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Accelerating GSK’s Open-Source Journey with Gen AI

This presentation provides an insightful exploration of GSK's innovative journey in integrating Large Language Models (LLMs) into biostatistics. It begins with the strategic introduction of LLMs to users, progressing through to the pioneering LLM …

Christina Fillmore’s Keynote

This presentation provides an insightful exploration of GSK's innovative journey in integrating Large Language Models (LLMs) into biostatistics. It begins with the strategic introduction of LLMs to users, progressing through to the pioneering LLM …

Responsive Regulation of AI in Drug Development

Over the past few decades, the volume of data available to support drug and biological product development have increased substantially. These increases in data volume were also accompanied by an expansion in data diversity with data originating from …

Tala Fakhouri’s Keynote

Over the past few decades, the volume of data available to support drug and biological product development have increased substantially. These increases in data volume were also accompanied by an expansion in data diversity with data originating from …

Joe Cheng’s Keynote

R users tend to be skeptical of modern AI models, given our weird insistence on answers being accurate, or at least supported by the data. But I believe the time has come—or maybe it’s a little late—for even the most AI-cynical among us to push past …

Summer is Coming: AI for R, Shiny, and Pharma

R users tend to be skeptical of modern AI models, given our weird insistence on answers being accurate, or at least supported by the data. But I believe the time has come—or maybe it’s a little late—for even the most AI-cynical among us to push past …

Why we Need to Improve Software Engineering in Biostatistics - A Call to Action

Programming is ubiquitous in applied biostatistics, and most statisticians know a programming language such as R - yet software engineering is still neglected as a skill and undervalued as a profession in pharmaceutical statistics. Why is this a …

The importance of the SCE in enabling our shift from proprietary programming to open-source data science

Historically building a great SCE for clinical reporting involved selecting a vendor, integrating their product, and supporting a single proprietary language. The shift to report clinical trials using R has had a much broader impact than just …

Our Impact in the Evolving Data Landscape

Data sources and the volume of data available for driving discovery and informing decisions have substantially increased over time. This increase has resulted in an evolving data and regulatory landscape ripe for the expertise of statisticians and …

BioTech Challenges

I will talk about some of the challenges that are now arising in BioTech. There are larger, more informative but much more complex, data sets available and being developed. While these hold great promise they add complexity to an already fragile …