Tobias Newmiwaka1, Benjamin Engelhardt1,2,3, Philipp Wendland1, Dominik Kahl1, Holger Fröhlich2, Maik Kschischo1. 1. Department of Mathematics and Technology, University of Applied Sciences Koblenz, RheinAhrCampus, Remagen 53424, Germany. 2. Bonn-Aachen International Center for IT (b-it), Rheinische Friedrich-Wilhelms-Universität Bonn, Bonn 53115, Germany. 3. AbbVie Deutschland GmbH & Co. KG, Clinical Pharmacology and Pharmacometrics, Knollstrasse, Ludwigshafen 67061, Germany.
Abstract
SUMMARY: Dynamic models formulated as ordinary differential equations can provide information about the mechanistic and causal interactions in biological systems to guide targeted interventions and to design further experiments. Inaccurate knowledge about the structure, functional form and parameters of interactions is a major obstacle to mechanistic modeling. A further challenge is the open nature of biological systems which receive unknown inputs from their environment. The R-package SEEDS implements two recently developed algorithms to infer structural model errors and unknown inputs from output measurements. This information can facilitate efficient model recalibration as well as experimental design in the case of misfits between the initial model and data. AVAILABILITY AND IMPLEMENTATION: For the R-package seeds, see the CRAN server https://cran.r-project.org/package=seeds.
SUMMARY: Dynamic models formulated as ordinary differential equations can provide information about the mechanistic and causal interactions in biological systems to guide targeted interventions and to design further experiments. Inaccurate knowledge about the structure, functional form and parameters of interactions is a major obstacle to mechanistic modeling. A further challenge is the open nature of biological systems which receive unknown inputs from their environment. The R-package SEEDS implements two recently developed algorithms to infer structural model errors and unknown inputs from output measurements. This information can facilitate efficient model recalibration as well as experimental design in the case of misfits between the initial model and data. AVAILABILITY AND IMPLEMENTATION: For the R-package seeds, see the CRAN server https://cran.r-project.org/package=seeds.