PSI Webinar: Open Source Software - is it really a free-for-all?

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.

AIMS SIG - Open-Source Lunch Bites

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.

PSI Mentoring 2026

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.

Speaker	Biography	Abstract
Matthew Lyon	Matt Lyon studied his Zoology BSc at the University of Liverpool. His degree included quantitative biology modules which used several statistical data packages. He started his career at The Francis Crick Institute in London as an Animal Technician before progressing to CRUK Manchester and finally moved to AstraZeneca in 2020 as an In-Vivo Scientist. Matt is currently the Global Head and his departments’ representative for Inclusion and Diversity (I&D).He also heads up a small, international cross functional team which focusses on creating and rolling out initiatives across the department. This also includes liaising with other areas of the business to promote AZ as a great place to work. Matt has taken over the Lead of the Steering Committee of the community of R users at AstraZeneca- ‘R@AZ’ – which currently has around 1600 members. Building on his I&D and quantitative biology skills, he is looking at expanding this community within AZ and beyond.	Building a BiggeR Community of R Users at AstraZeneca In the past years, the pharma industry has seen a true paradigm shift in its use of R. Up until recently, one had to choose between R and SAS. Today, most collaborators with a quantitative background are trained in at least 2 programming languages. With this in mind, at AstraZeneca we built on the growing interest for R, at any stage of the drug development but also company-wide. Since April 2021 we have launched a variety of initiatives, initially starting with a modified public initiative #azTidyTuesday and Function of the month. As the community grew, we launched our first AZ Conference, #AZRC2022 and this is now run on an annual basis. Throughout 2022, we have added a variety of initiatives to bring people together including: Lunch & LeaRn, AZ R Hot Desk and in 2023 we formed AZ R-Ladies. In early 2022, the R@AZ Leads were asked 3 questions: 1. What is the value of your community? 2. What is a Key Performance Indicator (KPI) of your community? 3. What is the Return On Investment (ROI) of your community? Prior to 2023, there were no definitive answers but whilst building this community internally, we have reached out and collaborated with external partners across the data science industry. In response, they have kindly provided us with educational and informative speakers for internal community events and continue to do so as we plan for 2024. The combination of all these initiatives, derived from the growth and passion of the steering committee, has led to an 800% increase in the internal social media community members; actively representing over 200 different departments with AstraZeneca. This is now highlighting the value, its KPI and ROI over 3 years in the making by building a network and a community.
Ari Siggaard Knoph	Ari is a Principal Statistical Programmer and International Lead Programmer at Novo Nordisk with a seat on the pharmaverse council. He is a driving force behind the adoption of R in clinical deliverables and submissions at Novo Nordisk. Ari is also the author and maintainer of multiple R packages used in the Novo Nordisk ecosystem.	Completing a submission and beyond in R In this presentation we will pull out some touch points of the Q&A phase of our first R-based submission. Examples of FDA interactions will be discussed and our thoughts on how to continuously manage a possibly drifting R environment in a submission will be shared.
Daniel Sabanes-Bove	Daniel Sabanes Bove studied Statistics in LMU Munich and obtained his PhD at the University of Zurich for his research work on Bayesian model selection. He started his career in 2013 at Roche as a biostatistician, then worked at Google as a data scientist from 2018 to 2020 before rejoining Roche. He currently leads the Statistical Engineering team in Roche Pharma Product Development that works on productionizing R packages, Shiny modules and how-to templates for data scientists. Daniel is co-author of multiple R packages published on CRAN and Bioconductor, as well as the book "Likelihood and Bayesian Inference: With Applications in Biology and Medicine", and is currently openstatsware.org (ASA BIOP working group on Software Engineering).	R(omeo) and Julia - A Love Story by openstatsware For implementing statistical methods in software, we recently started trying out the Julia language. "Julia is a high-level, general-purpose dynamic programming language, most commonly used for numerical analysis and computational science" (Wikipedia) and as such well suited for statistical applications. I will introduce two successful Julia projects. The first project implements joint models for time-to-event and longitudinal outcomes (see e.g. Kerioui et al. 2022), and is available open source as JointModels.jl. It uses Turing.jl for MCMC based Bayesian inference, based on a new distribution class for time-to-event data specified via hazard functions. The second project implements Bayesian safety signal detection as described by Brock et al. (2022), under construction and open source as SafetySignalDetection.jl, again using Turing.jl and with a suitable extension of the expectation-maximization algorithm for fitting Beta mixtures. I will discuss the reasons why these projects were successful, and describe how we could easily embed the Julia algorithms into an R based overall workflow. Finally, I will introduce openstatsware.org where a growing community of statistical software engineers comes together to build software packages and develop and share best practices for such.

