Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/33885
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dc.contributor.authorSher, Annaen_UK
dc.contributor.authorNiederer, Steven Aen_UK
dc.contributor.authorMirams, Gary Ren_UK
dc.contributor.authorKirpichnikova, Annaen_UK
dc.contributor.authorAllen, Richarden_UK
dc.contributor.authorPathmanathan, Prasen_UK
dc.contributor.authorGavaghan, David Jen_UK
dc.contributor.authorVan Der Graaf, Piet Hen_UK
dc.contributor.authorNoble, Denisen_UK
dc.date.accessioned2022-01-26T01:03:40Z-
dc.date.available2022-01-26T01:03:40Z-
dc.date.issued2022-03en_UK
dc.identifier.other39en_UK
dc.identifier.urihttp://hdl.handle.net/1893/33885-
dc.description.abstractThere is an inherent tension in Quantitative Systems Pharmacology (QSP) between the need to incorporate mathematical descriptions of complex physiology and drug targets with the necessity of developing robust, predictive and well-constrained models. In addition to this there is no "gold standard" for model development and assessment in QSP. Moreover, there can be confusion over terminology such as model and parameter identifiability; complex and simple models; virtual populations; and other concepts, which leads to potential miscommunication and misapplication of methodologies within modelling communities, both the QSP community and related disciplines. This perspective article highlights the pros and cons of using simple (often identifiable) vs. complex (more physiologically detailed but often non-identifiable) models, as well as aspects of parameter identifiability, sensitivity and inference methodologies for model development and analysis. The paper distills the central themes of the issue of identifiability and optimal model size and discusses open challenges.en_UK
dc.language.isoenen_UK
dc.publisherBMCen_UK
dc.relationSher A, Niederer SA, Mirams GR, Kirpichnikova A, Allen R, Pathmanathan P, Gavaghan DJ, Van Der Graaf PH & Noble D (2022) A Quantitative Systems Pharmacology perspective on the importance of parameter identifiability. Bulletin of Mathematical Biology, 84 (3), Art. No.: 39. https://doi.org/10.1007/s11538-021-00982-5en_UK
dc.rightsThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.en_UK
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en_UK
dc.subjectQuantitative Systems Pharmacologyen_UK
dc.subjectmodel identifiabilityen_UK
dc.subjectmodel developmenten_UK
dc.titleA Quantitative Systems Pharmacology perspective on the importance of parameter identifiabilityen_UK
dc.typeJournal Articleen_UK
dc.identifier.doi10.1007/s11538-021-00982-5en_UK
dc.identifier.pmid35132487en_UK
dc.citation.jtitleBulletin of Mathematical Biologyen_UK
dc.citation.issn1522-9602en_UK
dc.citation.issn0092-8240en_UK
dc.citation.volume84en_UK
dc.citation.issue3en_UK
dc.citation.publicationstatusPublisheden_UK
dc.citation.peerreviewedRefereeden_UK
dc.type.statusVoR - Version of Recorden_UK
dc.contributor.funderThe Wellcome Trusten_UK
dc.citation.date07/02/2022en_UK
dc.contributor.affiliationPfizer Global Research and Development - USAen_UK
dc.contributor.affiliationKing's College Londonen_UK
dc.contributor.affiliationUniversity of Nottinghamen_UK
dc.contributor.affiliationMathematicsen_UK
dc.contributor.affiliationPfizer Global Research and Development - USAen_UK
dc.contributor.affiliationU. S. Food and Drug Administrationen_UK
dc.contributor.affiliationUniversity of Oxforden_UK
dc.contributor.affiliationCertaraen_UK
dc.contributor.affiliationUniversity of Oxforden_UK
dc.identifier.isiWOS:000752324500001en_UK
dc.identifier.scopusid2-s2.0-85124322294en_UK
dc.identifier.wtid1777203en_UK
dc.contributor.orcid0000-0001-5153-7375en_UK
dc.date.accepted2021-11-30en_UK
dcterms.dateAccepted2021-11-30en_UK
dc.date.filedepositdate2022-01-25en_UK
dc.subject.tagComputational Systems Biologyen_UK
dc.subject.tagOptimisation and Biological Modellingen_UK
rioxxterms.apcnot requireden_UK
rioxxterms.typeJournal Article/Reviewen_UK
rioxxterms.versionVoRen_UK
local.rioxx.authorSher, Anna|en_UK
local.rioxx.authorNiederer, Steven A|en_UK
local.rioxx.authorMirams, Gary R|en_UK
local.rioxx.authorKirpichnikova, Anna|0000-0001-5153-7375en_UK
local.rioxx.authorAllen, Richard|en_UK
local.rioxx.authorPathmanathan, Pras|en_UK
local.rioxx.authorGavaghan, David J|en_UK
local.rioxx.authorVan Der Graaf, Piet H|en_UK
local.rioxx.authorNoble, Denis|en_UK
local.rioxx.projectProject ID unknown|The Wellcome Trust|en_UK
local.rioxx.freetoreaddate2022-01-25en_UK
local.rioxx.licencehttp://creativecommons.org/licenses/by/4.0/|2022-01-25|en_UK
local.rioxx.filenameSher2022_Article_AQuantitativeSystemsPharmacolo.pdfen_UK
local.rioxx.filecount1en_UK
local.rioxx.source1522-9602en_UK
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