Date: Monday 14th March - Thursday 7th April 2022
Time: Main sessions 10:00-12:00 GMT & Drop-in sessions 10:00-11:00
Please note: This course runs over set dates and has some slight variations in timings. Please refer below for further detail.
Speaker: Matt Neilson (Phastar)
Who is this event intended for? This course is aimed at statisticians who have experience of R and the tidyverse and would like to learn how to use the tidyverse to simulate clinical trials to evaluate the design and operating characteristics.
What is the benefit of attending? Attendees will have the chance to cover; Monte Carlo simulation, multivariate sampling, model fitting, power analysis, parallelisation, and data visualisation.
This course has early bird rates available, which are applicable for registrations made before 17:00 GMT on Friday 11th February.
Early Bird Members = £320+VAT
Early Bird Non-Members = £445*+VAT
Regular Members = £360+VAT
Regular Non-Members = £485*+VAT
*Please note: Non-Member rates include PSI membership until 31 Dec. 2022.
To book your space, please click here.
In this course, we introduce a framework for clinical trial simulations that makes extensive use of the tidyverse collection of R packages. The course is punctuated with real-world case studies that demonstrate the versatility of the framework, and the relative ease with which it can be applied in practice. The case studies will cover:
• Assurance
• Go/No-go decisions
• Power comparisons
• Count, binary and time to event endpoints
• Censored data
• Recurrent events
Pre-requisites: Participants must have some experience in R, in particular be familiar with writing simple functions and have experience of the tidyverse (dplyr: using the pipe operator, using mutate, group_by, select and filter). Participants who are not experienced with the tidyverse should familiarise themselves with the dplyr cheatsheet on R Studio website: (see “Data transformation with dplyr cheatsheet”, on https://www.rstudio.com/resources/cheatsheets/).
All sessions will be run online via Zoom.
Main presentation sessions:
Session 1 - Monday 14th March, 09:30-12:30 GMT
Session 2 - Monday 21st March, 10:00-12:00 GMT
Session 3 - Monday 28th March, 10:00-12:00 BST*
Session 4 - Monday 4th April, 10:00-12:00 BST*
Drop-in sessions:
Drop-in Session 1 - Thursday 17th March, 11:30-12:30 GMT
Drop-in Session 2 - Thursday 24th March, 10:00-11:00 GMT
Drop-in Session 3 - Thursday 31st March, 10:00-11:00 BST*
Drop-in Session 4 - Thursday 7th April, 10:00-11:00 BST*
*Please be advised: timings switch to British Summer Time (BST) on the 27th March.
|
Speaker |
Biography |
|
|
Matt Neilson entered the field of medical research in 2008, after obtaining his PhD in Mathematics from the University of Strathclyde. Following a two-year postdoc at the Health Economics and Health Technology Assessment group at the University of Glasgow, Matt spent eight years providing mathematical and statistical support to preclinical researchers as part of the core Computational Biology unit at the Beatson Institute for Cancer Research UK. Matt joined PHASTAR as a Senior Statistician in September 2021. |
Disclaimer
PSI is a non-profit organisation run by volunteers. Many of the event organisers and presenters donate their time, while the majority of the event registration cost is spent on administrative support, venue rental / online conferencing, travel costs for the presenter, software licences, and general running of the society. PSI strives to offer high quality courses, but cannot offer a guarantee that the content presented is accurate or fit for your particular needs. Please check if any software is required for this course and ensure you are able to run it prior to registering.
Cancellation and Moderation Terms
For cancellations received up to two weeks prior to a PSI event start-date, the event registration fee will be refunded less 25% administrative charge. After this date, no refunds will be possible. A handling fee of 20 GBP per registration will be charged for every registration modification received two weeks prior or less, including a delegate name change.
Date: Monday 14th March - Thursday 7th April 2022
Time: Main sessions 10:00-12:00 GMT & Drop-in sessions 10:00-11:00
Please note: This course runs over set dates and has some slight variations in timings. Please refer below for further detail.
