Related Experiment Video
Updated: Jun 16, 2026

Efficient Sampling of Genetically Encoded Biosensor Design Space Enabled with a Design of Experiments and Automation Workflow
Published on: October 17, 2025
An optimal experimental design approach to model discrimination in dynamic biochemical systems
1Center for Analysis of Biological Systems (ZBSA), University of Freiburg, Habsburgerstr. 49, 79104 Freiburg, Germany.
Motivation:
Finding suitable models of dynamic biochemical systems is an important task in systems biology approaches to the biosciences. On the one hand, a correct model helps to understand the underlying mechanisms and on the other hand, one can use the model to predict the behavior of a biological system under various circumstances. Typically, before the correct model of a biochemical system is found, different hypothetical models might be reasonable and consistent with previous knowledge and available data. The main goal now is to find the best suited model out of different hypotheses. The process of falsifying inappropriate candidate models is called model discrimination.
Results:
We have developed a new computational tool to compute optimal experiments for biochemical kinetic systems with underlying ordinary differential equation (ODE) models for the purpose of model discrimination. We were inspired by the demands of biological experimentalists which perform one run measurement where perturbations to the system are possible. We provide a criterion which calculates the number and location of time points of optimal measurements as well as optimal initial conditions and optimal perturbations to the system.
Availability:
The model discrimination algorithm described here is implemented in C++ in the package ModelDiscriminationToolkit. The source code can be downloaded from http://omnibus.unifreiburg.de/~ds500/_software.html.
Related Concept Videos
Pharmacokinetic Models: Comparison and Selection Criterion
Physiological models take a detailed approach by considering specific molecular processes. They can predict drug distribution, metabolism, and elimination changes, providing a comprehensive understanding of how drugs interact with the body.
Mechanistic Models: Compartment Models in Individual and Population Analysis
Bioequivalence Experimental Study Designs: Repeated Measures, Cross-Over, Carry-Over, and Latin Square Designs
Parameters Affecting Nonlinear Elimination: Zero-Order Input, First-Order Absorption and Two-Compartment Model
When a drug is administered through a constant intravenous infusion and eliminated via nonlinear pharmacokinetics, it follows zero-order input. For example, oral drugs undergo first-order absorption upon administration and are eliminated through nonlinear pharmacokinetics.
In the case of subcutaneously administered drugs,...
Pharmacodynamic Models: Link Model and Systems Pharmacodynamic Model
Model Approaches for Pharmacokinetic Data: Physiological Models