Speaker	Biography	Abstract
Matthew Lyon	Matt Lyon studied his Zoology BSc at the University of Liverpool. His degree included quantitative biology modules which used several statistical data packages. He started his career at The Francis Crick Institute in London as an Animal Technician before progressing to CRUK Manchester and finally moved to AstraZeneca in 2020 as an In-Vivo Scientist. Matt is currently the Global Head and his departments’ representative for Inclusion and Diversity (I&D).He also heads up a small, international cross functional team which focusses on creating and rolling out initiatives across the department. This also includes liaising with other areas of the business to promote AZ as a great place to work. Matt has taken over the Lead of the Steering Committee of the community of R users at AstraZeneca- ‘R@AZ’ – which currently has around 1600 members. Building on his I&D and quantitative biology skills, he is looking at expanding this community within AZ and beyond.	Building a BiggeR Community of R Users at AstraZeneca In the past years, the pharma industry has seen a true paradigm shift in its use of R. Up until recently, one had to choose between R and SAS. Today, most collaborators with a quantitative background are trained in at least 2 programming languages. With this in mind, at AstraZeneca we built on the growing interest for R, at any stage of the drug development but also company-wide. Since April 2021 we have launched a variety of initiatives, initially starting with a modified public initiative #azTidyTuesday and Function of the month. As the community grew, we launched our first AZ Conference, #AZRC2022 and this is now run on an annual basis. Throughout 2022, we have added a variety of initiatives to bring people together including: Lunch & LeaRn, AZ R Hot Desk and in 2023 we formed AZ R-Ladies. In early 2022, the R@AZ Leads were asked 3 questions: 1. What is the value of your community? 2. What is a Key Performance Indicator (KPI) of your community? 3. What is the Return On Investment (ROI) of your community? Prior to 2023, there were no definitive answers but whilst building this community internally, we have reached out and collaborated with external partners across the data science industry. In response, they have kindly provided us with educational and informative speakers for internal community events and continue to do so as we plan for 2024. The combination of all these initiatives, derived from the growth and passion of the steering committee, has led to an 800% increase in the internal social media community members; actively representing over 200 different departments with AstraZeneca. This is now highlighting the value, its KPI and ROI over 3 years in the making by building a network and a community.
Ari Siggaard Knoph	Ari is a Principal Statistical Programmer and International Lead Programmer at Novo Nordisk with a seat on the pharmaverse council. He is a driving force behind the adoption of R in clinical deliverables and submissions at Novo Nordisk. Ari is also the author and maintainer of multiple R packages used in the Novo Nordisk ecosystem.	Completing a submission and beyond in R In this presentation we will pull out some touch points of the Q&A phase of our first R-based submission. Examples of FDA interactions will be discussed and our thoughts on how to continuously manage a possibly drifting R environment in a submission will be shared.
Daniel Sabanes-Bove	Daniel Sabanes Bove studied Statistics in LMU Munich and obtained his PhD at the University of Zurich for his research work on Bayesian model selection. He started his career in 2013 at Roche as a biostatistician, then worked at Google as a data scientist from 2018 to 2020 before rejoining Roche. He currently leads the Statistical Engineering team in Roche Pharma Product Development that works on productionizing R packages, Shiny modules and how-to templates for data scientists. Daniel is co-author of multiple R packages published on CRAN and Bioconductor, as well as the book "Likelihood and Bayesian Inference: With Applications in Biology and Medicine", and is currently openstatsware.org (ASA BIOP working group on Software Engineering).	R(omeo) and Julia - A Love Story by openstatsware For implementing statistical methods in software, we recently started trying out the Julia language. "Julia is a high-level, general-purpose dynamic programming language, most commonly used for numerical analysis and computational science" (Wikipedia) and as such well suited for statistical applications. I will introduce two successful Julia projects. The first project implements joint models for time-to-event and longitudinal outcomes (see e.g. Kerioui et al. 2022), and is available open source as JointModels.jl. It uses Turing.jl for MCMC based Bayesian inference, based on a new distribution class for time-to-event data specified via hazard functions. The second project implements Bayesian safety signal detection as described by Brock et al. (2022), under construction and open source as SafetySignalDetection.jl, again using Turing.jl and with a suitable extension of the expectation-maximization algorithm for fitting Beta mixtures. I will discuss the reasons why these projects were successful, and describe how we could easily embed the Julia algorithms into an R based overall workflow. Finally, I will introduce openstatsware.org where a growing community of statistical software engineers comes together to build software packages and develop and share best practices for such.