Speaker: Matt Neilson (Phastar)
Who is this event intended for? This course is aimed at statisticians who have experience of R and the tidyverse and would like to learn how to use the tidyverse to simulate clinical trials to evaluate the design and operating characteristics.
What is the benefit of attending? Attendees will have the chance to cover; Monte Carlo simulation, multivariate sampling, model fitting, power analysis, parallelisation, and data visualisation.
This course has early bird rates available, which are applicable for registrations made before 17:00 GMT on Friday 11th February.
Early Bird Members = £320+VAT
Early Bird Non-Members = £445*+VAT
Regular Members = £360+VAT
Regular Non-Members = £485*+VAT
*Please note: Non-Member rates include PSI membership until 31 Dec. 2022.
To book your space, please click here.
In this course, we introduce a framework for clinical trial simulations that makes extensive use of the tidyverse collection of R packages. The course is punctuated with real-world case studies that demonstrate the versatility of the framework, and the relative ease with which it can be applied in practice. The case studies will cover:
• Assurance
• Go/No-go decisions
• Power comparisons
• Count, binary and time to event endpoints
• Censored data
• Recurrent events
Pre-requisites: Participants must have some experience in R, in particular be familiar with writing simple functions and have experience of the tidyverse (dplyr: using the pipe operator, using mutate, group_by, select and filter). Participants who are not experienced with the tidyverse should familiarise themselves with the dplyr cheatsheet on R Studio website: (see “Data transformation with dplyr cheatsheet”, on https://www.rstudio.com/resources/cheatsheets/).
All sessions will be run online via Zoom.
Main presentation sessions:
Session 1 - Monday 14th March, 09:30-12:30 GMT
Session 2 - Monday 21st March, 10:00-12:00 GMT
Session 3 - Monday 28th March, 10:00-12:00 BST*
Session 4 - Monday 4th April, 10:00-12:00 BST*
Drop-in sessions:
Drop-in Session 1 - Thursday 17th March, 11:30-12:30 GMT
Drop-in Session 2 - Thursday 24th March, 10:00-11:00 GMT
Drop-in Session 3 - Thursday 31st March, 10:00-11:00 BST*
Drop-in Session 4 - Thursday 7th April, 10:00-11:00 BST*
*Please be advised: timings switch to British Summer Time (BST) on the 27th March.
|
Speaker |
Biography |
|
|
Matt Neilson entered the field of medical research in 2008, after obtaining his PhD in Mathematics from the University of Strathclyde. Following a two-year postdoc at the Health Economics and Health Technology Assessment group at the University of Glasgow, Matt spent eight years providing mathematical and statistical support to preclinical researchers as part of the core Computational Biology unit at the Beatson Institute for Cancer Research UK. Matt joined PHASTAR as a Senior Statistician in September 2021. |
Disclaimer
PSI is a non-profit organisation run by volunteers. Many of the event organisers and presenters donate their time, while the majority of the event registration cost is spent on administrative support, venue rental / online conferencing, travel costs for the presenter, software licences, and general running of the society. PSI strives to offer high quality courses, but cannot offer a guarantee that the content presented is accurate or fit for your particular needs. Please check if any software is required for this course and ensure you are able to run it prior to registering.
Cancellation and Moderation Terms
For cancellations received up to two weeks prior to a PSI event start-date, the event registration fee will be refunded less 25% administrative charge. After this date, no refunds will be possible. A handling fee of 20 GBP per registration will be charged for every registration modification received two weeks prior or less, including a delegate name change.
Date: Monday 14th March - Thursday 7th April 2022
Time: Main sessions 10:00-12:00 GMT & Drop-in sessions 10:00-11:00
Please note: This course runs over set dates and has some slight variations in timings. Please refer below for further detail.
Speaker: Matt Neilson (Phastar)
Who is this event intended for? This course is aimed at statisticians who have experience of R and the tidyverse and would like to learn how to use the tidyverse to simulate clinical trials to evaluate the design and operating characteristics.
