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.
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.
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.
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.
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.
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.
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.
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.
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.
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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. | |||