Speaker	Biography	Abstract
Matthew Lyon	Matt Lyon studied his Zoology BSc at the University of Liverpool. His degree included quantitative biology modules which used several statistical data packages. He started his career at The Francis Crick Institute in London as an Animal Technician before progressing to CRUK Manchester and finally moved to AstraZeneca in 2020 as an In-Vivo Scientist. Matt is currently the Global Head and his departments’ representative for Inclusion and Diversity (I&D).He also heads up a small, international cross functional team which focusses on creating and rolling out initiatives across the department. This also includes liaising with other areas of the business to promote AZ as a great place to work. Matt has taken over the Lead of the Steering Committee of the community of R users at AstraZeneca- ‘R@AZ’ – which currently has around 1600 members. Building on his I&D and quantitative biology skills, he is looking at expanding this community within AZ and beyond.	Building a BiggeR Community of R Users at AstraZeneca In the past years, the pharma industry has seen a true paradigm shift in its use of R. Up until recently, one had to choose between R and SAS. Today, most collaborators with a quantitative background are trained in at least 2 programming languages. With this in mind, at AstraZeneca we built on the growing interest for R, at any stage of the drug development but also company-wide. Since April 2021 we have launched a variety of initiatives, initially starting with a modified public initiative #azTidyTuesday and Function of the month. As the community grew, we launched our first AZ Conference, #AZRC2022 and this is now run on an annual basis. Throughout 2022, we have added a variety of initiatives to bring people together including: Lunch & LeaRn, AZ R Hot Desk and in 2023 we formed AZ R-Ladies. In early 2022, the R@AZ Leads were asked 3 questions: 1. What is the value of your community? 2. What is a Key Performance Indicator (KPI) of your community? 3. What is the Return On Investment (ROI) of your community? Prior to 2023, there were no definitive answers but whilst building this community internally, we have reached out and collaborated with external partners across the data science industry. In response, they have kindly provided us with educational and informative speakers for internal community events and continue to do so as we plan for 2024. The combination of all these initiatives, derived from the growth and passion of the steering committee, has led to an 800% increase in the internal social media community members; actively representing over 200 different departments with AstraZeneca. This is now highlighting the value, its KPI and ROI over 3 years in the making by building a network and a community.
Ari Siggaard Knoph	Ari is a Principal Statistical Programmer and International Lead Programmer at Novo Nordisk with a seat on the pharmaverse council. He is a driving force behind the adoption of R in clinical deliverables and submissions at Novo Nordisk. Ari is also the author and maintainer of multiple R packages used in the Novo Nordisk ecosystem.	Completing a submission and beyond in R In this presentation we will pull out some touch points of the Q&A phase of our first R-based submission. Examples of FDA interactions will be discussed and our thoughts on how to continuously manage a possibly drifting R environment in a submission will be shared.
Daniel Sabanes-Bove	Daniel Sabanes Bove studied Statistics in LMU Munich and obtained his PhD at the University of Zurich for his research work on Bayesian model selection. He started his career in 2013 at Roche as a biostatistician, then worked at Google as a data scientist from 2018 to 2020 before rejoining Roche. He currently leads the Statistical Engineering team in Roche Pharma Product Development that works on productionizing R packages, Shiny modules and how-to templates for data scientists. Daniel is co-author of multiple R packages published on CRAN and Bioconductor, as well as the book "Likelihood and Bayesian Inference: With Applications in Biology and Medicine", and is currently openstatsware.org (ASA BIOP working group on Software Engineering).	R(omeo) and Julia - A Love Story by openstatsware For implementing statistical methods in software, we recently started trying out the Julia language. "Julia is a high-level, general-purpose dynamic programming language, most commonly used for numerical analysis and computational science" (Wikipedia) and as such well suited for statistical applications. I will introduce two successful Julia projects. The first project implements joint models for time-to-event and longitudinal outcomes (see e.g. Kerioui et al. 2022), and is available open source as JointModels.jl. It uses Turing.jl for MCMC based Bayesian inference, based on a new distribution class for time-to-event data specified via hazard functions. The second project implements Bayesian safety signal detection as described by Brock et al. (2022), under construction and open source as SafetySignalDetection.jl, again using Turing.jl and with a suitable extension of the expectation-maximization algorithm for fitting Beta mixtures. I will discuss the reasons why these projects were successful, and describe how we could easily embed the Julia algorithms into an R based overall workflow. Finally, I will introduce openstatsware.org where a growing community of statistical software engineers comes together to build software packages and develop and share best practices for such.