What is the benefit of attending? Attendees will have the chance to cover; Monte Carlo simulation, multivariate sampling, model fitting, power analysis, parallelisation, and data visualisation.
This course has early bird rates available, which are applicable for registrations made before 17:00 GMT on Friday 11th February.
Early Bird Members = £320+VAT
Early Bird Non-Members = £445*+VAT
Regular Members = £360+VAT
Regular Non-Members = £485*+VAT
*Please note: Non-Member rates include PSI membership until 31 Dec. 2022.
To book your space, please click here.
In this course, we introduce a framework for clinical trial simulations that makes extensive use of the tidyverse collection of R packages. The course is punctuated with real-world case studies that demonstrate the versatility of the framework, and the relative ease with which it can be applied in practice. The case studies will cover:
• Assurance
• Go/No-go decisions
• Power comparisons
• Count, binary and time to event endpoints
• Censored data
• Recurrent events
Pre-requisites: Participants must have some experience in R, in particular be familiar with writing simple functions and have experience of the tidyverse (dplyr: using the pipe operator, using mutate, group_by, select and filter). Participants who are not experienced with the tidyverse should familiarise themselves with the dplyr cheatsheet on R Studio website: (see “Data transformation with dplyr cheatsheet”, on https://www.rstudio.com/resources/cheatsheets/).
All sessions will be run online via Zoom.
Main presentation sessions:
Session 1 - Monday 14th March, 09:30-12:30 GMT
Session 2 - Monday 21st March, 10:00-12:00 GMT
Session 3 - Monday 28th March, 10:00-12:00 BST*
Session 4 - Monday 4th April, 10:00-12:00 BST*
Drop-in sessions:
Drop-in Session 1 - Thursday 17th March, 11:30-12:30 GMT
Drop-in Session 2 - Thursday 24th March, 10:00-11:00 GMT
Drop-in Session 3 - Thursday 31st March, 10:00-11:00 BST*
Drop-in Session 4 - Thursday 7th April, 10:00-11:00 BST*
*Please be advised: timings switch to British Summer Time (BST) on the 27th March.
|
Speaker |
Biography |
|
|
Matt Neilson entered the field of medical research in 2008, after obtaining his PhD in Mathematics from the University of Strathclyde. Following a two-year postdoc at the Health Economics and Health Technology Assessment group at the University of Glasgow, Matt spent eight years providing mathematical and statistical support to preclinical researchers as part of the core Computational Biology unit at the Beatson Institute for Cancer Research UK. Matt joined PHASTAR as a Senior Statistician in September 2021. |
Disclaimer
PSI is a non-profit organisation run by volunteers. Many of the event organisers and presenters donate their time, while the majority of the event registration cost is spent on administrative support, venue rental / online conferencing, travel costs for the presenter, software licences, and general running of the society. PSI strives to offer high quality courses, but cannot offer a guarantee that the content presented is accurate or fit for your particular needs. Please check if any software is required for this course and ensure you are able to run it prior to registering.
Cancellation and Moderation Terms
For cancellations received up to two weeks prior to a PSI event start-date, the event registration fee will be refunded less 25% administrative charge. After this date, no refunds will be possible. A handling fee of 20 GBP per registration will be charged for every registration modification received two weeks prior or less, including a delegate name change.
Date: Monday 14th March - Thursday 7th April 2022
Time: Main sessions 10:00-12:00 GMT & Drop-in sessions 10:00-11:00
Please note: This course runs over set dates and has some slight variations in timings. Please refer below for further detail.
Speaker: Matt Neilson (Phastar)
Who is this event intended for? This course is aimed at statisticians who have experience of R and the tidyverse and would like to learn how to use the tidyverse to simulate clinical trials to evaluate the design and operating characteristics.
What is the benefit of attending? Attendees will have the chance to cover; Monte Carlo simulation, multivariate sampling, model fitting, power analysis, parallelisation, and data visualisation.
