Regimen-Specific Population Pharmacokinetics of Isoniazid with and Without Rifamycin: A Bayesian Modeling Analysis of 6H, 3HR, and 3H2P2 Regimens.

Background

Isoniazid (INH) remains a cornerstone of tuberculosis (TB) prevention and treatment, administered either as monotherapy or in combination with rifamycin-containing regimens. In this study, the preventive regimens analyzed included 6 months of daily INH monotherapy (6H), 3 months of daily INH plus rifampicin (3HR), and 3 months of twice-weekly INH plus rifapentine (3H2P2). Despite the adoption of shorter-course regimens, substantial inter-individual variability (IIV) in INH exposure persists, potentially impacting both therapeutic efficacy and toxicity. A quantitative, regimen-specific characterization of INH pharmacokinetics is therefore critical to support model-informed dosing strategies.

Methods

Population pharmacokinetic models were developed separately for INH administered as 6H, 3HR, and 3H2P2. The models characterized absorption, clearance, and IIV of INH, while accounting for co-administered rifamycin. The effects of N-acetyltransferase 2 (NAT2) acetylator phenotype and relevant clinical covariates were systematically evaluated. Model performance was assessed using goodness-of-fit diagnostics, posterior predictive checks, and visual predictive checks. Population pharmacokinetic models were developed using a Bayesian nonlinear mixed-effects framework implemented in Stan through CmdStanR version 0.9.0, with additional data processing, statistical summaries, and visualization performed using R version 4.2.3.

Results

INH pharmacokinetics were adequately described by regimen-specific models, revealing distinct differences in absorption and variability across regimens. Typical INH apparent oral clearance (CL/F) estimates were 21.83 L/h for 6H, 26.32 L/h for 3HR, and 25.98 L/h for 3H2P2. NAT2 phenotype was a major determinant of INH clearance across regimens: compared with intermediate acetylators, slow acetylators showed 35.4% lower CL/F, whereas fast acetylators showed 48.4% higher CL/F, indicating higher INH exposure in slow acetylators and lower exposure in fast acetylators. Body weight also influenced INH pharmacokinetics. Co-administration with rifampicin or rifapentine influenced INH pharmacokinetics in a manner consistent with reduced exposure in rifamycin-containing regimens, particularly among fast acetylators.

Conclusions

Regimen-specific population pharmacokinetic modeling elucidated clinically relevant differences in INH exposure across commonly used preventive and treatment regimens. These findings highlight the importance of accounting for regimen- and genotype-specific effects when optimizing INH dosing and provide a quantitative framework for future model-informed precision dosing approaches in TB care.