With decades of clinical analytics expertise and a collective of thousands of trials analyzed and prepared, we understand the data and analyses within a regulatory environment. Acceptance and adoption of open-source tools are the future within this industry. Atorus sits on the forefront of this movement doing our part to embrace it.
If you want to adopt R and Python to start leveraging the power of open-source, Atorus can help you on your journey. As Full Service Certified Partners for RStudio, we can install, configure, and validate the full RStudio suite of products to meet your needs. Furthermore, we provide the support and training to ensure that your teams can leverage the power of not only the RStudio product suite, but R and open-source tools within pharma as well.
RStudio Server Pro
Enterprise scale requires enterprise quality products, and RStudio Server Pro gives you just that for your analytical environment. RStudio Server Pro is much more than just the RStudio IDE – it is the tool you need to deploy R to a production ready environment. Load balance your installation to handle huge workloads, parallel processing, and large numbers of users. RStudio Server Pro is just what you need to scale R across your organization.
R Shiny and R Markdown give developers and analysts to tools to create incredible reports to share their insights – but getting those insights in the hands of stakeholders can still be a challenge. But not with RStudio Connect. With the click of a button, R Shiny applications, R Markdown reports and Jupyter notebooks – can be deployed. Reports can be scheduled and delivered via email! RStudio Connect gives you lets analysts access their audience like never before, and helps you get the most out of R, Python, and more.
RStudio Package Manager
Scaling R out to an enterprise means taking control, and while the vast array of third-party packages available to R is its power, it is also its curse. RStudio Package Manager gives organizations the power to curate and control their own package repositories. Maintain your own internal archive of all R packages. Best of all – maintain these snapshots over time so users can always have access to the exact versions of packages at the time their analysis was conducted.