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.
PSI Introduction to Industry Training (ITIT) Course - 2024/2025
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.
PSI Training Course: Mixed Models and Repeated Measures
This course is presented through lectures and practical sessions using SAS code. It is suitable for statisticians working on clinical trials, who already have a good understanding of linear and generalised linear models.
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 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.
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