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Both models were built and thoroughly evaluated for their application in drug\u2013drug interaction (<jats:styled-content style=\"fixed-case\">DDI<\/jats:styled-content>) prediction in a network of perpetrator and victim drugs, combining them with previously developed models of caffeine (sensitive index <jats:styled-content style=\"fixed-case\">CYP<\/jats:styled-content>1A2 substrate), rifampicin (moderate <jats:styled-content style=\"fixed-case\">CYP<\/jats:styled-content>1A2 inducer), and midazolam (sensitive index <jats:styled-content style=\"fixed-case\">CYP<\/jats:styled-content>3A4 substrate). Simulation of all reported clinical <jats:styled-content style=\"fixed-case\">DDI<\/jats:styled-content> studies for combinations of these five drugs shows that the presented models reliably predict the observed drug concentrations, resulting in seven of eight of the predicted <jats:styled-content style=\"fixed-case\">DDI<\/jats:styled-content> area under the plasma curve (<jats:styled-content style=\"fixed-case\">AUC<\/jats:styled-content>) ratios (<jats:styled-content style=\"fixed-case\">AUC<\/jats:styled-content> during <jats:styled-content style=\"fixed-case\">DDI<\/jats:styled-content>\/<jats:styled-content style=\"fixed-case\">AUC<\/jats:styled-content> control) and seven of seven of the predicted <jats:styled-content style=\"fixed-case\">DDI<\/jats:styled-content> peak plasma concentration (C<jats:sub>max<\/jats:sub>) ratios (C<jats:sub>max<\/jats:sub> during <jats:styled-content style=\"fixed-case\">DDI<\/jats:styled-content>\/C<jats:sub>max<\/jats:sub> control) within twofold of the observed values. Therefore, the models are considered qualified for <jats:styled-content style=\"fixed-case\">DDI<\/jats:styled-content> prediction. All models are comprehensively documented and publicly available, as tools to support the drug development and clinical research community.<\/jats:p>","DOI":"10.1002\/psp4.12397","type":"journal-article","created":{"date-parts":[[2019,2,14]],"date-time":"2019-02-14T11:47:33Z","timestamp":1550144853000},"page":"296-307","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":37,"title":["Physiologically\u2010Based Pharmacokinetic Models for <scp>CYP<\/scp>1A2 Drug\u2013Drug Interaction Prediction: A Modeling Network of Fluvoxamine, Theophylline, Caffeine, Rifampicin, and Midazolam"],"prefix":"10.1002","volume":"8","author":[{"given":"Hannah","family":"Britz","sequence":"first","affiliation":[{"name":"Clinical Pharmacy Saarland University  Saarbr\u00fccken Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nina","family":"Hanke","sequence":"additional","affiliation":[{"name":"Clinical Pharmacy Saarland University  Saarbr\u00fccken Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Anke\u2010Katrin","family":"Volz","sequence":"additional","affiliation":[{"name":"Clinical Pharmacy Saarland University  Saarbr\u00fccken Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Olav","family":"Spigset","sequence":"additional","affiliation":[{"name":"Department of Clinical and Molecular Medicine Norwegian University of Science and Technology  Trondheim Norway"},{"name":"Department of Clinical Pharmacology St. Olav University Hospital  Trondheim Norway"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Matthias","family":"Schwab","sequence":"additional","affiliation":[{"name":"Dr. Margarete Fischer\u2010Bosch\u2010Institute of Clinical Pharmacology  Stuttgart Germany"},{"name":"Department of Clinical Pharmacology University Hospital T\u00fcbingen  T\u00fcbingen Germany"},{"name":"Department of Pharmacy and Biochemistry University T\u00fcbingen  T\u00fcbingen Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Thomas","family":"Eissing","sequence":"additional","affiliation":[{"name":"Clinical Pharmacometrics Bayer AG  Leverkusen Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Thomas","family":"Wendl","sequence":"additional","affiliation":[{"name":"Clinical Pharmacometrics Bayer AG  Leverkusen Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sebastian","family":"Frechen","sequence":"additional","affiliation":[{"name":"Clinical Pharmacometrics Bayer AG  Leverkusen Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Thorsten","family":"Lehr","sequence":"additional","affiliation":[{"name":"Clinical Pharmacy Saarland University  Saarbr\u00fccken Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2019,3,13]]},"reference":[{"key":"e_1_2_10_1_1","doi-asserted-by":"publisher","DOI":"10.1208\/s12248-009-9127-y"},{"key":"e_1_2_10_2_1","first-page":"414","article-title":"Interindividual variations in human liver cytochrome P\u2010450 enzymes involved in the oxidation of drugs, carcinogens and toxic chemicals: studies with liver microsomes of 30 Japanese and 30 caucasians","volume":"270","author":"Shimada T.","year":"1994","journal-title":"J. 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