
==== Front
Eur J Drug Metab Pharmacokinet
Eur J Drug Metab Pharmacokinet
European Journal of Drug Metabolism and Pharmacokinetics
0378-7966
2107-0180
Springer International Publishing Cham

39153028
910
10.1007/s13318-024-00910-7
Review Article
Precision Medicine Strategies to Improve Isoniazid Therapy in Patients with Tuberculosis
http://orcid.org/0000-0003-1520-9598
Thomas Levin
http://orcid.org/0000-0003-4723-8748
Raju Arun Prasath
http://orcid.org/0000-0003-2568-5096
Mallayasamy Surulivelrajan
http://orcid.org/0000-0003-3322-5399
Rao Mahadev mahadev.rao@manipal.edu

https://ror.org/02xzytt36 grid.411639.8 0000 0001 0571 5193 Department of Pharmacy Practice, Manipal College of Pharmaceutical Sciences, Manipal Academy of Higher Education (MAHE), Manipal, Karnataka 576104 India
17 8 2024
17 8 2024
2024
49 5 541557
15 7 2024
© The Author(s) 2024
2024
https://creativecommons.org/licenses/by-nc/4.0/ Open Access This article is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License, which permits any non-commercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc/4.0/.
Due to interindividual variability in drug metabolism and pharmacokinetics, traditional isoniazid fixed-dose regimens may lead to suboptimal or toxic isoniazid concentrations in the plasma of patients with tuberculosis, contributing to adverse drug reactions, therapeutic failure, or the development of drug resistance. Achieving precision therapy for isoniazid requires a multifaceted approach that could integrate various clinical and genomic factors to tailor the isoniazid dose to individual patient characteristics. This includes leveraging molecular diagnostics to perform the comprehensive profiling of host pharmacogenomics to determine how it affects isoniazid metabolism, such as its metabolism by N-acetyltransferase 2 (NAT2), and studying drug-resistant mutations in the Mycobacterium tuberculosis genome for enabling targeted therapy selection. Several other molecular signatures identified from the host pharmacogenomics as well as other omics-based approaches such as gut microbiome, epigenomic, proteomic, metabolomic, and lipidomic approaches have provided mechanistic explanations for isoniazid pharmacokinetic variability and/or adverse drug reactions and thereby may facilitate precision therapy of isoniazid, though further validations in larger and diverse populations with tuberculosis are required for clinical applications. Therapeutic drug monitoring and population pharmacokinetic approaches allow for the adjustment of isoniazid dosages based on patient-specific pharmacokinetic profiles, optimizing drug exposure while minimizing toxicity and the risk of resistance. Current evidence has shown that with the integration of the host pharmacogenomics—particularly NAT2 and Mycobacterium tuberculosis genomics data along with isoniazid pharmacokinetic concentrations in the blood and patient factors such as anthropometric measurements, comorbidities, and type and timing of food administered—precision therapy approaches in isoniazid therapy can be tailored to the specific characteristics of both the host and the pathogen for improving tuberculosis treatment outcomes.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13318-024-00910-7.

Manipal Academy of Higher Education, ManipalOpen access funding provided by Manipal Academy of Higher Education, Manipal

issue-copyright-statement© Springer Nature Switzerland AG 2024
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pmcKey Points

• Precision therapy of isoniazid requires a bedside to bench to bedside approach involving a comprehensive investigation of both Mycobacterium tuberculosis and the host pharmacogenomic profile, isoniazid drug concentrations in the blood, and the microbiological and clinical profile of patients with tuberculosis (TB).	
• Most of the biomarkers identified from the various omics approaches and population-modeling strategies, except for N-acetyltransferase 2 (NAT2)-genotype-integrated population pharmacokinetic approaches, require further validation via multicentric prospective longitudinal studies with larger sample sizes in diverse TB patient populations, long-term follow-up, and outcome assessment.	

