The case studies below show how to use Simulx for simulations.
Setting up a simulation from scratch
You can start a Simulx project by importing a Monolix run or you can define every element needed for the simulation from scratch. In this webinar, we explain how to setup a simulation by defining the model, parameters, treatments and outputs. A special focus will be given on the model writing in mlxtran language, with examples of translations from Nonmem and literature models.
The slides explain how to define each part of the mlxtran model and show screenshots of how to define the elements for the simulation in the GUI. The key points and results are also on the slides. The webinar can be reproduced step-by-step using the provided Simulx projects.
From Monolix to Simulx: how to explore new scenarios
When you have built a model, you can use it to compare new dosing regimens for the next trial, calculate the expected power of a study and select the most successful strategy? Learn effortless exploration of new scenarios with Simulx GUI – intuitive, flexible, and powerful application to simulate and compare countless strategies – and switch your focus to analysis and decision-making.
This video explains using Simulx with Monolix projects, it shows step-by-step how to simulate different groups, define target outcomes and assess the uncertainty and presents features that bring the best insight from simulations.
Optimizing Sample Size of a Phase III Trial
What if we could reduce the size of a phase III study from 400 to 80 subjects and make it twice as short? Thanks to model-informed clinical trial design, it’s possible! Watch an inspiring story based on real-world case study data and learn about Simulx at the same time. In an hour, we will take you from the modeling of phase II studies in Monolix to the estimation of a phase III study power in Simulx to finally optimizing sample size and study duration. Example scripts to script Simulx from R as done in this webinar can be found here.
