The R Adoption Series
This is a new series of webinars focused on the adoption of R. Each session will include a case study and often include panels or discussions to enable those starting their journey to ask questions.
R Consortium will keep this page updated with information on future webinars in the R Adoption series. If there is some information that you are looking for specifically and you don’t see it here, feel free to email us at firstname.lastname@example.org
Speaking Different Languages – Clinical Statistical Modelling in a World with Choice
Date/Time: Fri, Dec 10, 11am – 12:30pm EST / 8am – 9:30am PST / 4pm – 5:30pm GMT
Clinical Statistical Reporting in a Multilingual World (CSRMLW) is a collaborative working group project between the R Consortium and PHUSE aimed at empowering statisticians to make informed decisions about the implementation of statistical analyses when multiple languages yield different results. In addition to the possibility of software errors, the source of these discrepancies may be due to differences in modelling assumptions, default parameters, or the choice of estimator or algorithm to compute a particular quantity. Resolving some differences may require adjudication by experts, while others may not be critical. The primary objective of CSRMLW is to provide guidance on the types of questions an analyst should ask to identify the fundamental sources of discrepant results. By doing so, the analyst is empowered to make informed decisions on how to perform the analyses of interest most appropriately.
Applications of the framework under development within the project initially focus on R vs SAS differences in four classes of statistical models: linear model, mixed model, survival analyses, and Cochran–Mantel–Haenszel analyses (CMH). During this session, participants should expect a project update from the project leads, interactive breakouts sessions devoted to each of the four classes of models, and guidance on how they might contribute to the project in the future.
Schedule – 90 mins:
- Background/Intro – 15 mins
- 4 Use Cases – Each one 15 mins (5 min brief presentation, 10 min group discussion)
- Closing/Next Steps – 15 mins
Michael Rimler, Head of Technical Excellence and Innovation at GlaxoSmithKline
Michael Rimler is the Head of Technical Excellence and Innovation at GlaxoSmithKline, a group that aims to accelerate the programming function’s path to industry pre-eminence through innovation and facilitating excellence in data engineering, data analysis, and sharing of insights.
In addition to leading innovation activities within Clinical Programming, Michael serves as the primary business lead for the integration of R into GSK’s clinical reporting process. In this role, he oversees activities driving the use of R for independent QC, developing standard reporting tools in R, and exploring opportunities for using R for the generation of trial results.
Externally, Michael is a sub-team lead for TransCelerate’s Modernization of Statistical Analytics project, co-chair of the 2022 PHUSE US Connect, and the co-lead of the PHUSE working group on multilingual clinical reporting which brings us here today.
Mike Stackhouse, Chief Innovation Officer at Atorus
Mike is a 2020 UC Berkeley School of Information Master of Information and Data Science (MIDS) program graduate, where he worked on projects involving computer vision, natural language processing, cluster computing, and deep learning. Previously, Michael was a senior manager of statistical programming at Covance, where he led U.S. innovation activities for the FSP department. Michael and his team at Atorus have been actively developing and releasing open-source R packages, such as pharmaRTF and Tplyr.
Mike is a Lead of PHUSE’s Data Visualisation & Open Source Technology Working Group, home to the Clinical Statistical Reporting in a Multilingual World project, which he co-leads alongside Michael Rimler.
Archived Webinars – Full Recordings Available
R Package Management at Roche
Date/Time: Wednesday, November 17, 3pm – 5pm GMT / 7am – 9am PST / 10am – 12 noon EST
Kieran Martin, Tadeusz Lewandowski, Adrian Waddell
In this session we will be looking at various learnings obtained from creating a corporate R infrastructure and developing R packages to address the unique business problems presented by clinical trials.
Architecting and maintaining an R installation across a large organisation can be challenging. How do you balance between giving individual users the ability to meet their specific needs, but also provide a standardised environment which meets regulatory requirements? As R needs expand, then internal packages also get created, and these also need to be managed.
It is often useful to create custom R packages to complement the community R packages. We are developing both open and closed source packages that we validate and deploy on our R infrastructure. We will be discussing some learnings from the NEST software development team including: project management, automation, devops, testing, integration, releasing, validation, and deployment of the in-house built R packages. We will also be presenting steps we took towards simplifying the development process to enable co-creation and collaboration with internal and external developers.
Finally, we will split into break out rooms to discuss some relevant topics on how package creation and management can be dealt with effectively.
Kieran Martin, R Enablement Lead: PD Data Sciences at Roche
Kieran has a background in statistics and has a PhD in experimental design from the University of Southampton. He has been using R for over a decade, and has always advocated for it’s expanded usage as a tool for data science. He has been at Roche for 6 years, working on a variety of different molecules and projects, most recently he has become the R Enablement Lead for Product Development Data Sciences; his role is to promote the usage of R and influence how it is utilised.
Tadeusz Lewandowski, Pan-Pharma collaboration product lead
Tadeusz Lewandowski joined Roche in 2008 and he is currently a Pan-Pharma collaboration product lead. Tadeusz holds dual master’s degrees from the universities in Poland. He received his MSc in Economics from Poznan University of Economics, and MSc in Engineering (Electronics and Telecommunications). In 2016, Tadeusz was appointed to establish the Statistical Programming Analyst – Data Analytics Oncology group. In 2019 Tadeusz co-initiated the NEST project at Roche. NEST is a software development project for creating R based tools to analyze clinical trials data for exploratory and regulatory use.
