Evaluation of the drug-drug interaction potential of brigatinib using a physiologically-based pharmacokinetic modeling approach

被引:0
|
作者
Hanley, Michael J. [1 ]
Yeo, Karen Rowland [2 ]
Tugnait, Meera [3 ]
Iwasaki, Shinji [4 ]
Narasimhan, Narayana [5 ]
Zhang, Pingkuan [6 ]
Venkatakrishnan, Karthik [7 ]
Gupta, Neeraj [1 ,8 ]
机构
[1] Takeda Dev Ctr Amer Inc, Clin Pharmacol, Lexington, MA 02421 USA
[2] Certara UK Ltd, Simcyp Div, Sheffield, S Yorkshire, England
[3] Cerevel Therapeut, Clin Pharmacol, Cambridge, MA USA
[4] Takeda Dev Ctr Amer Inc, Global DMPK, Lexington, MA USA
[5] Theseus Pharmaceut, DMPK & Preclin Safety, Cambridge, MA USA
[6] Takeda Dev Ctr Amer Inc, Clin Sci, Lexington, MA 02421 USA
[7] EMD Serono Res & Dev Inst Inc, Quantitat Pharmacol, Billerica, MA USA
[8] Takeda Dev Ctr Amer Inc, Quantitat Clin Pharmacol, 95 Hayden Ave, Lexington, MA 02421 USA
来源
关键词
ALK-POSITIVE NSCLC; REGULATORY DECISION-MAKING; CELL LUNG-CANCER; TRANSPORTERS; PREDICTION; INHIBITORS; IMPACT; SUBMISSIONS; CRIZOTINIB; ALECTINIB;
D O I
10.1002/psp4.13106
中图分类号
R9 [药学];
学科分类号
1007 ;
摘要
Brigatinib is an oral anaplastic lymphoma kinase (ALK) inhibitor approved for the treatment of ALK-positive metastatic non-small cell lung cancer. In vitro studies indicated that brigatinib is primarily metabolized by CYP2C8 and CYP3A4 and inhibits P-gp, BCRP, OCT1, MATE1, and MATE2K. Clinical drug-drug interaction (DDI) studies with the strong CYP3A inhibitor itraconazole or the strong CYP3A inducer rifampin demonstrated that CYP3A-mediated metabolism was the primary contributor to overall brigatinib clearance in humans. A physiologically-based 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-time curve from time 0 to infinity [AUC(infinity)] ratio [with/without itraconazole]: predicted 1.86; observed 2.01) and rifampin (AUC(infinity) 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(infinity) by similar to 40%, whereas moderate CYP3A inducers (e.g., efavirenz) may decrease brigatinib AUC(infinity) by similar to 50%. Simulations of potential transporter-mediated DDIs predicted that brigatinib may increase systemic exposures (AUC(infinity)) of P-gp substrates (e.g., digoxin and dabigatran) by 15%-43% and MATE1 substrates (e.g., metformin) by up to 29%; however, negligible effects were predicted on BCRP-mediated efflux and OCT1-mediated 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.
引用
收藏
页码:624 / 637
页数:14
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