Chapter 5: Pharmacokinetics of high-dose isoniazid for treatment of multidrug resistant
5.4 Results
5.4.2 Pharmacokinetic model
102
103 Table 5.2:Final PK parameter estimates for isoniazid.
Parameter Typical Value (95% CIa) Variability b, %CV (95%
CIa)
CLint.maxc (L/h) NAT2 Rapid 51.7 (38.8 – 56.0)
32.1 (20.5 – 43.1)*
CLint.maxcc (L/h) NAT2 Intermediate 29.6 (21.8 – 35.0)
CLint.maxc (L/h) NAT2 Slow 12.5 (10.3 – 14.7)
Vc d (L) 41.2 (37.1 – 43.8)
Vpd (L) 9.97 (7.08 – 11.9)
VHd (L) 1 FIXED
Q c (L/h) 2.26 (1.62 – 2.83)
ka (1/h) 5.50 (3.96 – 5.58) 155 (117 - 172)#
MTT (h) 0.154 (0.102– 0.200) 106 (93.3- 138)#
NN (.) 2.55 (1.67 – 3.02)
QHc (L/h) 90 FIXED
fu (%) 95FIXED
Prehepatic relative bioavailability
[FpreH] - INHindsight (%) 100FIXED 21.4 (14.3 – 23.4)# Prehepatic relative bioavailability
[FpreH ] – PODRtbf (%) 34.5 (28.4 – 42.3) 63.3 (42.3 – 69.3)#g Scaling parameter for between-
occasion variability in FpreH– PODRtb
(folds) 2.96 (2.56 – 4.52)
Effect of dose on PODRtb FpreH - per
unit increase from 10 mg/kg (%) +2.82 (1.40 – 4.24) Proportional error (%) 12.3(10.8 – 14.0) Additive error (mg/L) 0.021e FIXED
Km(mg/L) 19.5 (14.2 – 34.5)
Ethionamide effect on CLint (%) -29.5 (-40.1 – -14.6)
Abbreviations: CLint clearance intrinsic; Vc apparent central volume of distribution; VP apparent peripheral volume of distribution; VH apparent hepatic volume of distribution; Q apparent intercompartmental clearance for INH; ka first-order rate constant of INH absorption; MTT absorption mean transit time; NN Number of absorption transit compartment; QH
blood liver flow 19; fu unbound fraction of isoniazid in plasma (Alghamdi et al., 2018); Km drug concentration that produces 50% of the maximal elimination rate of the system.
Shrinkage of variability in the final model are below 30% for all estimates, and epsilon shrinkage is 15%
a 95% confidence intervals (CIs) were obtained with a 200-sample nonparametric bootstrap
b Variability was modelled with log-normal distribution and is presented as an approximate percentage CV.
c Clearance parameters are allometrically scaled based on fat-free mass (typical value reported for 44 kg, which was the median fat-free mass of the study population)
d Volume of distribution parameters are scaled based on weight (typical value reported for 51 kg, which was the median weight of the study population).
e Additive error was fixed to 20% of the LLOQ.
f The reference of the PODRTB estimated Prehepatic relative bioavailability – PODRtb (FpreH) was 10 mg/kg dose.
g Inflated between occasion variability due to the scaling parameter of the PODRtb study bioavailability.
* Between subject variability.
# Between occasion variability
104 Allometric scaling was applied on all disposition parameters, including those for the hepatic model (Clint, Vh, and Qh) to account for effect of body size, improving model fit (ΔOFV=-17.6), and explaining part of between-subject variability (a drop of 12% in BSVCL). Replacing body weight with fat-free mass for clearance parameters (but not volume) further improved model fit (ΔOFV=-18.6). NAT2 genotype significantly affected clearance of isoniazid (ΔOFV=-90, p≪0.001), as CLint varied greatly between rapid (51.7 L/h), intermediate (29.6 L/h), and slow (12.5 L/h) acetylators. After adjusting for body size and NAT2 genotype, the model detected a 29% decrease in isoniazid intrinsic clearance due to ethionamide co-administration (ΔOFV=−16.1, p≪0.001) irrespective of NAT2 genotypes. There was no significant effect of crushed tablets on FpreH (p= 0.130); however, the model estimated faster absorption for crushed tablets (no delay before first-order absorption) and a transit compartment model with an estimated mean transit time of 9 minutes for the whole tablets (ΔOFV=−28, p≪0.001). There was no significant effect of efavirenz co-administration on clearance (p=0.265).
