Machine Learning in Clinical Development. The What?, the Why?, and (a bit of) the How?
A Talk by Eliana Garcia Cossio PhD , Antigoni Elefsinioti and Dr. Sandra González Maldonado
About this Talk
This 90-minute workshop is aimed at statisticians with basic knowledge of machine learning concepts, looking to learn about its applications in clinical development. The workshop will begin with a refresher on ML basics. After this warm-up, we will talk about how ML can add value across the entire drug development life cycle. We will discuss how it can complement our classical statistical toolkit by allowing us to uncover complex patterns in data from clinical trials. And because there is no magic bullet, we will briefly mention the challenges it presents, including the non-trivial interpretability.
Finally, there will be two follow-along demos. The first will focus on employing ML techniques for the analysis of survival outcomes. The second one will present the application of two methods for the identification of treatment effect heterogeneity.
About The Speakers
Senior Biomarker Data Scientist, Bayer
Biomedical engineer with a PhD in neuroscience, experienced in developing innovative biomedical solutions and using statistical programming languages to manage, analyze, and derive insights from large datasets.
Lead Data Scientist Biomarker and Data Insights, Bayer
She is part of a specialized group focused on biomarkers, particularly in European biomarker research, and is associated with Bayer's efforts in using biomarker data in pharmaceutical development.
Senior Therapeutic Area and Methodology Statistician, Boehringer Ingelheim
She is a Senior Therapeutic Area and Methodology Statistician at Boehringer Ingelheim. She focuses on providing high-level statistical expertise for clinical development, working across therapeutic areas to improve statistical methodologies and enhance trial designs.