Introduction

First synthesized in 1912, isoniazid (also known as isonicotinic acid hydrazide or INH) has been used as a first-line antitubercular drug since 1952. Isoniazid exerts a bactericidal effect against Mycobacterium tuberculosis, especially when it is in the fast-growing phase, and a bacteriostatic effect on slow-growing Mycobacterium tuberculosis or even that in a latent state, primarily by inhibiting the biosynthesis of mycolic acids [1–4]. Isoniazid does not violate Lipinski's rule of five, as its molecular weight, calculated logP or octanol:water partition coefficient (cLogP), number of hydrogen-bond donors, and number of hydrogen-bond acceptors are 137.14 daltons, − 0.67, 2, and 4, respectively [5]. Isoniazid is unlikely to permeate readily through the stomach mucosa, as it undergoes protonation in acidic media and is primarily absorbed from the small intestine [6]. Isoniazid exhibits high solubility but, due to inconclusive reports on its permeability, may be considered to lie at the borderline between Biopharmaceutics Classification System (BCS) classes 1 and 3 [5, 7]. In vitro reports suggest that isoniazid is transported across the intestinal mucosa exclusively via a passive transport mechanism as well as by complex kinetics comprising both passive and capacity-limited transport components [8–10]. The median (range) protein binding % of isoniazid has been estimated to be 13.8 (0.0–34.1). Further, isoniazid protein binding was reported to be negatively correlated with isoniazid plasma concentration, suggesting that the free drug concentration of isoniazid could increase at higher doses [11]. Isoniazid is primarily metabolized in the liver and intestines (50–90%) by N-acetylation of its hydrazine functionality by the enzyme arylamine N-acetyltransferase 2 (NAT2) to N-acetylisoniazid [12–15]. Isoniazid may also be hydrolyzed by an amidase enzyme to hydrazine [13–16]. N-acetylisoniazid may be further hydrolyzed by an amidase to form acetylhydrazine, which may undergo further NAT2-mediated acetylation to diacetylhydrazine [14–20]. Isoniazid and its metabolites acetylhydrazine and hydrazine are likely oxidized into potentially hepatotoxic intermediates in part by the enzyme cytochrome P450 2E1 (CYP2E1) [20–22]. Further conjugation of these potentially harmful metabolites with glutathione by the glutathione S-transferase (GST) enzyme family may remove them [15]. Isoniazid has a low intrinsic clearance (CLint) of 21.7 and 13.9 μL/min/mg in mouse and human, respectively [5]. The isoniazid metabolites N-acetylisoniazid, acetylhydrazine, and diacetylhydrazine are mainly excreted in urine (~ 80%), while about < 10% of an oral isoniazid dose is excreted in the feces [15, 23].

Numerous research studies have identified suboptimal isoniazid plasma concentrations among patients with tuberculosis (TB), suggesting that higher isoniazid doses, guided by therapeutic drug monitoring (TDM), may be beneficial [24–26]. A low isoniazid concentration was reported to be associated with delayed sputum culture conversion [27]. Patients with TB who had lower isoniazid serum concentrations at 2 h (C2 h) (target range = 3–6 μg/mL) were more likely to have a history of TB treatment and drug-resistant TB compared to those who had C2 h in the normal range [28]. A higher frequency of TB patients with signs of severe disease in chest radiographs to have a low isoniazid C2 h was observed, along with a tendency of patients with low C2 h to be associated with culture positivity at 2 months [28].

NAT2 single-nucleotide polymorphisms (SNPs) significantly influence the pharmacokinetic properties of isoniazid in adult, child, and adolescent populations with TB [26–29]. NAT2 rapid acetylators had a lower isoniazid area under the plasma concentration–time curve over the 24-h dosing interval (AUC0–24 h) than intermediate acetylators, whereas slow acetylators had a higher isoniazid  AUC0-24 h than intermediate acetylators [29]. NAT2 rapid acetylators were more likely to have a microbiological failure compared to slow acetylators [30]. A retrospective study reported that the 3-h isoniazid concentration post-isoniazid intake (C3 h) was significantly higher among adult patients with TB who experienced adverse drug reactions (ADRs) to first-line antitubercular drugs [31]. A higher isoniazid maximum (or peak) concentration (Cmax) was significantly correlated with an increased risk of developing any ADR among patients with a latent tuberculosis infection (LTBI) [32].