Speaker	Biography	Abstract
Matthew Lyon	Matt Lyon studied his Zoology BSc at the University of Liverpool. His degree included quantitative biology modules which used several statistical data packages. He started his career at The Francis Crick Institute in London as an Animal Technician before progressing to CRUK Manchester and finally moved to AstraZeneca in 2020 as an In-Vivo Scientist. Matt is currently the Global Head and his departments’ representative for Inclusion and Diversity (I&D).He also heads up a small, international cross functional team which focusses on creating and rolling out initiatives across the department. This also includes liaising with other areas of the business to promote AZ as a great place to work. Matt has taken over the Lead of the Steering Committee of the community of R users at AstraZeneca- ‘R@AZ’ – which currently has around 1600 members. Building on his I&D and quantitative biology skills, he is looking at expanding this community within AZ and beyond.	Building a BiggeR Community of R Users at AstraZeneca In the past years, the pharma industry has seen a true paradigm shift in its use of R. Up until recently, one had to choose between R and SAS. Today, most collaborators with a quantitative background are trained in at least 2 programming languages. With this in mind, at AstraZeneca we built on the growing interest for R, at any stage of the drug development but also company-wide. Since April 2021 we have launched a variety of initiatives, initially starting with a modified public initiative #azTidyTuesday and Function of the month. As the community grew, we launched our first AZ Conference, #AZRC2022 and this is now run on an annual basis. Throughout 2022, we have added a variety of initiatives to bring people together including: Lunch & LeaRn, AZ R Hot Desk and in 2023 we formed AZ R-Ladies. In early 2022, the R@AZ Leads were asked 3 questions: 1. What is the value of your community? 2. What is a Key Performance Indicator (KPI) of your community? 3. What is the Return On Investment (ROI) of your community? Prior to 2023, there were no definitive answers but whilst building this community internally, we have reached out and collaborated with external partners across the data science industry. In response, they have kindly provided us with educational and informative speakers for internal community events and continue to do so as we plan for 2024. The combination of all these initiatives, derived from the growth and passion of the steering committee, has led to an 800% increase in the internal social media community members; actively representing over 200 different departments with AstraZeneca. This is now highlighting the value, its KPI and ROI over 3 years in the making by building a network and a community.
Ari Siggaard Knoph	Ari is a Principal Statistical Programmer and International Lead Programmer at Novo Nordisk with a seat on the pharmaverse council. He is a driving force behind the adoption of R in clinical deliverables and submissions at Novo Nordisk. Ari is also the author and maintainer of multiple R packages used in the Novo Nordisk ecosystem.	Completing a submission and beyond in R In this presentation we will pull out some touch points of the Q&A phase of our first R-based submission. Examples of FDA interactions will be discussed and our thoughts on how to continuously manage a possibly drifting R environment in a submission will be shared.
Daniel Sabanes-Bove	Daniel Sabanes Bove studied Statistics in LMU Munich and obtained his PhD at the University of Zurich for his research work on Bayesian model selection. He started his career in 2013 at Roche as a biostatistician, then worked at Google as a data scientist from 2018 to 2020 before rejoining Roche. He currently leads the Statistical Engineering team in Roche Pharma Product Development that works on productionizing R packages, Shiny modules and how-to templates for data scientists. Daniel is co-author of multiple R packages published on CRAN and Bioconductor, as well as the book "Likelihood and Bayesian Inference: With Applications in Biology and Medicine", and is currently openstatsware.org (ASA BIOP working group on Software Engineering).	R(omeo) and Julia - A Love Story by openstatsware For implementing statistical methods in software, we recently started trying out the Julia language. "Julia is a high-level, general-purpose dynamic programming language, most commonly used for numerical analysis and computational science" (Wikipedia) and as such well suited for statistical applications. I will introduce two successful Julia projects. The first project implements joint models for time-to-event and longitudinal outcomes (see e.g. Kerioui et al. 2022), and is available open source as JointModels.jl. It uses Turing.jl for MCMC based Bayesian inference, based on a new distribution class for time-to-event data specified via hazard functions. The second project implements Bayesian safety signal detection as described by Brock et al. (2022), under construction and open source as SafetySignalDetection.jl, again using Turing.jl and with a suitable extension of the expectation-maximization algorithm for fitting Beta mixtures. I will discuss the reasons why these projects were successful, and describe how we could easily embed the Julia algorithms into an R based overall workflow. Finally, I will introduce openstatsware.org where a growing community of statistical software engineers comes together to build software packages and develop and share best practices for such.

