Effective visual communication is a core competency for pharmacometricians, statisticians, and, more generally, any quantitative scientist. It is essential in every step of a quantitative workflow, from scoping to execution and communicating results …
metashiny is an R package that provides a point-and-click interface to quickly design, prototype, and deploy essential Shiny applications without having to write one single line of R code. The core idea behind metashiny is to parametrize Shiny …
In recent years, R users' understanding of Shiny has greatly increased but so have client expectations. While one of Shiny's greatest strengths is that it allows producing web applications solely from R code, meeting client's more delicate …
Scientists in drug discovery research utilize a wide variety of instrumentation and techniques to advance their research. While instrumentation vendors often provide software tools to deal with data wrangling and visualization, a simple collection of …
We define and illustrate a "deep visualization" paradigm for the analysis of a relatively large and complex clinical database for psoriasis (PSO) and psoriatic arthritis (PsA). This paradigm supports a growing number of machine learning and …
Introduction As pharmacometricians, we sometimes jump into complex modeling before thoroughly exploring our data. This can happen due to tight timelines, lack of ready-to-use graphic tools or enthusiasm for complex models. Exploratory plots can help …
nlmixr is a free and open source R package for fitting nonlinear pharmacokinetic (PK), pharmacodynamic (PD), joint PK/PD and quantitative systems pharmacology (QSP) mixed-effects models. Currently, nlmixr is capable of fitting both traditional …
R has become a prominent data science tool, empowered by a fast-growing modern R eco-system. At Novartis, Shiny and markdown have gained a lot of popularity in analyzing, visualizing and reporting of clinical trial data. Traditional report analysis …