<HashMap><database>Cell Collective</database><scores/><additional><omics_type>Models</omics_type><submitter>Violeta Balbas Martinez</submitter><version_name></version_name><full_dataset_link>https://cellcollective.org/#8558/inflammatory-bowel-disease-(ibd)-model</full_dataset_link><model_score>4.5101</model_score><default_version>1</default_version><ModelFormat>SBML</ModelFormat><submitter_affiliation></submitter_affiliation><submitter_email></submitter_email><version_id>1</version_id><repository>Cell Collective</repository><version_url>https://cellcollective.org/#8558:1/inflammatory-bowel-disease-(ibd)-model</version_url><version_description></version_description><pubmed_abstract>&lt;h4>Motivation&lt;/h4>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.&lt;h4>Results&lt;/h4>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.</pubmed_abstract><pubmed_title>A systems pharmacology model for inflammatory bowel disease.</pubmed_title><pubmed_authors>Balbas-Martinez Violeta V, Ruiz-Cerdá Leire L, Irurzun-Arana Itziar I, González-García Ignacio I, Vermeulen An A, Gómez-Mantilla José David JD, Trocóniz Iñaki F IF</pubmed_authors><description_synonyms>mode of action, Inflammatory Bowel Diseases, pharmacodynamics, pharmacologic action, mechanism of action, Bowel Diseases, inflammatory bowel disease., IBD, Inflammatory bowel disease, autoimmune bowel disorder, INFLAMM BOWEL DIS, Pharmacologies, Inflammatory, Inflammatory Bowel Disease</description_synonyms><pubmed_title_synonyms>mode of action, Inflammatory Bowel Diseases, pharmacodynamics, pharmacologic action, mechanism of action, Bowel Diseases, inflammatory bowel disease., IBD, Inflammatory bowel disease, autoimmune bowel disorder, INFLAMM BOWEL DIS, Pharmacologies, Inflammatory, Inflammatory Bowel Disease</pubmed_title_synonyms><name_synonyms>Inflammatory bowel disease, autoimmune bowel disorder, INFLAMM BOWEL DIS, Inflammatory Bowel Diseases, Bowel Diseases, Inflammatory, psychogenic IBS., IBD, Inflammatory Bowel Disease, inflammatory bowel disease</name_synonyms><pubmed_abstract_synonyms>Biological Markers, Viral Marker, Granulocyte, mononuclear leukocyte, Inflammations, Surrogate Endpoints, determination, Il-2, Laboratory, Biochemical, Endpoint, fam:IL-17, Serum, Pharmaceutical Development, MAGE-E1 antigen, Laboratory Markers, Interleukin II, Pheresis, diseases, IL-2, dorsal marginal zone, Biological, Inflammatory bowel disease, IL10X, diseases and disorders, RU-49637, Cytokine Synthesis Inhibitory Factor, Interleukine 2, treatment, human disease, inflammatory response, aldesleukin, IBD, Tissue, hypoplasia, CSIF-10, Lymphocyte Mitogenic Factor, Monocyte, Inflammatory Bowel Diseases, Immune, Markers, HCA1, Pharmaceutical, Viral Markers, polymorphonuclear leukocyte, disease management, T-Cell Stimulating Factor, Therapies, Homo sapiens disease, monocyte, RU 49637, nongranular leukocyte, Therapy, CTLA8, Viral, Surrogate Endpoint, Il17, typical plasmatocyte, Phereses, Biochemical Markers, Biologic Marker, results, T Cell Growth Factor, Incentive, IL10, Literatures, Prediction, Ro-23-6019, IL17, Marker, DAMAGE, Hepatocellular carcinoma-associated protein 1, Diseases, Henson's node, simple tissue, Target Prediction, CTLA-8, Disincentive, Ro 236019, End Points, Ro-236019, Ctla8, Immunologic, Laboratory Marker, Treatments, Il-10, disease, Biochemical Marker, T-cell growth factor, Ro236019, DMZ, autoimmune bowel disorder, TGIF, Innate, mMage-e1, Incentives, other disease, Inflammatory Response, Thymocyte Stimulating Factor, Logics, Clinical Markers, Clinical Marker, number, Blood Component Removals, Development, Medication, Ctla-8, Inflammatory Bowel Disease, presence, Surrogate End Points, Surrogate Markers, granular leucocyte, reduced, Ro 23 6019, inflammatory bowel disease, IL-10, disease or disorder, tiny, IL-17, Interleukin 10, Drug Target Prediction, agranular plasmatocyte, Biomarker, Motivations, Clinical, nodus primitivus, Biological Marker, Medication Development, Interleukin 2, inflammation, AI847422, non-neoplastic, Immunologic Markers, Innate Inflammatory Response, lamellocyte, Blood Component, stem node, IL2, disorder, Chronic, Disincentives, Inflammatory, Aphereses, Immunologic Marker, Lymphocyte, Biologic, Removal, small, Apheresis, Bowel Diseases, granular leukocyte, Alpha-dystrobrevin-associated MAGE Protein, Serum Markers, disorders, CSIF, End Point, medical condition, GVHDS, Immune Marker, presence., count in organism, TCGF, Surrogate End Point, chemical analysis, condition, lymphokine, Drug Target Predictions, Biologic Markers, Serum Marker, Mitogenic Factor, nodal stem, underdeveloped, RGD1560259, Surrogate, RU49637, Endpoints, T-Cell Growth Factor, INFLAMM BOWEL DIS, IL10A, cytokine synthesis inhibitory factor, Surrogate Marker, Drug, Computational Prediction of Drug-Target Interactions, Cytokine formation-inhibiting factor (mouse clone F115 protein moiety reduced), IL-17A, Therapeutic, Innate Inflammatory Responses, psychogenic IBS, Drug Target, granulocyte, T Cell Stimulating Factor, Treatment, assay, Immune Markers</pubmed_abstract_synonyms></additional><is_claimable>false</is_claimable><name>Inflammatory Bowel Disease (IBD) Model</name><description>A Systems Pharmacology model for Inflammatory Bowel Disease</description><dates><created>2017-09-18</created><publication></publication><submission>2018-04-05</submission><last_modified>2018-04-05</last_modified></dates><accession>8558</accession><cross_references><pubmed>29513758</pubmed></cross_references></HashMap>