Speaker	Biography	Abstract
Matthew Lyon	Matt Lyon studied his Zoology BSc at the University of Liverpool. His degree included quantitative biology modules which used several statistical data packages. He started his career at The Francis Crick Institute in London as an Animal Technician before progressing to CRUK Manchester and finally moved to AstraZeneca in 2020 as an In-Vivo Scientist. Matt is currently the Global Head and his departments’ representative for Inclusion and Diversity (I&D).He also heads up a small, international cross functional team which focusses on creating and rolling out initiatives across the department. This also includes liaising with other areas of the business to promote AZ as a great place to work. Matt has taken over the Lead of the Steering Committee of the community of R users at AstraZeneca- ‘R@AZ’ – which currently has around 1600 members. Building on his I&D and quantitative biology skills, he is looking at expanding this community within AZ and beyond.	Building a BiggeR Community of R Users at AstraZeneca In the past years, the pharma industry has seen a true paradigm shift in its use of R. Up until recently, one had to choose between R and SAS. Today, most collaborators with a quantitative background are trained in at least 2 programming languages. With this in mind, at AstraZeneca we built on the growing interest for R, at any stage of the drug development but also company-wide. Since April 2021 we have launched a variety of initiatives, initially starting with a modified public initiative #azTidyTuesday and Function of the month. As the community grew, we launched our first AZ Conference, #AZRC2022 and this is now run on an annual basis. Throughout 2022, we have added a variety of initiatives to bring people together including: Lunch & LeaRn, AZ R Hot Desk and in 2023 we formed AZ R-Ladies. In early 2022, the R@AZ Leads were asked 3 questions: 1. What is the value of your community? 2. What is a Key Performance Indicator (KPI) of your community? 3. What is the Return On Investment (ROI) of your community? Prior to 2023, there were no definitive answers but whilst building this community internally, we have reached out and collaborated with external partners across the data science industry. In response, they have kindly provided us with educational and informative speakers for internal community events and continue to do so as we plan for 2024. The combination of all these initiatives, derived from the growth and passion of the steering committee, has led to an 800% increase in the internal social media community members; actively representing over 200 different departments with AstraZeneca. This is now highlighting the value, its KPI and ROI over 3 years in the making by building a network and a community.
Ari Siggaard Knoph	Ari is a Principal Statistical Programmer and International Lead Programmer at Novo Nordisk with a seat on the pharmaverse council. He is a driving force behind the adoption of R in clinical deliverables and submissions at Novo Nordisk. Ari is also the author and maintainer of multiple R packages used in the Novo Nordisk ecosystem.	Completing a submission and beyond in R In this presentation we will pull out some touch points of the Q&A phase of our first R-based submission. Examples of FDA interactions will be discussed and our thoughts on how to continuously manage a possibly drifting R environment in a submission will be shared.
Daniel Sabanes-Bove	Daniel Sabanes Bove studied Statistics in LMU Munich and obtained his PhD at the University of Zurich for his research work on Bayesian model selection. He started his career in 2013 at Roche as a biostatistician, then worked at Google as a data scientist from 2018 to 2020 before rejoining Roche. He currently leads the Statistical Engineering team in Roche Pharma Product Development that works on productionizing R packages, Shiny modules and how-to templates for data scientists. Daniel is co-author of multiple R packages published on CRAN and Bioconductor, as well as the book "Likelihood and Bayesian Inference: With Applications in Biology and Medicine", and is currently openstatsware.org (ASA BIOP working group on Software Engineering).	R(omeo) and Julia - A Love Story by openstatsware For implementing statistical methods in software, we recently started trying out the Julia language. "Julia is a high-level, general-purpose dynamic programming language, most commonly used for numerical analysis and computational science" (Wikipedia) and as such well suited for statistical applications. I will introduce two successful Julia projects. The first project implements joint models for time-to-event and longitudinal outcomes (see e.g. Kerioui et al. 2022), and is available open source as JointModels.jl. It uses Turing.jl for MCMC based Bayesian inference, based on a new distribution class for time-to-event data specified via hazard functions. The second project implements Bayesian safety signal detection as described by Brock et al. (2022), under construction and open source as SafetySignalDetection.jl, again using Turing.jl and with a suitable extension of the expectation-maximization algorithm for fitting Beta mixtures. I will discuss the reasons why these projects were successful, and describe how we could easily embed the Julia algorithms into an R based overall workflow. Finally, I will introduce openstatsware.org where a growing community of statistical software engineers comes together to build software packages and develop and share best practices for such.

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