For decades, SAS has been regarded as the industry standard for statistical programming and regulatory submissions in clinical trials. However, the analytics landscape is rapidly evolving. With the rise of open-source innovation, reproducible research frameworks, AI integration and cost-conscious technology strategies, R has emerged as a powerful alternative and, increasingly, a strategic choice for clinical data analytics.
This webinar explores whether R is positioned to take a leading role in the future of clinical research. The featured speakers will examine the technical, operational and regulatory factors driving the shift, including advances in validation frameworks, package governance, reproducibility tools and compliant computing environments. Real-world adoption trends among pharmaceutical and biotech companies will be discussed, as will the growing integration of R into modern data science ecosystems and AI-enabled workflows.
Importantly, this webinar will address the key concerns that often arise in regulated settings: validation, 21 CFR Part 11 compliance, auditability, package control and long-term sustainability. Rather than framing the discussion as a binary “R vs. SAS” debate, this session will provide a balanced and strategic perspective on how organizations can design future-ready statistical computing environments that align with regulatory expectations while maximizing innovation and efficiency.
Register for this webinar to learn how R can support a compliant, future-ready approach to clinical data analytics.
Speakers
(Presenter) Tai Xie, PhD, CEO, CIMS Global
Tai Xie obtained his PhD in Statistics from the University of Arizona. He is the Founder and CEO of CIMS Global and previously founded Brightech, which was acquired in 2022. Prior to that, he spent 10 years at pharmaceutical companies, including Pfizer, Johnson & Johnson, and Eli Lilly, where he gained expertise in clinical trials, statistical analysis, reporting, and regulatory submissions.
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Tai advocates for the use of open-source tools (R and Python), as well as AI, in clinical trials. He leads a team of over 40 developers to build innovative platforms such as Compliant R Environment (CRE), DMC-HUB, and AI governance solutions.
Tai is a thought leader who shares insights on clinical data analytics and AI adoption on LinkedIn and other professional platforms. He specializes in adaptive trial design and co-invented Dynamic Data Monitoring (DDM), which has been used successfully in multiple clinical trials.
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(Paneslist) Peng Zhang, PhD, Associate Director of Innovative Data Sciences, CIMS Global
Peng Zhang is the Associate Director of Innovative Data Sciences Department at CIMS Global. He graduated from Rutgers School of Public Health with Ph.D. in Biostatistics with research interest in adaptive design and statistical monitoring of clinical trials.
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Peng leads the internal development of R packages, R Shiny apps, agentic workflow, and supports software development with open-source solutions. Peng has also served as independent statistician for 30+ DSMB meetings and 10+ ongoing clinical trials from phase 2 to phase 3 for different therapeutical areas.
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(Panelist) Daniel Sabanés Bové, PhD, Co-Founder, RPACT
Daniel Sabanés Bové studied statistics at LMU Munich, Germany and obtained his PhD at the University of Zurich, Switzerland in 2013 for his research work on Bayesian model selection. He started his career with 5 years in Roche as a biostatistician, then worked 2 years at Google as a Data Scientist, before rejoining Roche in 2020 to found and lead the Statistical Engineering team. Mid-2024, Daniel co-founded inferential.biostatistics and the RCONIS joint venture, and joined RPACT as a partner in October 2025.
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Daniel is (co-)author of multiple R packages published on CRAN and Bioconductor (recent ones include crmPack, mmrm and RobinCar2), as well as the book “Likelihood and Bayesian Inference: With Applications in Biology and Medicine”. He is currently a co-chair of the openstatsware.org working group on Software Engineering in Biostatistics.
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(Panelist) Will Landau, Senior Advisor, Innovative Statistics, Eli Lilly and Company
Will Landau earned his PhD from Iowa State University in 2016, where his research applied Bayesian methods and GPU computing to genomic data analysis. He works at Eli Lilly and Company, where he builds methods and tools for clinical statisticians. His work includes disease progression modeling, historical borrowing, and the design and simulation of clinical trials.
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Will develops open-source R packages such as targets, crew, brms.mmrm, and pmrm, and he co-leads the r-multiverse.org dual repository. He is active in rOpenSci, Openstatsware, and the R Consortium.
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(Paneslist) Joseph Rickert, R Community Champion
Joe is a long time champion of the R language with a career in data science and technology marketing that spanned multiple industries. He had the good fortune to become deeply involved in the R community while working at Revolution Analytics, RStudio and serving as Executive Director and Chairman of the Board of the R Consortium.
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Joe is an ASA member and Lifetime IEEE member who still has a passion for data analysis and mathematical modeling. He earned an MS in Computational Statistics, an MA in Humanities, and a BA in Mathematics. Joe was a prolific contributor to the Revolution Analytics blog, the R Views RsStudio blog, and is currently an editor for R Works (www.rworks.dev).
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Who Should Attend?
This webinar will be relevant to professionals across pharma, biotech, life sciences research organizations and CROs, particularly those involved in clinical data, analytics and digital leadership roles, including:
- Biostatisticians, clinical data scientists, and statistical programmers working in clinical trials
- Heads, Directors, and VPs of Biometrics, Biostatistics, and Statistical Programming
- Clinical data management and data governance leaders
- Technology and innovation leaders driving adoption of modern analytics environments (R, cloud, AI)
- CRO and sponsor-side decision-makers responsible for clinical data strategy, efficiency, and compliance
What You Will Learn
Attendees will gain insights into:
- The evolving regulatory and technological landscape
- Governance and validation strategies for R in GxP environments
- Organizational considerations when transitioning analytic platforms
- A forward-looking vision for modern clinical data analytics
Xtalks Partner
CIMS Global
With over 16 years of industry experience, CIMS has pioneered the reshaping of clinical trials with novel technologies and services that streamline and fast-tracks clinical trials creating pathways for life-saving therapies. We bridge the gap between visionary researchers and effective treatments with speed and reliable data with a powerful toolkit.
CIMS Global specializes in delivering innovative data science services and solutions for clinical trials. By leveraging proprietary and advanced technologies, including Artificial Intelligence (AI), Large Language Models (LLM), Natural Language Processing (NLP), and Machine Learning (ML) coupled with advanced statistical methodologies, CIMS Global accelerates and enhances the quality and efficiency of clinical trial data acquisition, processing, analysis, and regulatory submissions.
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