A significant difference was identified in FpreH of isoniazid between the two studies (ΔOFV=−144, p≪0.001); PODRtb study FpreH was 65.5% lower compared to the INHindsight study. The PODRtb study had between-occasion variability in FpreH of 3 folds greater than the INHindsight study (ΔOFV=−102, p <0.001). Figure 5.2 displays FpreH of the two studies stratified by the three-dose categories, FpreH for PODRtb is lower and more variable than the INHindsight. FpreH of a typical individual in the INHindsight study was fixed to 1, presented by the green dashed line in Figure 5.2. The FpreH of the PODRtb study was dose-dependent, with a 2.82% increase in FpreH with a unit increase in dose/kg displayed in Figure 5.2 (ΔOFV=−19.8, p≪0.001). In contrast, there was no significant difference between the INHindsight FpreH
across the different doses. Figure 5.3 shows the comparison of the exposures observed in the
105 two studies with that of historical drug-sensitive TB data (Hong et al., 2020). For easy comparison with previous reports, the rapid and intermediate NAT2 exposure in Figure 3 were merged. The boxplot illustrates that the INHindsight exposures are in line with historical data, while the PODRtb exposures are lower for all the NAT2 genotypes. When trying to replace the study effect with any of the co-administered drugs, the model fit did not improve.
In particular, the model could not meaningfully discriminate between study effect and the three co-administered drugs that nearly all PODRtb study participants were taking, namely pyrazinamide, moxifloxacin, and terizidone/cycloserine. The decrease in OFV when testing each of these drugs was similar to that of study effect, so we decided to simply include study effect in the final model.
106 Figure 5.2: Boxplot of relative prehepatic bioavailability for the two studies (INHindsight and PODRtb) stratified by the three-dose categories. The green line is the reference relative prehepatic bioavailability, which was fixed to 1. All values for NAT2 for the PODRtb study were imputed using a mixture model.
Nonlinear PK of isoniazid was observed at higher doses, as the drug-metabolizing enzymes in the liver were exposed to a concentration higher than the predicted Km(19.5 mg/L). Such isoniazid concentrations were only achieved in the liver during absorption before the first pass, while the central compartment concentration was below the predicted Km. Figure 5.4 shows the dose exposure relationship, illustrating how the nonlinear model (which the data supported) a more-than-proportional increases in exposure with higher doses (approximately a 50% increase in AUC0-24 above linearity at a dose of 20 mg/kg). The marks on the x-axis of Figure 5.4 represent the mg/kg dose that the patients in the two studies received. Model
107 evaluation through VPC (Figure 5.5) shows that the model generally described the data well.
Figure 5. 3: A boxplot comparing the exposure of participants administered the standard dose (5mg/kg) in the two studies (INHindsight and PODRtb), stratified by NAT2 genotype. The purple line represents isoniazid AUC0-24 from historical data (Hong et al., 2020), 10.4 and 27.5 for the Rapid &
Intermediate, and slow respectively. A weighted geometric mean for the Rapid and intermediate was calculated to determine the purple line in the Rapid & intermediate panel.
108 Figure 5.4: Lineplot comparing the isoniazid exposure for different doses, stratified by NAT2
genotype for a linear dose exposure and nonlinear dose exposure model. The three colours represent the different NAT2 genotype, the solid lines represent nonlinear dose exposure, and the dotted line represent linear dose exposure. The marks on the x-axis represent the mg/kg dose observed in the two studies.
109 Figure 5.5: Visual predictive check (VPC) of the isoniazid model, stratified by dose and NAT2
genotype. Panel A is the VPC of the INHindsight, while panel B is for the PODRtb data. The solid and dashed lines are the 10th, 50th, and 90th percentiles of the observations, while the shaded areas represent the 95% model-predicted confidence intervals for the same percentiles. For the panels with few data, represented by §, we display only the 50th percentile.
110