biostudies-otherUnknown174Steven WattersonBritish journal of pharmacology4362-4382https://www.ebi.ac.uk/biostudies/studies/MODEL1506220000biostudies-other28910500Steven WattersonfalseBenson2017 - Systems Pharmacology Multidrug (cholesterol biosynthesis pathway)<notes xmlns="http://www.sbml.org/sbml/level2/version4"> <body xmlns="http://www.w3.org/1999/xhtml"> <div class="dc:title">BensonWattersonetal_SystemsPharmacology_Multidrug</div><div class="dc:bibliographicCitation"> <p>This model is described in the article:</p> <div class="bibo:title"> <a href="http://identifiers.org/pubmed/28910500" title="Access to this publication">Is systems pharmacology ready to impact upon therapy development? A study on the cholesterol biosynthesis pathway.</a> </div> <div class="bibo:authorList">Benson H, Watterson S, Sharman J, Mpamhanga C, Parton A, Southan C, Harmar A, Ghazal P.</div> <div class="bibo:Journal">Br. J. Pharmacol. 2017 Sep; :</div> <p>Abstract:</p> <div class="bibo:abstract"> <p>An ever-growing wealth of information on current drugs and their pharmacological effects is available from online databases. As our understanding of systems biology increases, we have the opportunity to predict, model and quantify how drug combinations can be introduced that outperform conventional single-drug therapies. Here, we explore the feasibility of such systems pharmacology approaches with an analysis of the mevalonate branch of the cholesterol biosynthesis pathway.Using open online resources, we assembled a computational model of the mevalonate pathway and compiled a set of inhibitors directed against targets in this pathway. We used computational optimisation to identify combination and dose options that show not only maximal efficacy of inhibition on the cholesterol producing branch but also minimal impact on the geranylation branch, known to mediate the side effects of pharmaceutical treatment.We describe serious impediments to systems pharmacology studies arising from limitations in the data, incomplete coverage and inconsistent reporting. By curating a more complete dataset, we demonstrate the utility of computational optimization for identifying multi-drug treatments with high efficacy and minimal off-target effects.We suggest solutions that facilitate systems pharmacology studies, based on the introduction of standards for data capture that increase the power of experimental data. We propose a systems pharmacology work-flow for the refinement of data and the generation of future therapeutic hypotheses.</p> </div></div><div class="dc:publisher"> <p>This model is hosted on <a href="http://www.ebi.ac.uk/biomodels/">BioModels Database</a> and identified by: <a href="http://identifiers.org/biomodels.db/MODEL1506220000">MODEL1506220000</a>.</p> <p>To cite BioModels Database, please use: <a href="http://identifiers.org/pubmed/25414348" target="_blank">Chelliah V et al. BioModels: ten-year anniversary. Nucl. Acids Res. 2015, 43(Database issue):D542-8</a>.</p></div><div class="dc:license"> <p>To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to <a href="http://creativecommons.org/publicdomain/zero/1.0/" title="Access to: CC0 1.0 Universal (CC0 1.0), Public Domain Dedication">CC0 Public Domain Dedication</a> for more information.</p></div></body> </notes>2015-06-22T00:00:00Z2025-07-15T09:15:52.834Z2025-03-30T21:55:25.306ZMODEL150622000028910500MAMO_0000046