This course has early bird rates available, which are applicable for registrations made before 17:00 GMT on Friday 11th February.
Early Bird Members = £320+VAT
Early Bird Non-Members = £445*+VAT
Regular Members = £360+VAT
Regular Non-Members = £485*+VAT
*Please note: Non-Member rates include PSI membership until 31 Dec. 2022.
To book your space, please click here.
In this course, we introduce a framework for clinical trial simulations that makes extensive use of the tidyverse collection of R packages. The course is punctuated with real-world case studies that demonstrate the versatility of the framework, and the relative ease with which it can be applied in practice. The case studies will cover:
• Assurance
• Go/No-go decisions
• Power comparisons
• Count, binary and time to event endpoints
• Censored data
• Recurrent events
Pre-requisites: Participants must have some experience in R, in particular be familiar with writing simple functions and have experience of the tidyverse (dplyr: using the pipe operator, using mutate, group_by, select and filter). Participants who are not experienced with the tidyverse should familiarise themselves with the dplyr cheatsheet on R Studio website: (see “Data transformation with dplyr cheatsheet”, on https://www.rstudio.com/resources/cheatsheets/).
All sessions will be run online via Zoom.
Main presentation sessions:
Session 1 - Monday 14th March, 09:30-12:30 GMT
Session 2 - Monday 21st March, 10:00-12:00 GMT
Session 3 - Monday 28th March, 10:00-12:00 BST*
Session 4 - Monday 4th April, 10:00-12:00 BST*
Drop-in sessions:
Drop-in Session 1 - Thursday 17th March, 11:30-12:30 GMT
Drop-in Session 2 - Thursday 24th March, 10:00-11:00 GMT
Drop-in Session 3 - Thursday 31st March, 10:00-11:00 BST*
Drop-in Session 4 - Thursday 7th April, 10:00-11:00 BST*
*Please be advised: timings switch to British Summer Time (BST) on the 27th March.
|
Speaker |
Biography |
|
|
Matt Neilson entered the field of medical research in 2008, after obtaining his PhD in Mathematics from the University of Strathclyde. Following a two-year postdoc at the Health Economics and Health Technology Assessment group at the University of Glasgow, Matt spent eight years providing mathematical and statistical support to preclinical researchers as part of the core Computational Biology unit at the Beatson Institute for Cancer Research UK. Matt joined PHASTAR as a Senior Statistician in September 2021. |
Disclaimer
PSI is a non-profit organisation run by volunteers. Many of the event organisers and presenters donate their time, while the majority of the event registration cost is spent on administrative support, venue rental / online conferencing, travel costs for the presenter, software licences, and general running of the society. PSI strives to offer high quality courses, but cannot offer a guarantee that the content presented is accurate or fit for your particular needs. Please check if any software is required for this course and ensure you are able to run it prior to registering.
Cancellation and Moderation Terms
For cancellations received up to two weeks prior to a PSI event start-date, the event registration fee will be refunded less 25% administrative charge. After this date, no refunds will be possible. A handling fee of 20 GBP per registration will be charged for every registration modification received two weeks prior or less, including a delegate name change.
Date: Monday 14th March - Thursday 7th April 2022
Time: Main sessions 10:00-12:00 GMT & Drop-in sessions 10:00-11:00
Please note: This course runs over set dates and has some slight variations in timings. Please refer below for further detail.
Speaker: Matt Neilson (Phastar)
Who is this event intended for? This course is aimed at statisticians who have experience of R and the tidyverse and would like to learn how to use the tidyverse to simulate clinical trials to evaluate the design and operating characteristics.
What is the benefit of attending? Attendees will have the chance to cover; Monte Carlo simulation, multivariate sampling, model fitting, power analysis, parallelisation, and data visualisation.
This course has early bird rates available, which are applicable for registrations made before 17:00 GMT on Friday 11th February.