The global prevalence of rifampin-susceptible, isoniazid-resistant patients with TB was 7.4% (95% CI 6.5–8.4%) among those who were newly diagnosed and 11.4% (95% CI 9.4–13.4%) among those were previously treated for TB [33]. About one-fifth of the isoniazid mono-resistant patients were reported to have poor TB treatment outcomes [34]. Reports on leveraging isoniazid, which is a time-tested, relatively safe, and widely accessible antitubercular drug with few pharmacokinetic interactions, in cases of isoniazid resistance have emerged [35]. Hence, there is a need to optimize the isoniazid dose in patients with TB to achieve optimum pharmacokinetic levels and a clinical response considering the genetic profiles of the host and Mycobacterium tuberculosis as well as clinical covariates. The current review focuses on host and Mycobacterium tuberculosis-based considerations for precision therapy of isoniazid. The literature search strategy is described in Online Resource 1.

Host-Based Isoniazid Dosing Consideration

Several host-based omics, TDM, pharmacokinetic–pharmacodynamic, and population-modeling approaches such as population pharmacokinetics (PopPK) and physiologically based pharmacokinetics (PBPK) have aimed to address the inter- and intra-individual variabilities of isoniazid treatment in patients with TB.

Pharmacogenomics

NAT2 Gene Polymorphisms

About 72% of the pharmacokinetic variability of isoniazid has been attributed to differences in NAT2 polymorphisms [36]. The NAT2 gene, located on the human chromosome 8p22, consists of a non-coding 103-base-pair-long exon 1 at the 5′ end that is separated by an 8.6-kb-long intronic region from the single protein-coding exon 2 region, which is 873 base pairs (including the stop codon) in length [37–40]. Exon 2 in the NAT2 gene encodes for the 290-amino-acid protein NAT2 [41, 42]. NAT2 messenger RNA (mRNA) levels were found to be highest in the liver, with slightly lower amounts found in the small intestine and colon, and this  mRNA was also detected in most other tissues, albeit at levels that are ≤ 1% of those in the liver [43]. NAT2 polymorphism significantly impacts the pharmacokinetic properties of isoniazid [26]. Genetic polymorphisms in the NAT2 gene result in a trimodal (fast, intermediate, and slow) isoniazid elimination pattern [44]. The most well-studied SNPs in the NAT2 coding region (exon 2), represented as the nucleotide position and change (rs identification; amino acid change in the NAT2 protein) are 191G>A (rs1801279; arginine64glutamine), 282C>T (rs1041983; tyrosine94tyrosine), 341T>C (rs1801280; isoleucine114threonine), 481C>T (rs1799929; leucine161leucine), 590G>A (rs1799930; arginine197glutamine), 803A>G (rs1208; lysine268arginine), and 857G>A (rs1799931; glycine286glutamic acid). The NAT2 SNP 191G>A has been reported to be absent in several Asian populations [45].

The NAT2 341T>C SNP accounted for an eightfold reduction in NAT2 catalytic activity and a 6.1-fold reduction in NAT2 protein levels in comparison to the reference NAT2*4 activity. This SNP significantly enhanced NAT2 protein degradation, whereas no alteration of the substrate or cofactor binding affinity or NAT2 protein thermostability or reduction of the NAT2 mRNA level was observed [46]. The NAT2 590G>A SNP caused a modest reduction (33%) in NAT2 catalytic activity along with a threefold reduction in NAT2 protein expression and a fivefold reduction in thermostability compared to the reference NAT2*4 activity [47]. However, this SNP did not change the substrate affinity [48]. Ugandan patients with pulmonary TB (PTB) and HIV coinfection who were NAT2 590G>A heterozygous (GA) or homozygous (AA) mutant carriers had a 26.3% or 74.6% reduction in clearance, respectively (p < 0.001), compared to those who were homozygous wildtype (GG) carriers [49]. The NAT2 857G>A SNP accounted for a significant reduction in NAT2 protein thermostability (p < 0.01) in comparison to the reference NAT2*4 activity [48]. The NAT2 SNPs 282C>T, SNP 481C>T, and 803A>G did not have significant effects on the NAT2 mRNA, protein, or catalytic activity [48]. A significant reduction (>85%) in N-acetylation activity by NAT2 was observed among the haplotypes NAT2*5B (341T>C + 481C>T + 803A>G) and NAT2*6A (282C>T + 590G>A) and a 70% reduction was observed with the NAT2*7B (282C>T + 857G>A) haplotype in comparison to the wild type, NAT2*4 [48]. The NAT2 intermediate and slow genotypes had ∼40% (p < 0.01) and ∼60% (p < 0.0001) lower NAT2 protein expression levels, respectively, as compared to the NAT2 rapid genotypes. No statistical difference in mRNA levels (p > 0.05) in hepatocyte samples between the NAT2 rapid, intermediate, and slow genotypes was observed [50].

