2026-08-12 –, Room 4
The most popular modeling framework in pharmacometrics is nonlinear mixed-effects modeling. In the pharmacometric application of the model framework, the time dimension is typically a solution to a dynamical system. The combination of the nonlinearity of the statistical model and the computational costs of numerically solving differential equations has made the use of staged programming necessary in all available software packages. The staged programming requirement has historically been associated with a large maintenance burden, but staged programming is also what Julia was designed for. In this talk, I outline the modeling class most popular in pharmacometrics, give an overview of how historical solutions are used, and explain how Julia is well suited for pharmacometrics.
Andreas Noack is the Vice President of Product Development at PumasAI. His expertise includes nonlinear mixed-effects modeling, numerical linear algebra, and parallel computing, with contributions to several open source Julia packages and the proprietary Pumas application for pharmacometrics. He has a background in econometrics and computer science with a PhD in economics from the University of Copenhagen and three years of experience as a postdoctoral associate at MIT's Computer Science and Artificial Intelligence Laboratory.