Early Bird Members = £320+VAT
Early Bird Non-Members = £445*+VAT
Regular Members = £360+VAT
Regular Non-Members = £485*+VAT
*Please note: Non-Member rates include PSI membership until 31 Dec. 2022.
To book your space, please click here.
In this course, we introduce a framework for clinical trial simulations that makes extensive use of the tidyverse collection of R packages. The course is punctuated with real-world case studies that demonstrate the versatility of the framework, and the relative ease with which it can be applied in practice. The case studies will cover:
• Assurance
• Go/No-go decisions
• Power comparisons
• Count, binary and time to event endpoints
• Censored data
• Recurrent events
Pre-requisites: Participants must have some experience in R, in particular be familiar with writing simple functions and have experience of the tidyverse (dplyr: using the pipe operator, using mutate, group_by, select and filter). Participants who are not experienced with the tidyverse should familiarise themselves with the dplyr cheatsheet on R Studio website: (see “Data transformation with dplyr cheatsheet”, on https://www.rstudio.com/resources/cheatsheets/).
All sessions will be run online via Zoom.
Main presentation sessions:
Session 1 - Monday 14th March, 09:30-12:30 GMT
Session 2 - Monday 21st March, 10:00-12:00 GMT
Session 3 - Monday 28th March, 10:00-12:00 BST*
Session 4 - Monday 4th April, 10:00-12:00 BST*
Drop-in sessions:
Drop-in Session 1 - Thursday 17th March, 11:30-12:30 GMT
Drop-in Session 2 - Thursday 24th March, 10:00-11:00 GMT
Drop-in Session 3 - Thursday 31st March, 10:00-11:00 BST*
Drop-in Session 4 - Thursday 7th April, 10:00-11:00 BST*
*Please be advised: timings switch to British Summer Time (BST) on the 27th March.
|
Speaker |
Biography |
|
|
Matt Neilson entered the field of medical research in 2008, after obtaining his PhD in Mathematics from the University of Strathclyde. Following a two-year postdoc at the Health Economics and Health Technology Assessment group at the University of Glasgow, Matt spent eight years providing mathematical and statistical support to preclinical researchers as part of the core Computational Biology unit at the Beatson Institute for Cancer Research UK. Matt joined PHASTAR as a Senior Statistician in September 2021. |
Disclaimer
PSI is a non-profit organisation run by volunteers. Many of the event organisers and presenters donate their time, while the majority of the event registration cost is spent on administrative support, venue rental / online conferencing, travel costs for the presenter, software licences, and general running of the society. PSI strives to offer high quality courses, but cannot offer a guarantee that the content presented is accurate or fit for your particular needs. Please check if any software is required for this course and ensure you are able to run it prior to registering.
Cancellation and Moderation Terms
For cancellations received up to two weeks prior to a PSI event start-date, the event registration fee will be refunded less 25% administrative charge. After this date, no refunds will be possible. A handling fee of 20 GBP per registration will be charged for every registration modification received two weeks prior or less, including a delegate name change.
Date: Monday 14th March - Thursday 7th April 2022
Time: Main sessions 10:00-12:00 GMT & Drop-in sessions 10:00-11:00
Please note: This course runs over set dates and has some slight variations in timings. Please refer below for further detail.
Speaker: Matt Neilson (Phastar)
Who is this event intended for? This course is aimed at statisticians who have experience of R and the tidyverse and would like to learn how to use the tidyverse to simulate clinical trials to evaluate the design and operating characteristics.
What is the benefit of attending? Attendees will have the chance to cover; Monte Carlo simulation, multivariate sampling, model fitting, power analysis, parallelisation, and data visualisation.
This course has early bird rates available, which are applicable for registrations made before 17:00 GMT on Friday 11th February.
Early Bird Members = £320+VAT
Early Bird Non-Members = £445*+VAT
Regular Members = £360+VAT
Regular Non-Members = £485*+VAT
*Please note: Non-Member rates include PSI membership until 31 Dec. 2022.
To book your space, please click here.
