A semi-mechanistic model of the bactericidal activity of high-dose isoniazid against multidrug-resistant tuberculosis. 108 Figure 5.5: Visual predictive validation (VPC) of the isoniazid model stratified by dose and NAT2 genotype.
Introduction and literature review
Global disease burden of HIV and tuberculosis
2 Tuberculosis remained the leading cause of death among people living with HIV and accounted for approximately one third of AIDS-related deaths (UNAIDS, 2020b). The administration of tuberculosis treatment with ART prevented an estimated 11 million deaths between 2000 and 2019 (WHO, 2020) in individuals living with HIV.
Tuberculosis and HIV in neglected populations
- Pregnancy-induced physiological changes
The situation is further complicated by the physiological changes resulting from pregnancy that can alter the pharmacokinetics of a drug (Westin et al., 2018). Pregnant or breastfeeding mothers with tuberculosis and their infants have an increased risk of preeclampsia, vaginal bleeding, low birth weight, maternal and infant death (Mathad et al., 2014).
Tuberculosis disease
Two distinct acute phases characterize tuberculosis; the actively growing bacterial phase and the persistent phase, in which M.tb grows slowly or does not grow (Stewart et al., 2003). The ability of M.tb to remain in the persistent phase (a state persistent to immune clearance) for decades is key to M.tb's success and an important barrier to tuberculosis control, as most anti-tuberculosis drugs are inactive against non-TB dividing cells (Beste et al. al., 2009).
Tuberculosis treatment
- Tuberculosis drug resistance
- Multi-drug resistant TB
- Drug-drug interaction between ART and tuberculosis drugs
- Pharmacology of Isoniazid
- Absorption
- Distribution
- NAT2 genotyping and acetylator status
- Excretion
- Drug interaction
- Mechanism of action
- Mechanism of resistance
- Adverse events
- Pharmacology of bedaquiline
- Tuberculosis treatment efficacy measures
This enzyme is reported by Argyrou et al. 2006) to be inhibited by isoniazid-NADP adducts. The drug has bactericidal activity against M.tb that does not reproduce at a therapeutically achievable concentration (Vocat et al., 2015).
HIV treatment
- Pharmacology of efavirenz
18, the plate is counted manually to determine CFU, assuming that each colony originated from a single bacterium (MacLean et al., 2019). These polymorphisms have been associated with the heterogeneity of treatment response and toxicity observed in patients receiving efavirenz (Rotger et al., 2006).
Study justification
This led in part to the WHO recommending a shorter MDR-TB regimen incorporating high doses of isoniazid. However, the pharmacokinetics of high-dose isoniazid within the MDR-TB regimen are not well described.
Objective
Methodology
- Study designs and data description
- IMPAACT P1078 study
- ACTG A5312 INHindsight study
- PODRtb study
- Bedaquiline in pregnant women study
- Pharmacometrics
- Population pharmacokinetics
- Nonlinear mixed-effects modelling
- Pharmacodynamics
- Software
- Procedure for model development
At the time of the study (between 2016 and 2017), the standard MDR treatment regimen included pyrazinamide, moxifloxacin, kanamycin, cycloserine (dosed as terizidone), ethionamide, and/or isoniazid. This delay is captured using a bacterial growth delay time in the MGIT.
Pharmacokinetics and drug-drug interactions of isoniazid and efavirenz in
Abstract
Introduction
43 few data regarding the effect of pharmacogenomics and pregnancy on isoniazid PK and on the drug interaction between isoniazid and efavirenz during pregnancy and postpartum. As part of the recently completed IMPAACT study P1078 TB APPRISE trial, which investigated the safety and efficacy of administering IPT to pregnant women living with HIV, reported a significantly higher rate of adverse pregnancy outcomes in women who received IPT during pregnancy (Gupta, et al. ., 2019), we analyzed the main pharmacogenetic polymorphisms of efavirenz and isoniazid metabolism, the changes in drug concentrations and PK of these two drugs during pregnancy, and their drug-drug interactions.
Methods
- Participants and study design
- Sample collection
- Data Analysis
Isoniazid and efavirenz concentrations were interpreted using population pharmacokinetic modeling using NONMEM version 7.4.3 (Boeckmann et al., 2011). Hepatic hepatic blood flow Qh (Yang et al., 2007) was 90 L/h in a typical individual and adjusted for the effect of body size using allometric scaling (Mehvar, 2018).
Results
- Study profile
- Distribution of drug metabolizer genotypes
- Structural model
- Isoniazid Pharmacokinetics – Covariate effects
- Efavirenz pharmacokinetics - Covariate effects
The model-predicted individual exposures are shown in Figure 3.4, with panels A and B stratifying by CYP2B6 genotype and pregnancy status, while panels C and D stratifying by CYP2B6 genotype and isoniazid co-administration. 57 Figure 3.4: Efavirenz exposures stratified by CYP2B6 genotype, pregnancy and co-administration of isoniazid Panels A and B show box plots (with box representing median and inter-quartile range and whiskers 5th-95th interval) summarizing, respectively, AUC0- 24 and C12 for the three genotypes (slow, intermediate and normal metabolizer) stratified by pregnancy (solid line) and postpartum (dashed lines) visits.
