PBPK modeling predicts rilzabrutinib dose adjustments using BTK occupancy for CYP3A4 interactions and hepatic impairment

ratios within the acceptable range of 1.5-fold error and 15% difference between observed and predicted BO data. The predicted ratios for DDIs and hepatic impairment scenarios demonstrated good agreement with clinical observations. Based on BO as the efficacy criterion, DDI simulations predicted significant interactions with strong CYP3A4 inhibitors, necessitating dose reductions for RIL when co-administered with ritonavir (RIT; 25 mg BID or 50 mg OD), itraconazole (ITR; 50 mg BID), or clarithromycin (CLA; 75 mg BID). For moderate inhibitors like fluconazole (FLUC) or fluvoxamine (FLUV), dose adjustments to 250 mg BID and 300 mg BID, respectively, were required to maintain efficacy. The model advised against co-administration with strong inducers like rifampicin (RIF) or moderate inducers like efavirenz (EFA) and rifabutin (RIFA), though increasing the dose to 800 mg BID with RIFA could overcome the inductive effect. Hepatic impairment simulations predicted increased RIL exposure, requiring dose reductions to 300 mg BID, 200 mg BID, and 75 mg BID for mild, moderate, and severe impairment, respectively, to achieve target BO levels. The PBPK model for RIL demonstrated predictive capabilities for PK and BO profiles under various scenarios. This model can guide clinical decision-making to optimize RIL dosing in patients with and without DDIs and hepatic impairment.

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Journal
Scientific Reports
Published
2026-05-01
DOI
https://doi.org/10.1038/s41598-026-50990-5
Primary Topic
Pharmacogenetics and Drug Metabolism
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article
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article

PBPK modeling predicts rilzabrutinib dose adjustments using BTK occupancy for CYP3A4 interactions and hepatic impairment

Lirong Xiao, Dehu Lu, Zhiwei Yan, Xiaoping Yan
Scientific Reports
Pharmacogenetics and Drug Metabolism
article

PBPK modeling predicts rilzabrutinib dose adjustments using BTK occupancy for CYP3A4 interactions and hepatic impairment

Lirong Xiao, Dehu Lu, Zhiwei Yan, Xiaoping Yan
article en

Abstract

ratios within the acceptable range of 1.5-fold error and 15% difference between observed and predicted BO data. The predicted ratios for DDIs and hepatic impairment scenarios demonstrated good agreement with clinical observations. Based on BO as the efficacy criterion, DDI simulations predicted significant interactions with strong CYP3A4 inhibitors, necessitating dose reductions for RIL when co-administered with ritonavir (RIT; 25 mg BID or 50 mg OD), itraconazole (ITR; 50 mg BID), or clarithromycin (CLA; 75 mg BID). For moderate inhibitors like fluconazole (FLUC) or fluvoxamine (FLUV), dose adjustments to 250 mg BID and 300 mg BID, respectively, were required to maintain efficacy. The model advised against co-administration with strong inducers like rifampicin (RIF) or moderate inducers like efavirenz (EFA) and rifabutin (RIFA), though increasing the dose to 800 mg BID with RIFA could overcome the inductive effect. Hepatic impairment simulations predicted increased RIL exposure, requiring dose reductions to 300 mg BID, 200 mg BID, and 75 mg BID for mild, moderate, and severe impairment, respectively, to achieve target BO levels. The PBPK model for RIL demonstrated predictive capabilities for PK and BO profiles under various scenarios. This model can guide clinical decision-making to optimize RIL dosing in patients with and without DDIs and hepatic impairment.

Scientific Reports
Fujian Medical University (CN), Peking University (CN), Zhangzhou Municipal Hospital of Fujian Province (CN), First Affiliated Hospital of Fujian Medical University (CN), 175th Hospital of People's Liberation Army (CN), Peking University International Hospital (CN), Zhangzhou Vocational and Technical College (CN)
Peace, Justice and strong institutions
Openalex Percentile: Top 11%
Pharmacogenetics and Drug Metabolism
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PBPK modeling predicts rilzabrutinib dose adjustments using BTK occupancy for CYP3A4 interactions and hepatic impairment — Lirong Xiao, Dehu Lu, et al. · Scientific Reports (2026) | TGRS Research Map | TGRS