Introducing a new Coursera course for hands-on clinical data science using R.

Shifting to R in an industry traditionally reliant on SAS is no small feat. It requires not just new tools, but also significant upskilling for programmers. Roche-Genentech is addressing this need by offering three publicly available Coursera courses aimed at enhancing the skills of current data scientists within the pharmaceutical sector and introducing our work to those outside the industry. In this post, we are excited to announce the release of our second Coursera course, and we will discuss how R open-source software is being embraced across the industry and particularly within Roche-Genentech. Additionally, we will provide an overview of the three Coursera courses and explain why such initiatives are essential for a successful transition to open-source tools and a new mindset.

In recent years, the pharmaceutical industry has witnessed a significant shift towards adopting open-source software and programming languages for various applications. Among them, R has emerged as a game-changer, revolutionizing the way we approach Health Authority electronic submissions and pharmaceutical analysis.

As the industry embraces new ways of working, R has gained immense popularity due to its flexibility, versatility, and extensive range of open-source packages and tools. Open source tools specifically created for the clinical data scientist are collected under and shared within the pharmaverse, enabling data scientists and researchers to leverage the power of R for a wide array of applications, including clinical trial studies, data set creation, and analytical reports.

Within Roche-Genentech, a dedicated working group of Data Scientists recognized the potential of R in a pharmaceutical regulatory setting. Leveraging their expertise and pharmaverse knowledge, they developed a series of trainings on Coursera. These trainings provide hands-on demonstrations and examples, guiding industry professionals on how to effectively utilize R in running a complete clinical trial study. Specifically, the first training, Making Data Science Work for Clinical Reporting, offers a broad introduction to the work as a data scientist within the pharmaceutical industry. This should be of particular interest to aspiring clinical data scientists. The second training – which we are releasing this week – dives deep into the workflow of a clinical data scientist and introduces the tools we use on a daily basis. Looking into the future, there will be a project capstone training course that integrates the concepts from the preceding two courses, culminating in comprehensive learning, providing a strong foundation of knowledge for aspiring data scientists using R in the Pharma industry.

Here is an outline of what participants will gain from the training we are releasing this week.

Hands-On Clinical Reporting Using R

1. Fundamentals & SDTM; the Study Data Tabulation Model

2. ADaM Transformations (Introductory, using {admiral} )

3. ADaM Transformations (Advanced, using {admiral} )

4. Static Tables, Listings, and Graphs (using NEST including {tern} , {rtables} , and {rlistings} )

5. Interactive Data Displays (using {teal} )

In essence, participants will learn how to navigate and manipulate datasets using R, ensuring data integrity and accuracy. Additionally, R’s powerful statistical capabilities enable the creation of insightful Tables, Listings, and Figures/Graphs (TLF/Gs), which are vital components of regulatory submissions. Even further, the Coursera training offered by Roche-Genentech will empower industry professionals to unlock the full potential of R Shiny in their analytical reports. This feature enables researchers to present complex data in a user-friendly and interactive manner, enhancing the understanding and interpretation of results.

A stepping stone towards the future: For those in the industry who are embracing these new ways of working, the Coursera training provided by Roche-Genentech serves as a valuable stepping stone into the world of R open-source software. The training equips participants with the necessary skills to harness the power of R, facilitating efficient and effective pharmaceutical analysis.

In conclusion, the adoption of R open-source software and programming language is transforming the pharmaceutical industry, enabling professionals to streamline their processes, enhance data analysis, and improve regulatory submissions. Roche-Genentech’s commitment to sharing knowledge and expertise through the Coursera trainings demonstrates their dedication to advancing the pharmaverse As the industry continues to embrace this new direction, the future of pharmaceutical analysis looks increasingly promising with R at its core.

Your journey to revolutionizing your pharmaceutical analysis knowledge awaits!

Huge thanks to Adrian Chan who led the effort of building this course and the instructors Jana Stoilova, Joel Laxamana, M.S., Leena Khatri, Tatiana Alonso Amor & Stefan Thoma.

Last updated

2025-04-16 09:37:46.128947

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