PSI Careers - MEDMathS: Medicine Empowered by Data, Maths and Statistics
Date: Wednesday 6th November 2024 A careers talk about medical statistics and how it plays a crucial role in developing new medicines
Date: Wednesday 17th April 2024
Time: 14:00-15:30 BST | 15:00-16:30 CEST
Location: Online via Zoom
Speakers: Matthew Lyon (AstraZeneca), Ari Siggaard Knoph (Novo Nordisk) and Daniel Sabanes-Bove (Roche).
Who is this event intended for? Statisticians and programmers who are working or thinking of working in software beyond SAS.
What is the benefit of attending? Learning from the experiences of teams working with R and software beyond SAS in the pharma industry.
This webinar is free to both Members of PSI and Non-Members.
To register for this event, please click here.
Talks from the speakers will cover the use of R in a programming community, submitted to regulators using R, and also programming beyond R in C++ and Julia.
Speaker |
Biography |
Abstract |
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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 |
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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 |
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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).
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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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