Development of a population pharmacokinetic model and Bayesian estimators for isoniazid in Tunisian tuberculosis patients.

This study aimed to develop a population pharmacokinetic model using full pharmacokinetic (PK) profiles of isoniazid (INH) taking into account demographic and genetic covariates and to develop Bayesian estimators for predicting INH area under the curve (AUC) in Tunisian tuberculosis patients. The INH concentrations in the building data set were fitted using a one- to three-compartment model. The impact of the different covariates was assessed on the PK parameters of the best model. The best limited sampling strategy (LSS) for estimating the INH AUC was selected by comparing the predicted values to an independent data set. INH PK was best described using a three-compartment model with lag-time absorption. The different studied covariates did not have any impact on the PK parameters of the building model. The Bayesian estimation using one-point concentrations gave the lowest values of prediction errors for the C3 LSS model. This model could be sufficient in routine activity for INH monitoring in this population.

Clinical and genetic influencing factors on clozapine pharmacokinetics in Tunisian schizophrenic patients.

Clozapine (Clz) is an atypical antipsychotic, which its pharmacokinetics can be influenced by several factors. The CYP1A2 and CYP2C19, major enzymes implicated in Clz metabolism, present an interethnic variation on their activity caused by single nucleotide polymorphisms (SNPs). The present study investigated the influence of genetic and nongenetic factors on Clz pharmacokinetics in a southern Mediterranean population. We included adult Tunisian schizophrenic patients having received Clz and undergone a therapeutic drug monitoring (TDM) of Clz by morning C0 monitoring. The genomic DNA was extracted using a salting-out procedure. CYP1A2*1F (rs762551;-163C>A), CYP1A2*1C (rs2069514;-3860 G>A) and CYP 2C19*2 (rs4244285; 681G>A) was analyzed using PCR-RFLP. Fifty-one patients were enrolled in the study. The mutant allele (CYP1A2*1F) was the most frequently detected (58.8%). For CYP1A2*1F, Clz dose-normalized (C0/D ratio) was as high as 1.28 ± 0.37 in CC versus 0.67 ± 0.32 ng mL-1 per mg day-1 in AA group (p < 0.001). The influence of genetic (CYP1A2*1F, CYP1A2*1C and CYP2C19*2) and nongenetic parameters (age, weight, gender, tobacco, coffee, and alcohol consumption) on the variation of the Clz C0/D ratio was investigated. Only the CYP1A2*1 F polymorphism correlates significantly with the Clz C0/D variation and could explain 24% of its variability. Our data support a critical role of the CYP1A2 -163C>A on the variation of Clz exposure in Tunisian schizophrenic patients. Considering its narrow therapeutic range, CYP1A2 genotyping combined with TDM of Clz may improve efficacy and safety of this drug. Further studies are needed to investigate this issue.

Isoniazid Therapeutic Drug Monitoring in Tunisian Patients With Tuberculosis.

A regular therapeutic drug monitoring (TDM) of isoniazid could be useful to predict the acetylation profile and to prescribe doses associated with optimal efficacy and safety. We aimed to assess the usefulness of isoniazid TDM in the Tunisian population, to describe the acetylation profile distribution in this population, and to investigate the influence of certain parameters on acetylation phenotype. We performed a retrospective study including Tunisian patients with tuberculosis underwent an isoniazid TDM. Isoniazid concentrations were measured 3 hours after drug intake (C3 ). Subsequent isoniazid doses were adjusted to maintain the C3 within the recommended target (1-2 µg/mL). Patients were qualified as slow acetylators (SAs) or rapid acetylators (RAs) according to their acetylation index. Among the 255 patients, 58% were SAs and 42% were RAs. Of all patients, only 30.6% had a C3 value within the target range. A dose adjustment has been performed for patients with C3 outside the target range. C3 was controlled in 77 patients. It became within the target range in 39 patients (50.6%). The median recommended isoniazid weight doses for SAs and RAs were 2.1 ± 0.7 mg/kg and 4.2 ± 1.4 mg/kg, respectively. The multivariate analysis showed that body weight, C3, and C3 /isoniazid dose were found to be significantly different between the 2 acetylation groups. In the pediatric group, only 9 had a C3 value within the target range, and all of them were RAs. The irrevocable interest of isoniazid TDM has been shown in Tunisian patients with tuberculosis, in both adult and pediatric patients, as isoniazid demonstrates an unpredictable pharmacokinetic profile.

Limited sampling strategy for predicting isoniazid exposure in patients with extrapulmonary tuberculosis.

WHAT IS KNOWN AND OBJECTIVE: Limited sampling strategies (LSS), using few sampling times after dosing, have been used to reliably predict the isoniazid area under the 24-hour concentration-time curve (AUC). Experience with isoniazid is very limited, and no LSS has been developed in south-Mediterranean populations. Hence, we aimed to develop an accurate and convenient LSS for predicting isoniazid AUC in Tunisian patients with extrapulmonary tuberculosis. METHODS: Pharmacokinetic profiles consisting of six blood samples each, collected during the 24-hour dosing interval, were obtained from 25 (6 men and 19 women) Tunisian patients with extrapulmonary tuberculosis. The AUC was calculated according to the linear trapezoidal rule. The isoniazid concentrations at each sampling time were correlated by a linear regression analysis with the measured AUC. We analysed all the developed models for their ability to estimate the isoniazid AUC. Error indices including the percentage of Mean Absolute Prediction Error (%MAE) and the percentage of Root Mean Squared Prediction Error (%RMSE) were used to evaluate the predictive performance. The agreement between predicted and measured AUCs was investigated using Bland and Altman and mountain plot analyses. RESULTS AND DISCUSSION: Among the 1-time-point estimations, the C3 -predicted AUC showed the highest correlation with the measured one (r2  = .906, %MAE = 10.45% and %RMSE = 2.69%). For the 2-time-point estimations, the model including the C2 and C6 provided the highest correlation between predicted and measured isoniazid AUC (r2  = .960, %MAE = 8.02% and %RMSE = 1.75%). The C0 /C3 LSS model provided satisfactory correlation and agreement (r2  = .930, %MAE = 10.19% and %RMSE = 2.32%). The best multilinear regression model for predicting the full isoniazid AUC was found to be the combination of 3 time points: C0 , C1 and C6 (r2  = .992, %MAE = 4.06% and %RMSE = 0.80%). The use of a 2-time-point LSS to predict AUC in our population could be sufficient. C2 /C6 combination has shown the best correlation but the use of the C0 /C3 combination could be more practical with an accurate prediction. Therapeutic drug monitoring of isoniazid based on the C3 can be used also in daily clinical practice in view of its reliability and practicality. WHAT IS NEW AND CONCLUSION: The LSS using C0 and C3 is reliable, accurate and practical to estimate the AUC of isoniazid. A 1-time-point LSS including C3 had acceptable correlation coefficient and prediction error indicators could be used alternatively.