them effectively to support data analysis and reproducible research. The session will provide a solid starting point, clarify common misconceptions, and offer valuable resources for continued learning.
Date: Ongoing 6 month cycle beginning late April/early May 2026
Are you a member of PSI looking to further your career or help develop others - why not sign up to the PSI Mentoring scheme? You can expand your network, improve your leadership skills and learn from more senior colleagues in the industry.
PSI Book Club Lunch and Learn: Communicating with Clarity and Confidence
If you have read Ros Atkins’ book The Art of Explanation or want to listen to the BBC’s ‘Communicator in Chief’, you are invited to join the PSI Book Club Lunch and Learn, to discuss the content and application with the author, Ros Atkins. Having written the book within the context of the news industry, Ros is keen to hear how we have applied the ideas as statisticians within drug development and clinical trials. There will be dedicated time during the webinar to ASK THE AUTHOR any questions – don’t miss out on this exclusive PSI Book Club event!
Haven’t read the book yet? Pick up a copy today and join us.
Explanation - identifying and communicating what we want to say - is described as an art, in the title of his book. However, the creativity comes from Ros’ discernment in identifying and describing a clear step-by-step process to follow and practice. Readers can learn Ros’ rules, developed and polished throughout his career as a journalist, to help communicate complex written or spoken information clearly.
PSI Training Course: Effective Leadership – the keys to growing your leadership capabilities
This course will consist of three online half-day workshops. The first will be aimed at building trust, the backbone of leadership and a key to becoming effective. This is key to building a solid foundation.
The second will be on improving communication as a technical leader. This workshop will focus on communication strategies for different stakeholders and will involve tips on effective communication and how to develop the skills of active listening, coaching and what improv can teach us about good communication.
The final workshop will bring these two components together to help leaders become more influential. This will also focus on how to use Steven Covey’s 7-Habits, in particular Habits 4, 5 and 6, which are called the habits of communication.
The workshops will be interactive, allowing you to practice the concepts discussed. There will be plenty of time for questions and discussion. There will also be reflective time where you can think about what you are learning and how you might experiment with it.