This webinar is free to both Members of PSI and Non-Members.
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is event\, please
Talks from the speakers will cover th e use of R in a programming community\, submitted to regulators using R\, and also programming beyond R in C++ and Julia.
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Speaker \n | \n Biograph y \n | \n Abstract \n < /td>\n |
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| Matt Lyon \;studied his Zoology BSc at the Un
iversity of Liverpool. His degree included quantitative biology modules wh
ich used several statistical data packages. He started his career at The F
rancis Crick Institute in London as an Animal Technician before progressin
g to CRUK Manchester and finally moved to AstraZeneca in 2020 as an In-Viv
o Scientist. \n \n Matt is currently the Global Head and his departments&rsquo\; representative for Inclusion and D iversity (I&\;D).He also heads up a small\, international cross functio nal 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. \n \n Matt has taken over the Lead of the Steering Committee of the communi ty of R users at AstraZeneca- &lsquo\;R@AZ&rsquo\; &ndash\; which currentl y has around 1600 members. Building on his I&\;D and quantitative biolo gy skills\, he is looking at expanding this community within AZ and beyond . \n \n \n
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Building a BiggeR Community of R Users at AstraZenec
a |
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| \n Ari is a Principal Statistica l 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 th e author and maintainer of multiple R packages used in the Novo Nordisk ec osystem. \n | \n Completing a submission and beyond in
R \n |
\n <
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ymode="Custom" alt="danieledit" title="danieledit" /> | \n 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 sc ientist from 2018 to 2020 before rejoining Roche. He currently leads the S tatistical Engineering team in Roche Pharma Product Development that works on productionizing R packages\, Shiny modules and how-to templates for da ta scientists. Daniel is co-author of multiple R packages published on CRA N and Bioconductor\, as well as the book "Likelihood and Bayesian Inferenc e: With Applications in Biology and Medicine"\, and is currently openstatsware.org (ASA BIOP working g roup on Software Engineering). \n\; \n | \n
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 common ly used for numerical analysis and computational science" (Wikipedia) and as such well suited for statistical applications. I will introduce two suc cessful Julia projects. The first project implements joint models for time -to-event and longitudinal outcomes (see e.g. Kerioui et al. 2022)\, and i s 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 imp lements Bayesian safety signal detection as described by Brock et al. (202 2)\, under construction and open source as SafetySignalDetection.jl\, again using Turing.jl and with a suitabl e extension of the expectation-maximization algorithm for fitting Beta mix tures. I will discuss the reasons why these projects were successful\, and describe how we could easily embed the Julia algorithms into an R based o verall workflow. Finally\, I will introduce openstatsware.org where a growing community of sta tistical software engineers comes together to build software packages and develop and share best practices for such. \n\; \n |