Adrian Waddell, Chief Engineer NEST Project
Adrian Waddell joined Roche in 2016 and he is currently part of the Data Science Acceleration group. Adrian holds a PhD in Statistics with focus on interactive data visualization and exploration from the University of Waterloo, Canada, and a bachelor degree in data analysis and process design from the Zurich University of Applied Sciences. In 2019 Adrian co-initiated the NEST project at Roche and he is currently the technical lead. NEST is a software development project for creating R based tools to analyze clinical trials data for exploratory and regulatory use.
R Training Strategies at Janssen
September 29, 11am EDT
Paulo R. Bargo, Daniel Hofstaedter and Gayathri Kolandaivelu
Janssen Pharmaceuticals R&D
Full video recording available here (1:34:21 mins)
As the Pharmaceutical sector boosts its interactions with regulatory agencies using R programming as one key instrument for drug development submissions, we face a dilemma that several members of statistics and statistical programming teams are not currently advanced R programmers. At Janssen we aim to improve the literacy in R programming and achieve nearly 100% adoption by these teams. To achieve this goal, we are leveraging all types of training formats, from online training to in-house instructor led seminars, to one-on-one mentoring as well as internal crowd-led hands-on workshops where statisticians/programmers are “thought” to solve on-the-job real problems ranging from visualization to automated reports. In this presentation we will discuss our experience implementing these strategies, challenges we faced, share lessons learned, mistakes and successes. We will also discuss topics on continued support and change management. A panel discussion with members from other pharmaceutical companies will close the event.
- Intro – 5 mins
- Presentation – 45 mins
- Q&A – 10 mins
- Panel Discussion – 30 mins
Paulo R. Bargo, Ph.D., Head of R&D Data and Advanced Analytics, Ethicon, part of the Johnson & Johnson family of Companies
Paulo Bargo is currently the head of Data and Advanced Analytics for Ethicon R&D, developing strategies to enable Ethicon’s digital transformation and promoting use of open-source solutions as well as developing training initiatives to improve data literacy. He was head of Scientific Computing for Statistics & Decision Sciences at Janssen Pharmaceuticals R&D for 5 years, developing cloud computing strategies to enable data science projects in clinical and non-clinical space. Prior to joining the pharmaceutical sector, he spent 13 years in the consumer and personal industry with tenures at Johnson & Johnson Consumer Companies and L’Oreal USA. He is a member of the R Validation Hub executive committee and the R/Pharma executive committee.
Paulo has a BS in Electrical Engineering (EE), MS in Biomedical Engineering and a PhD in EE. During his scientific career he published 13 peer-reviewed articles, 1 book chapter and authored/presented 40+ abstracts in scientific conferences.
His research interests are data science, connected/wearable technologies, biomedical optics, tissue spectroscopy and medical imaging.
Dan Hofstaedter is a statistical programmer within the Janssen Clinical & Statistical Programming group. Over the course of his twenty years at Janssen, he has led the programming efforts for numerous regulatory submissions within the Immunology therapeutic area and was the primary author of the Janssen SAS Reporting Macro suite. More recently, Dan has supported the adoption of R within Janssen, co-leading the R Training initiative.
Dan has BS Degrees in Mathematics and Business Administration from Delaware Valley University and an MS Degree in Applied Statistics from Villanova University. Prior to entering the field of statistical programming, Dan was a high school mathematics teacher.
Gayathri Kolandaivelu has over 13 years of experience in the pharmaceutical industry. She is currently an associate director supporting sourcing and process group in Business operations in Clinical and statistical programming group at Janssen Pharmaceutical company (JnJ), Springhouse, PA. She was a pediatric portfolio lead in immunology and has experience in Early Development, Late Development, and Regulatory Submission. Worked as a Clinical programmer, Programming Lead, Portfolio Lead in Janssen and ICON. She is a Change management lead (Prosi certified) and a communication lead for Clinical and statistical programming in Janssen. She is a Design thinking expert has conducted many DT workshops for PHUSE US connects and CSS.
She has a Master’s in Bioengineering from UT southwestern medical center/UTA, Dallas, Texas and currently pursuing MBA from Drexel Lebow, Philadelphia, Pennsylvania.
Scaling R at GSK
Full video recording available here (58:52 mins)
Summary: In this presentation, Andy Nicholls, Head of Data Science within GSK Biostatistics, provided an overview of GSK’s WARP environment for Biostatistics. The presentation described the key requirements that led to building the environment and included an overview of the basic technical components that enabled these requirements. Nicholls also discussed GSK support and maintenance strategy for R and R packages.
The presentation touched upon important topics that fed into the discussion:
- Support and maintenance strategy for R
- Controlled execution of R (GxP workflows)
- In-house vs cloud infrastructure
- Intro – 10 mins
- Case Study presentation: Scaling R at GSK – 45 mins (including 10 mins for Q&A)
- Break – 5 mins
- Parallel discussions – 45 mins
Andy Nicholls is Head of Data Science within GSK Biostatistics. He has been a user and strong advocate for the use of R for over 15 years. Andy is responsible for driving the R adoption initiative within GSK Biostatistics. His team helped create Biostatistics’ first dedicated analytics platform for R and developed a world-wide R training programming. The team has also led the development of several R-based tools and applications to assist the rollout and adoption of R as a clinical and non-clinical reporting capability. Within the wider industry, Andy is the lead for the R Validation Hub, a collaboration to support the adoption of R within a biopharmaceutical regulation setting.
Andy has an MMath degree from University of Bath and MSc Statistics with Applications in Medicine from University of Southampton. Prior to re-joining GSK in 2017 Andy was the Head of Data Science Consultancy at Mango Solutions.