Your browser doesn't support javascript.
loading
Evaluation of the drug-drug interaction potential of brigatinib using a physiologically-based pharmacokinetic modeling approach.
Hanley, Michael J; Yeo, Karen Rowland; Tugnait, Meera; Iwasaki, Shinji; Narasimhan, Narayana; Zhang, Pingkuan; Venkatakrishnan, Karthik; Gupta, Neeraj.
Afiliação
  • Hanley MJ; Clinical Pharmacology, Takeda Development Center Americas, Inc., Lexington, Massachusetts, USA.
  • Yeo KR; Simcyp Division, Certara UK Limited, Sheffield, South Yorkshire, UK.
  • Tugnait M; Clinical Pharmacology, Cerevel Therapeutics, Cambridge, Massachusetts, USA.
  • Iwasaki S; Global DMPK, Takeda Development Center Americas, Inc., Lexington, Massachusetts, USA.
  • Narasimhan N; DMPK & Preclinical Safety, Theseus Pharmaceuticals, Cambridge, Massachusetts, USA.
  • Zhang P; Clinical Science, Takeda Development Center Americas, Inc., Lexington, Massachusetts, USA.
  • Venkatakrishnan K; Quantitative Pharmacology, EMD Serono Research & Development Institute, Inc., Billerica, Massachusetts, USA.
  • Gupta N; Clinical Pharmacology, Takeda Development Center Americas, Inc., Lexington, Massachusetts, USA.
CPT Pharmacometrics Syst Pharmacol ; 13(4): 624-637, 2024 04.
Article em En | MEDLINE | ID: mdl-38288787
ABSTRACT
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∞] ratio [with/without itraconazole] predicted 1.86; observed 2.01) and rifampin (AUC∞ 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∞ by ~40%, whereas moderate CYP3A inducers (e.g., efavirenz) may decrease brigatinib AUC∞ by ~50%. Simulations of potential transporter-mediated DDIs predicted that brigatinib may increase systemic exposures (AUC∞) 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.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Compostos Organofosforados / Pirimidinas / Carcinoma Pulmonar de Células não Pequenas / Neoplasias Pulmonares Tipo de estudo: Guideline / Prognostic_studies Limite: Humans Idioma: En Revista: CPT Pharmacometrics Syst Pharmacol Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Compostos Organofosforados / Pirimidinas / Carcinoma Pulmonar de Células não Pequenas / Neoplasias Pulmonares Tipo de estudo: Guideline / Prognostic_studies Limite: Humans Idioma: En Revista: CPT Pharmacometrics Syst Pharmacol Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Estados Unidos