Discussion
Tsutsumi et al., 2001) observed a reduction in NAT2 activity during pregnancy, but the reduction was not clinically significant. Sabbagh et al., 2011) show the highest level of within-population diversity of NAT2 genotype in Africans.
Supplementary material
The solid and dashed lines are the 5th, 50th, and 95th percentiles of the observations, while the shaded areas represent the model-predicted 95% confidence intervals for the same percentiles.
Bedaquiline exposure in pregnancy and breastfeeding in women with
Abstract
A single random bedaquiline and M2 plasma concentration was available in four infants (mean age: 6.5 weeks): concentrations in one breastfed infant were similar to maternal plasma concentrations; concentrations in the three non-breastfed infants were detectable but lower than maternal plasma concentrations. Bedaquiline accumulates significantly in breast milk; Breastfed infants receive mg/kg doses of bedaquiline equivalent to maternal doses.
Introduction
Pharmacokinetics during pregnancy can be complex: one of the reasons for reduced drug concentrations during pregnancy is the reduction in plasma concentrations of the two main drug-binding proteins: albumin and α1-acid glycoprotein (Schalkwijk et al., 2017). In contrast, clofazimine shows effective penetration into breast milk, with skin discoloration observed in infants of nursing mothers treated with clofazimine for leprosy (Loveday et al., 2020; Ozturk & Tatliparmak, 2017);
Methods
- Study design
- Bedaquiline assays
- Pharmacokinetic Modelling
- Calculation of the milk: plasma ratio (M:P)
- Calculation of infant bedaquiline intake with breast milk
- Ethics
Bedaquiline and its M2 metabolite in breast milk were analyzed with a validated assay developed at the Division of Clinical Pharmacology laboratory validated using PK of bedaquiline and M2 in breast milk from the mothers with paired plasma and milk samples were characterized using an effect space (Upton & Mold , 2014).
Results
- Study population and sampling
- Pharmacokinetic model
- Breast milk and infant exposures
A graphical overview of the infant and breast milk data is provided in Figures 4.2 and 4.3, together with plasma concentrations in the respective mothers. Further details of the breast milk concentration model are presented in the supplementary text in the appendix.
Discussion
We observed relatively high concentrations of bedaquiline in the breast milk samples we analyzed, significantly higher than the maternal bedaquiline plasma concentrations, consistent with the results of an animal study (Jannsen Products, 2015). The high concentration of bedaquiline in breast milk suggests that the mammary glands could be a clearing site for bedaquiline.
Supplemental Pharmacokinetic model of breast milk
Kmilk is the equilibrium rate constant in plasma and human milk, and Rmilk and M2_Rmilk are the accumulation ratios of bedaquiline and M2, respectively. The model supported intersubject variability (BSV) in bedaquiline Rmilk (ΔOFV=5.05) and only proportional error for bedaquiline and M2.
Pharmacokinetics of high-dose isoniazid for treatment of multidrug resistant
Abstract
Significantly lower exposure to isoniazid was observed in participants on MDR-TB combination therapy compared to monotherapy exposure.
Introduction
The greater number of drugs used in the treatment of MDR-TB increases the likelihood of drug interactions (DDIs). Therefore, we aim to characterize the pharmacokinetics of standard (5 mg/kg) to high dose isoniazid (10-15 mg/kg) as monotherapy or part of the MDR-TB treatment regimen, thus investigating DDIs within the MDR-TB treatment regimen. .
Methods
- Study design and participants
- Study procedure
- Pharmacokinetics analysis
One such drug is Isoniazid, which is metabolized mainly in the liver and intestine (50-90%) by N-acetyltransferase 2 (NAT2) (McDonagh et al., 2014). The choice of ethionamide and/or isoniazid use was at the discretion of the treating clinician (Chirehwa et al., 2021).
Results
- Study Profile
- Pharmacokinetic model
When attempting to replace the study effect with any of the co-administered drugs, model fit was not improved. The solid and dashed lines are the 10th, 50th, and 90th percentiles of the observations, while the shaded regions represent the 95% model-predicted confidence intervals for the same percentiles.
Discussion
A preclinical study observed that ethionamide exposure (AUC) was significantly reduced when co-administered with D-cycloserine, but not when the two drugs were administered separately (Ranjan et al., 2019). A study by Chirehwa et al., 2021 found a similar decrease in ethionamide clearance when co-administered with isoniazid.
A semi-mechanistic model of the bactericidal activity of high-dose isoniazid
Abstract
116 15-mg/kg doses are required against isolates with the inhA mutation in the slow and intermediate N-acetyltransferase 2 acetylators, respectively. Conclusions: Isoniazid dosing based on N-acetyltransferase 2 acetylator status may help patients achieve effective exposures to inhA -mutated isolates.