Higher mean liver function test values were observed among the NAT2 slow acetylators during the 8–28 days of isoniazid-containing antitubercular regimen initiation as compared to intermediate acetylators/rapid acetylators [51]. A higher proportion of NAT2 slow acetylators had elevated liver enzyme levels (aspartate transaminase (AST) or alanine transaminase (ALT) levels were more than twofold the upper limit of normal) and antitubercular drug-induced liver injury (AT-DILI) levels relative to intermediate and rapid acetylators [52]. Over the years, several systematic reviews and meta-analysis reports have identified the NAT2 genotype as a potential risk factor for the development of AT-DILI, as shown in Table 1 [53–57]. Table 1 Systematic reviews investigating NAT2 genotype as a risk factor for AT-DILI

Author (year) [reference]	Number of studies (sample size)	Risk for developing AT-DILI	
Richardson et al. (2019) [53]	40 (39 distinct patient cohorts)	NAT2 SA/IA vs. RA = OR: 1.59, 95% CI 1.26–2.01	
Yang et al. (2019) [54]	35 (1323 cases and 7319 controls)	NAT2 SA vs. NAT2 IA/RA = OR: 3.30, 95% CI 2.65-4.11	
Zhang et al. (2018) [55]	37 (1527 cases and 7184 controls)	NAT2 SA vs. NAT2 IA/RA = OR: 3.15, 95% CI 2.58–3.84	
Shi et al. (2015) [56]	27 (1289 cases and 5462 controls)	NAT2 SA vs. NAT2 IA/RA = OR: 3.08, 95% CI 2.29–4.15	
Wang et al. (2012) [57]	14 (474 cases and 1446 controls)	NAT2 SA vs. NAT2 IA/RA = OR: 3.73, 95% CI 2.90–4.79	
AT-DILI antitubercular drug-induced liver injury, CI confidence interval, IA intermediate acetylator, NAT2 N-acetyltransferase 2, OR odds ratio, RA rapid acetylator, SA slow acetylator, vs. versus

A multicenter, parallel, randomized, and controlled trial of newly diagnosed Japanese patients with PTB who were assigned to receive either conventional standard isoniazid treatment (~ 5 mg/kg) or NAT2-genotype-guided treatment reported that 78% of the NAT2 slow acetylators in the conventional standard treatment group developed isoniazid-associated drug-induced liver injury (DILI). Among the NAT2-genotype-guided treatment group, none of the NAT2 slow acetylators developed isoniazid-associated DILI. A reduced incidence of early treatment failure was observed in the NAT2-genotype-guided treatment group (15%) than in the conventional standard treatment group (39.5%) among rapid acetylators (RR: 0.37, 95% CI 0.11–0.86, p = 0.013) [58]. Another NAT2-genotype-based randomized study was carried out in healthy subjects who were on isoniazid therapy for 29 days. Among the NAT2 slow acetylators, the standard treatment group received 300 mg of isoniazid and the pharmacogenomic treatment group received 200 mg of isoniazid randomly. All NAT2 rapid acetylators (reference group) received 300 mg of isoniazid. The pharmacogenomic treatment group had a more stable serum liver enzyme profile and a lower incidence of ADRs as compared to the standard treatment group [59]. These results imply that an isoniazid dosing strategy based on NAT2 genotype may result in a reduced incidence of isoniazid-associated ADRs and better TB treatment outcomes.