In this course, we introduce a framework for clinical trial simulations that makes extensive use of the tidyverse collection of R packages. The course is punctuated with real-world case studies that demonstrate the versatility of the framework, and the relative ease with which it can be applied in practice. The case studies will cover:
• Assurance
• Go/No-go decisions
• Power comparisons
• Count, binary and time to event endpoints
• Censored data
• Recurrent events
Pre-requisites: Participants must have some experience in R, in particular be familiar with writing simple functions and have experience of the tidyverse (dplyr: using the pipe operator, using mutate, group_by, select and filter). Participants who are not experienced with the tidyverse should familiarise themselves with the dplyr cheatsheet on R Studio website: (see “Data transformation with dplyr cheatsheet”, on https://www.rstudio.com/resources/cheatsheets/).
All sessions will be run online via Zoom.
Main presentation sessions:
Session 1 - Monday 14th March, 09:30-12:30 GMT
Session 2 - Monday 21st March, 10:00-12:00 GMT
Session 3 - Monday 28th March, 10:00-12:00 BST*
Session 4 - Monday 4th April, 10:00-12:00 BST*
Drop-in sessions:
Drop-in Session 1 - Thursday 17th March, 11:30-12:30 GMT
Drop-in Session 2 - Thursday 24th March, 10:00-11:00 GMT
Drop-in Session 3 - Thursday 31st March, 10:00-11:00 BST*
Drop-in Session 4 - Thursday 7th April, 10:00-11:00 BST*
*Please be advised: timings switch to British Summer Time (BST) on the 27th March.
|
Speaker |
Biography |
|
|
Matt Neilson entered the field of medical research in 2008, after obtaining his PhD in Mathematics from the University of Strathclyde. Following a two-year postdoc at the Health Economics and Health Technology Assessment group at the University of Glasgow, Matt spent eight years providing mathematical and statistical support to preclinical researchers as part of the core Computational Biology unit at the Beatson Institute for Cancer Research UK. Matt joined PHASTAR as a Senior Statistician in September 2021. |
Disclaimer
PSI is a non-profit organisation run by volunteers. Many of the event organisers and presenters donate their time, while the majority of the event registration cost is spent on administrative support, venue rental / online conferencing, travel costs for the presenter, software licences, and general running of the society. PSI strives to offer high quality courses, but cannot offer a guarantee that the content presented is accurate or fit for your particular needs. Please check if any software is required for this course and ensure you are able to run it prior to registering.
Cancellation and Moderation Terms
For cancellations received up to two weeks prior to a PSI event start-date, the event registration fee will be refunded less 25% administrative charge. After this date, no refunds will be possible. A handling fee of 20 GBP per registration will be charged for every registration modification received two weeks prior or less, including a delegate name change.
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.
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.
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.
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.
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.
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).
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.
Date: Wednesday 5th November 2025 A careers talk about medical statistics and how it plays a crucial role in developing new medicines
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.
This networking event is aimed at statisticians that are new to the pharmaceutical industry who wish to meet colleagues from different companies and backgrounds.
As an Associate Director Biostatistics Early Development, you will be a key member of our biostatistics group, you will play a crucial role in the design, analysis, and interpretation of clinical trials for early development programs.
If you are passionate about biostatistics and real-world data, and are looking for an exciting opportunity to contribute to groundbreaking research, we encourage you to apply.
Are you passionate about making a difference in the world of healthcare? Novartis is seeking a dynamic and experienced professional to join our team in London at The Westworks.
As the Director of HTA Biostatistics & Medical Affairs, you will play a pivotal role in shaping the future of healthcare by providing strategic biostatistical leadership and expertise.
As a Senior Principal Biostatistician, you will be responsible and accountable for all statistical work, both scientific and operational, for one or more assigned clinical trials
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Contains a unique identifier used by Google Analytics 4 to determine that two distinct hits belong to the same user across browsing sessions. | |||
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Contains a unique identifier used by Google Analytics to determine that two distinct hits belong to the same user across browsing sessions. | |||