Introduction
Tuberculosis biomarkers (colony-forming units (CFU) and time to positive result (TTP)) and isoniazid exposure are characterized by high inter- and intra-individual variability, and biomarker measurement is highly noisy (Rockwood et al., 2016). Such an approach becomes even more useful in identifying subgroups that may need dose adjustments (Ogasawara et al., 2018).
Methods
- Study Design and Participants
- Study procedures
- Pharmacokinetic/Pharmacodynamic Modelling
We previously reported (Dooley et al., 2020) measurable EBA against inhA-mutated isolates at high doses of isoniazid (mean EBACFU0-7 of 0.17 and 0.22 log10CFU/ml/day, at 10 and 15 mg/kg, respectively, in the inhA group compared to 0.16 log10CFU/ml/day in drug-sensitive patients). NAT2 was assigned the following phenotype: fast, medium or slow, using the suggestion of Sabbagh et al. (Sabbagh et al., 2009).
Results
- Enrolment and Baseline Characteristics
- Pharmacokinetics/pharmacodynamics model
- Dosing simulation
Dotted red and green lines represent the EC80 of inhA-mutated and drug-susceptible M.tb, respectively. Red and green lines represent EC80 of inhA-mutated M.tb and drug-susceptible M.tb, respectively.
Discussion
- Limitations
This may be caused by the loss in microbial fitness (O'Sullivan et al., 2010), resulting in the inhA mutant isolates growing at a slower rate compared to the drug-susceptible isolates. 134 Isoniazid's bactericidal activity in drug-susceptible M.tb is known to be greatest during the first 2 days of treatment and to decline thereafter (Wang et al., 2012).
Conclusion
Despite this, our model was able to describe the overall maximum kill achieved with the standard dose against drug-susceptible M.tb. Similarly, our model may have limited ability to predict the role of isoniazid later in treatment when fewer actively metabolizing bacilli remain.
Supplemental Methods
- Study procedures
- Pharmacokinetic model development
- Pharmacokinetics/pharmacodynamic (PK/PD) model development
- Handling of missing data
It explains the delay in the onset of the drug effect relative to its plasma concentration. Participants with a missing genotype were assigned to one of three phenotypes using an admixture model (Keizer et al., 2012) with three subpopulations.
Supplemental Results
- Pharmacokinetic model
- Pharmacokinetics/pharmacodynamic model
Introducing a delay in the onset of drug action or a bi-exponential decline provided a slight improvement of the model fit, but made the parameter estimates unstable and unreliable. Interestingly, replacing AUC24 with AUC24/MIC led to worsening of the model fit and an increase in the unexplained variation.
Conclusions
Pharmacokinetics and drug-drug interactions of isoniazid and efavirenz in pregnant women
The study's main findings were a modest reduction in isoniazid and efavirenz exposure due to pregnancy and a drug-drug interaction between isoniazid and efavirenz, resulting in an increase in efavirenz exposure that was pronounced only in CYP2B6 intermediate and slow metabolizers . A limitation of the P1078 study was the use of the postpartum visit at 7-23 weeks as a control when assessing the effect of pregnancy on the pharmacokinetics of isoniazid and efavirenz, as the passage of weeks may not be sufficient for all of the pregnancy-induced effects to resolve. .
Bedaquiline exposure in pregnancy and breastfeeding in women with rifampicin-resistant
This finding is important in the future use of IPT for TB prevention during pregnancy (Gupta, et al., 2019). The risk of toxicity is increased due to infants' immature CYP3A4, which is reported to mature around one year of age (Phillips et al., 2020).
Pharmacokinetics of standard vs high-dose isoniazid for treatment of multidrug resistant
However, NAT2 genetic information of participants on the MDR-TB regimen (which had low bioavailability of isoniazid) was not available, which was one of the limitations of our study. Furthermore, determining the mechanism of drug interaction between isoniazid and ethionamide would help in better understanding the interaction and identifying ways to overcome the interaction.
A semi-mechanistic model of the bactericidal activity of high-dose isoniazid against multi-
For this PK/PD analysis, we used a simpler version of the pharmacokinetic model developed in Chapter 5. Due to the simple nature of the model, run times were faster, but the ability to predict individual AUC to a good degree was sufficient to modulate M.tb kill was not compromised.
Implication of findings on tuberculosis and HIV treatment and research
- Neglected populations
- Pharmacogenetic testing and therapeutical drug monitoring
- Handling of sparse or noisy data
PBPK modeling could be used to describe the potential impact of physiological and anatomical changes during pregnancy on drug pharmacokinetics and also on drug exposure in breast milk (Metushi et al., 2016). A significant portion of the variability in drug response can be attributed to genetic factors that could influence drug pharmacokinetics and/or pharmacodynamics (Gervasini et al., 2010).
Overall summary and conclusion
The International Journal of Tuberculosis and Lung Disease: The official journal of the International Union against Tuberculosis and Lung Disease. The International Journal of Tuberculosis and Lung Disease: The Journal of the International Union against.
NONMEM scripts
