Population Pharmacokinetics of Isoniazid, Pyrazinamide, and Ethambutol in Pregnant South African Women with Tuberculosis and HIV

Abstract

Tuberculosis is an important cause of maternal morbidity, but little is known about the effects of pregnancy on antituberculosis drug concentrations. We developed population pharmacokinetic models to describe drug dispositions of isoniazid, pyrazinamide, and ethambutol in pregnant women with tuberculosis and HIV. HIV-positive pregnant women with tuberculosis receiving standard first-line tuberculosis treatment and participating in Tshepiso, a prospective cohort study in Soweto, South Africa, underwent sparse pharmacokinetic sampling at >36 weeks of gestation and 7 weeks postpartum. The effects of pregnancy on the pharmacokinetics of isoniazid, pyrazinamide, and ethambutol were investigated via population pharmacokinetic modeling. Isoniazid, pyrazinamide, and ethambutol concentrations were available for 29, 18, and 18 women, respectively. Their median weight was 66 kg while pregnant and 64 kg postpartum. No significant differences were observed in drug clearance, volume of distribution, or bioavailability during and after pregnancy. The model-estimated isoniazid, pyrazinamide, and ethambutol area under the concentration-time curve from 0 to 24 h (AUC0–24) medians were, respectively, 6.88, 419, and 16.5 mg · h/liter during pregnancy versus 5.01, 407, and 19.0 mg · h/liter postpartum. The model-estimated maximum concentration (Cmax) medians for isoniazid, pyrazinamide, and ethambutol were, respectively, 1.39, 35.9, and 1.82 mg/liter during pregnancy versus 1.43, 34.5, and 2.11 mg/liter postpartum. A posteriori power calculations determined that our analysis was powered 91.8%, 59.2%, and 90.1% at a P of <0.01 to detect a 40% decrease in the AUCs of isoniazid, pyrazinamide, and ethambutol, respectively. Pregnancy does not appear to cause relevant changes in the exposure to isoniazid, pyrazinamide, and ethambutol. Additional studies of antituberculosis drugs in pregnancy are needed.

Prior information for population pharmacokinetic and pharmacokinetic/pharmacodynamic analysis: overview and guidance with a focus on the NONMEM PRIOR subroutine

“…VPC [5, 6, 9, 11-14, 17-24, 28, 30-34], pcVPC [8,10,16,29], and NPDE [9,25,29]). Some used bootstrap [4, 5, 9, 11-14, 16-18, 20, 23-25, 27, 32, 34], SIR [28] and external validation [30,33,34].…”

“…Two articles used MCMC Bayesian analysis with $PRIOR NWPRI statement, which allowed the specification of prior parameters distributions [ 6 , 26 ]. The PRIOR subroutine was mostly used for empirical popPK models in special populations, for example to analyze sparse data from children [ 9 , 10 , 12 , 13 , 18 , 20 , 25 – 27 ] or pregnant women [ 19 , 20 , 28 ]. In one pediatric model, the PRIOR subroutine was used to stabilize the parameters of the maturation function ( i.e.…”

“…In our review, only two out of 32 articles analyzing sparse data used TNPRI [ 15 , 29 ]: in both articles, the previous analysis had been done by the same team. Eighteen articles [ 4 – 14 , 23 , 25 , 27 , 30 , 32 – 34 ] used NWPRI; in the remaining 12 articles the method was not specified [ 16 – 22 , 24 , 26 , 28 , 31 , 35 ], among which six used prior only on THETA [ 19 , 20 , 22 , 24 , 28 , 35 ], the distribution attributed to the OMEGA consequently having no impact.…”

“…Eight out of 32 articles analyzing sparse data reviewed implemented informative priors on all parameters [ 5 , 10 , 12 , 15 , 23 , 29 – 31 ], 18 implemented informative priors, and/or so-called “weakly informative” (when they are associated to 10% [ 20 ] or 50% [ 24 , 28 ] uncertainty) only on a part of the parameters [ 7 – 9 , 13 , 16 – 22 , 24 , 25 , 28 , 32 – 35 ], and three implemented uninformative priors on some of the parameters while had informative priors on the rest of the parameters [ 4 , 6 , 11 ]. The latter included the study using MCMC [ 6 ] and the study comparing FOCE to MCMC [ 4 ].…”

“…Most articles reviewed validated the models built with priors using simulation-based diagnostics (i.e. VPC [ 5 , 6 , 9 , 11 – 14 , 17 – 24 , 28 , 30 – 34 ], pcVPC [ 8 , 10 , 16 , 29 ], and NPDE [ 9 , 25 , 29 ]). Some used bootstrap [ 4 , 5 , 9 , 11 – 14 , 16 – 18 , 20 , 23 – 25 , 27 , 32 , 34 ], SIR [ 28 ] and external validation [ 30 , 33 , 34 ].…”