Limited sampling strategies for determining the area under the plasma concentration-time curve for isoniazid might be a valuable approach for optimizing treatment in adult patients with tuberculosis.

This study aimed to develop clinically feasible models of limited sampling strategy (LSS) for estimation of the area under the concentration-time curve (AUC) for isoniazid, that could be applied easily in daily clinical practice for dosage adjustment in adult patients with tuberculosis. Isoniazid plasma concentrations (n = 1665) from 185 adult tuberculous patients were used for the development and validation of LSS models to estimate AUC following administration of the standard 5 mg/kg dose of isoniazid. Population pharmacokinetic analysis for appropriate estimation of isoniazid pharmacokinetic parameters was performed in a modelling group (n = 100). The Bayesian estimates of AUC (AUC) obtained for each individual were used as the dependent variable in the regression analysis for the development of various LSS models. The LSS models were validated in a separate cohort (n = 85). Several three and four time point LSS models were built and tested. Model H (AUC = -1.88 + 1.05 × C + 0.78 × C + 9.44 × C) and Model I (AUC= -0.65 + 1.00 × C + 1.94 × C + 15.45 × C) had the best performances [adj-R = 0.93, median prediction error (MPE) = -0.20, root median squared prediction error (RMSE) = 4.65 for Model H; adj-R = 0.96, MPE = -0.05 RMSE = 3.56 for Model I]. The very high R values (≥0.94) of these regression equations in the validation cohort confirmed their high reliability. These LSS models could be applied in the context of therapeutic drug monitoring programmes aiming to personalize isoniazid dosing regimens for adult patients with tuberculosis.