Different cases studies are presented here to show how to use Mlxtran to define a model and how to use Mlxplore for model exploration.
Tumor growth model:
- Tumor growth inhibition model exploration: The purpose of this example is the exploration of a tumor growth inhibition model for low-grade glioma treated with chemotherapy or radiotherapy. The model comes from a paper from Ribba et al. in Clinical Cancer Research (18(18); 5071–80). The research goal is to describe tumor size evolution in patients treated with chemotherapy or radiotherapy and to explore the impact of treatments on the tumor growth, along with the impact of inter-individual variability.
Delay modeling:
- Using delays, the example of rheumatoid arthritis: Rheumatoid arthritis (RA) is an immune-mediated inflammatory disease and is characterized by a chronic inflammation and synovial hyperplasia leading to the destruction of cartilage and bone. Approximately one percent of the world-wide population suffers from RA. The model comes from a poster published at PAGE in 2011 by Gilbert Koch. The research goal is to develop a multi response model to describe the time course of the total arthritic score and the strongly delayed ankylosis score measured in collagen induced arthritic (CIA) mice. The authors used a three compartment delay differential equation model to get a deeper understanding between cytokine level, inflammation and bone destruction.
Pharmacokinetic modeling:
- Tobramycin pharmacokinetics: In this example, the pharmacokinetics of Tobramycin, an antimicrobial agent, is explored. It is part of a case study crossing over all applications (Datxplore, Monolix, Mlxplore, Simulx).
Physiologically-based pharmacokinetic (PBPK) models:
- Glucose-insulin model: the example explores the homeostasis of glucose and insulin plasma concentrations after glucose or carbohydrate uptakes as performed during glucose tolerance tests. The PBPK model represents glucose, insulin, incretins and glucagon and has 28 equations.
Target-mediated drug disposition models:
- TMDD models: TMDD models exhibit a characteristic concentration-time profile. Each parameter of the model has a precise impact that we can visualize using Mlxplore. This knowledge helps to determine which parameter are identifiable depending on the data set.
Treatment explorations:
- From single dose to multiple doses: after having estimated a PK model on a single dose data set, the model is exported to Mlxplore to explore new dosing regimens, in particular multiple doses. The simulations are overlaid with actual data for comparison.
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