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.

PSI Webinar: Drug Development in Women's Health

The event will open with an overview on drug development in women’s health from a clinician perspective. This talk is followed by talks about statistical challenges when planning IVF studies and analysing the menstrual cycles.

PSI Webinar: Surrogacy

This webinar will provide an overview of surrogacy for licensing and reimbursement. In turn, the need of extensions of the SPIRIT and CONSORT statement will be defined and outlined, with case studies to support.

Joint PSI/EFSPI Pre-Clinical SIG Webinar: Virtual Control Groups in Toxicity Studies

Lea Vaas will present how replacement of concurrent control animals by Virtual Control Groups (VCGs) in systemic toxicity studies may help in contributing to the 3R's principle of animal experimentation: Reduce, Refine, Replace.

Joint PSI/EFSPI Data Science SIG Webinar: Developing Digital Measures (Digital Biomarkers) in Drug Development – insights from Mobilise D consortium

We will share a brief overview of what Mobilise D is and why it is an important step stone in the development of digital biomarkers, and how Mobilise D outputs can be relevant for you.

PSI Career Young Virtual Event (Q2 2024)

This networking event is aimed at statisticians that are new to the pharmaceutical industry who wish to meet colleagues from different companies and backgrounds.

PSI Webinar: Development of Gene Therapies: Strategic, Scientific, Regulatory and Access Considerations

This webinar will cover the history of cell/gene therapy, major regulatory advances, the role of quantitative scientists in drug development of these novel therapeutics, and discuss opportunities for innovation and product advancement.

PSI Career Young Virtual Event (Q3 2024)

This networking event is aimed at statisticians that are new to the pharmaceutical industry who wish to meet colleagues from different companies and backgrounds.

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 Career Young Virtual Event (Q4 2024)

This networking event is aimed at statisticians that are new to the pharmaceutical industry who wish to meet colleagues from different companies and backgrounds.

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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