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dc.contributor.authorWicha, Sebastian G.
dc.contributor.authorClewe, Oskar
dc.contributor.authorSvensson, Robin J.
dc.contributor.authorGillespie, Stephen H.
dc.contributor.authorHu, Yanmin
dc.contributor.authorCoates, Anthony R.m.
dc.contributor.authorSimonsson, Ulrika S.h.
dc.date.accessioned2018-06-26T11:30:06Z
dc.date.available2018-06-26T11:30:06Z
dc.date.issued2018-06-19
dc.identifier.citationWicha , S G , Clewe , O , Svensson , R J , Gillespie , S H , Hu , Y , Coates , A R M & Simonsson , U S H 2018 , ' Forecasting clinical dose-response from pre-clinical studies in tuberculosis research - translational predictions with rifampicin ' , Clinical Pharmacology & Therapeutics , vol. Early View . https://doi.org/10.1002/cpt.1102en
dc.identifier.issn0009-9236
dc.identifier.otherPURE: 252974692
dc.identifier.otherPURE UUID: d6b8c6f4-d40e-4fc9-811d-d94b3118b714
dc.identifier.othercrossref: 10.1002/cpt.1102
dc.identifier.otherScopus: 85049597221
dc.identifier.otherORCID: /0000-0001-6537-7712/work/46152091
dc.identifier.otherWOS: 000449645100021
dc.identifier.urihttps://hdl.handle.net/10023/14604
dc.descriptionThis work was funded by: The Swedish Research Council (grant number 521‐2011‐3442) and the Innovative Medicines Initiative Joint Undertaking (www.imi.europe.eu) under grant agreement 115337, resources of which are composed of financial contribution from the European Union's Seventh Framework Programme (FP7/2007‐2013) and EFPIA companies' in kind contribution.en
dc.description.abstractA crucial step for accelerating tuberculosis drug development is bridging the gap between pre‐clinical and clinical trials. In this study, we developed a pre‐clinical model‐informed translational approach to predict drug effects across pre‐clinical systems and early clinical trials using the in vitro‐based Multistate Tuberculosis Pharmacometric (MTP) model using rifampicin as an example. The MTP model predicted rifampicin biomarker response observed in (i) a hollow‐fiber infection model, (ii) a murine study to determine PK/PD indices, and (iii) several clinical phase IIa early bactericidal activity (EBA) studies. In addition, we predicted rifampicin biomarker response at high doses of up to 50 mg/kg, leading to an increased median EBA0‐2 days (90% prediction interval) of 0.513 log CFU/mL/day (0.310; 0.701) compared to the standard dose of 10 mg/kg of 0.181 log/CFU/mL/day (0.076; 0.483). These results suggest that the translational approach could assist in the selection of drugs and doses in early‐phase clinical tuberculosis trials.
dc.language.isoeng
dc.relation.ispartofClinical Pharmacology & Therapeuticsen
dc.rights© 2018 The Authors Clinical Pharmacology & Therapeutics published by Wiley Periodicals, Inc. on behalf of American Society for Clinical Pharmacology and Therapeutics This is an open access article under the terms of the Creative Commons Attribution‐NonCommercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.en
dc.subjectForward translationalen
dc.subjectTuberculosisen
dc.subjectRifampicinen
dc.subjectRA0421 Public health. Hygiene. Preventive Medicineen
dc.subjectRM Therapeutics. Pharmacologyen
dc.subjectNDASen
dc.subjectSDG 3 - Good Health and Well-beingen
dc.subject.lccRA0421en
dc.subject.lccRMen
dc.titleForecasting clinical dose-response from pre-clinical studies in tuberculosis research - translational predictions with rifampicinen
dc.typeJournal articleen
dc.contributor.sponsorEuropean Commissionen
dc.description.versionPublisher PDFen
dc.contributor.institutionUniversity of St Andrews. School of Medicineen
dc.contributor.institutionUniversity of St Andrews. Infection and Global Health Divisionen
dc.contributor.institutionUniversity of St Andrews. Global Health Implementation Groupen
dc.contributor.institutionUniversity of St Andrews. Gillespie Groupen
dc.contributor.institutionUniversity of St Andrews. Biomedical Sciences Research Complexen
dc.contributor.institutionUniversity of St Andrews. Infection Groupen
dc.identifier.doihttps://doi.org/10.1002/cpt.1102
dc.description.statusPeer revieweden
dc.identifier.grantnumberen


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