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In\u00a0vitro studies indicated that brigatinib is primarily metabolized by CYP2C8 and CYP3A4 and inhibits P\u2010gp, BCRP, OCT1, MATE1, and MATE2K. Clinical drug\u2013drug interaction (DDI) studies with the strong CYP3A inhibitor itraconazole or the strong CYP3A inducer rifampin demonstrated that CYP3A\u2010mediated metabolism was the primary contributor to overall brigatinib clearance in humans. A physiologically\u2010based pharmacokinetic (PBPK) model for brigatinib was developed to predict potential DDIs, including the effect of moderate CYP3A inhibitors or inducers on brigatinib pharmacokinetics (PK) and the effect of brigatinib on the PK of transporter substrates. The developed model was able to predict clinical DDIs with itraconazole (area under the plasma concentration\u2013time curve from time 0 to infinity [AUC<jats:sub>\u221e<\/jats:sub>] ratio [with\/without itraconazole]: predicted 1.86; observed 2.01) and rifampin (AUC<jats:sub>\u221e<\/jats:sub> ratio [with\/without rifampin]: predicted 0.16; observed 0.20). Simulations using the developed model predicted that moderate CYP3A inhibitors (e.g., verapamil and diltiazem) may increase brigatinib AUC<jats:sub>\u221e<\/jats:sub> by ~40%, whereas moderate CYP3A inducers (e.g., efavirenz) may decrease brigatinib AUC<jats:sub>\u221e<\/jats:sub> by ~50%. Simulations of potential transporter\u2010mediated DDIs predicted that brigatinib may increase systemic exposures (AUC<jats:sub>\u221e<\/jats:sub>) of P\u2010gp substrates (e.g., digoxin and dabigatran) by 15%\u201343% and MATE1 substrates (e.g., metformin) by up to 29%; however, negligible effects were predicted on BCRP\u2010mediated efflux and OCT1\u2010mediated uptake. The PBPK analysis results informed dosing recommendations for patients receiving moderate CYP3A inhibitors (40% brigatinib dose reduction) or inducers (up to 100% increase in brigatinib dose) during treatment, as reflected in the brigatinib prescribing information.<\/jats:p>","DOI":"10.1002\/psp4.13106","type":"journal-article","created":{"date-parts":[[2024,1,30]],"date-time":"2024-01-30T11:49:21Z","timestamp":1706615361000},"page":"624-637","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Evaluation of the drug\u2013drug interaction potential of brigatinib using a physiologically\u2010based pharmacokinetic modeling approach"],"prefix":"10.1002","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9266-2797","authenticated-orcid":false,"given":"Michael J.","family":"Hanley","sequence":"first","affiliation":[{"name":"Clinical Pharmacology, Takeda Development Center Americas, Inc.  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