ABSTRACT
MOTIVATION: The literature on complex diseases is abundant but not always quantitative. This is particularly so for Inflammatory Bowel Disease (IBD), where many molecular pathways are qualitatively well described but this information cannot be used in traditional quantitative mathematical models employed in drug development. We propose the elaboration and validation of a logic network for IBD able to capture the information available in the literature that will facilitate the identification/validation of therapeutic targets. RESULTS: In this article, we propose a logic model for Inflammatory Bowel Disease (IBD) which consists of 43 nodes and 298 qualitative interactions. The model presented is able to describe the pathogenic mechanisms of the disorder and qualitatively describes the characteristic chronic inflammation. A perturbation analysis performed on the IBD network indicates that the model is robust. Also, as described in clinical trials, a simulation of anti-TNFα, anti-IL2 and Granulocyte and Monocyte Apheresis showed a decrease in the Metalloproteinases node (MMPs), which means a decrease in tissue damage. In contrast, as clinical trials have demonstrated, a simulation of anti-IL17 and anti-IFNγ or IL10 overexpression therapy did not show any major change in MMPs expression, as corresponds to a failed therapy. The model proved to be a promising in silico tool for the evaluation of potential therapeutic targets, the identification of new IBD biomarkers, the integration of IBD polymorphisms to anticipate responders and non-responders and can be reduced and transformed in quantitative model/s.
Subject(s)
Algorithms , Inflammatory Bowel Diseases/metabolism , Matrix Metalloproteinases/metabolism , Models, Biological , Computer Simulation , Humans , Inflammatory Bowel Diseases/drug therapy , Interferon-gamma/antagonists & inhibitors , Interferon-gamma/metabolism , Interleukin-17/antagonists & inhibitors , Interleukin-17/metabolism , Molecular Targeted Therapy/methods , Tumor Necrosis Factor-alpha/antagonists & inhibitors , Tumor Necrosis Factor-alpha/metabolismABSTRACT
Pharmacokinetic modeling, traditionally using drug exposure, is widely used to support decision-making in translational medicine and patient care. The development of mechanistic computational models that integrate drug concentrations at the site of action making use of existing knowledge opens a new paradigm in optimal dosing. Clin Cancer Res; 24(14); 3236-8. ©2018 AACRSee related article by Ribba et al., p. 3325.
