DateMay 14-17, 2023 LocationSan Francisco, CA

Atorus is attending and presenting at PharmaSUG 2023. Learn more about our presentations and request a meeting using the form to the right.

Evolving Analytics: The Technological Migration of Biometrics

mike stackhouse

Presented by:

Mike Stackhouse

Atorus Research

In our highly regulated industry, change doesn’t come easily. Modern technology is evolving around us and migrations are beginning – evolving the procedures we follow and our roles themselves. Let’s take a look at how the promise of today might be the process of tomorrow.

Making Multilingual Programmers – A Targeted Approach to R for Clinical Trials Training

Ashley Tarasiewicz

Presented by:

Ashley Tarasiewicz

Atorus Research

Jagan Achi

Jazz Pharmaceuticals

Over the past few years many pharmaceutical organizations have encountered the same challenge – there is a wealth of training available on open-source languages like R, but very little training specific to the traditional clinical trial workflows we use on a daily basis. Companies are beginning to see and realize the benefits of having a multilingual programming team – they can incorporate the best parts of each programming language in their processes to maximize efficiency. In recent months, Jazz Pharmaceuticals has implemented several successful strategies to train their SAS® programmers in the use of R. This paper will examine the challenges and successes of finding the right training content, format, and candidates for teaching clinical programmers how to use R.

Real Projects, Real Transition, Really Revolutionary – Transitioning to R for Biometrics Work

danielle

Presented by:

Danielle Stephenson

Atorus Research

alyssa

Alyssa Wittle

Atorus Research

Rebekah Oster

Atorus Research

Technology is developing quickly and staying on the cutting edge has its challenges. Often, diving into something new is an intimidating idea for programmers, companies, and sponsors – especially when the day-to-day work must continue. The pharmaceutical industry has been entrenched in SAS® for decades, and the time has come to explore open-source and dedicate the time to figure this out. What are the ups and downs of this transition? How can the learning curve become a bit less curvy? Can TFLs and CDISC-compliant datasets be created using R? We will dive into what it looks like for a team to go from SAS-fluent to multi-lingual in real time, with real projects, and ways to ensure quality while making the transition.

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