Other Gene Polymorphisms

Several other gene polymorphisms have been implicated in altered isoniazid pharmacokinetics or antitubercular therapy (ATT)-induced ADRs, as shown in Table 2. Table 2 Implications of other pharmacogenomic variants for isoniazid pharmacokinetics or ATT-induced ADRs

Authors (year) [reference]	Gene investigated	Study details	Gene variant implications	
Ulanova et al. (2024) [60]	CYP2E1	Prospective cohort study among Latvian patients with PTB (n = 34)	Increased isoniazid AUC0–6 h (p = 0.047) was observed in 4 patients who had the SNP rs6413432 (mean AUC0–6 h = 16.4 µg/mL·h) as compared to 30 patients who did not have this SNP (mean AUC0–6 h = 10.4 µg/mL·h)	
Deng (2012) [61]	CYP2E1	Meta-analysis of 13 studies (599 patients who developed AT-DILI and 1813 controls)	For the CYP2E1 SNP rs2031920, patients with the c1/c1 genotype were associated with an increased risk of developing AT-DILI compared to variant genotypes (c1/c2 + c2/c2) [OR: 1.36, 95% CI 1.09–1.69].	
Tang (2013) [62]	GSTM1	Meta-analysis of 13 studies (963 patients who developed AT-DILI and 1953 controls)	Patients with the GSTM1 null genotype were associated with an increased risk of developing AT-DILI (OR: 1.50, 95% CI 1.15–1.95)	
Leiro (2008) [63]	GSTT1	Case–control study of Caucasian patients with TB (35 patients who developed AT-DILI and 60 controls)	Patients with the GSTT1 null genotype were associated with an increased risk of developing AT-DILI [OR: 2.60, 95% CI 1.08–6.24]	
Lee (2019) [64]	NAT2	177 Taiwanese participants with LTBI on weekly rifapentine and isoniazid therapy	Participants with LTBI who had the NAT2 SNP rs1041983 were associated with systemic drug reactions (TT vs. CC + CT = OR: 7.00; 95% CI 2.03–24.1)	
CYP2E1	Participants with LTBI who had the CYP2E1 SNP rs2070673 were associated with systemic drug reactions (AA vs. TT + TA = OR: 3.50; 95% CI 1.02–12.0)	
Sun (2020) [65]	NOS2	Case–control study of Chinese patients with TB (461 patients who developed AT-DILI and 466 controls in the discovery cohort; 216 patients who developed AT-DILI and 432 controls in the replication cohort)	Patients with the NOS2 SNPs rs9906835 (discovery cohort—GA vs. AA = OR: 1.60, 95% CI 1.21–2.13; replication cohort—GA vs. AA = OR: 1.76, 95% CI 1.23–2.51), rs944725 (discovery cohort—TC vs. CC = OR: 1.52, 95% CI 1.16–2.00; replication cohort—TC vs. CC = OR: 1.67, 95% CI 1.18–2.36), and rs3794764 (discovery cohort—GA vs. GG = OR: 2.11, 95% CI 1.60–2.78; replication cohort—GA vs. GG = OR: 1.96, 95% CI 1.39–2.78) had an increased risk of AT-DILI	
MAFK	Patients with MAFK SNP rs3735656 (discovery cohort—TC vs. TT = OR: 0.65, 95% CI 0.49–0.86; replication cohort—TC vs. TT = OR: 0.62, 95% CI 0.44–0.89) had a decreased risk for AT-DILI	
Yang (2019) [66]	HMOX1	Case–control study of Chinese patients with TB (314 patients who developed AT-DILI and 628 controls)	Patients with the GG genotype at rs2071748 (A>G) in HMOX1 had a higher risk of developing AT-DILI than those with the AA genotype (OR = 1.50, 95% CI 1.00-2.24)	
ADRs adverse drug reactions, AT-DILI antitubercular drug-induced liver injury, ATT antitubercular therapy, AUC0–6 h area under the plasma concentration–time curve over the 6-h dosing interval, CI confidence interval, CYP2E1 cytochrome P450 2E1, HMOX1 heme oxygenase 1, LTBI latent tuberculosis infection, GSTM1 glutathione S-transferase mu 1, GSTT1 glutathione S-transferase theta 1, NAT2 N-acetyltransferase 2, NOS2 nitric oxide synthase 2, OR odds ratio, PTB pulmonary tuberculosis, SNP single-nucleotide polymorphism, TB tuberculosis, vs. versus

Low-cost portable instruments that use nanopore sequencing panels and target 15 SNPs in five genes (NAT2, CYP2E1, SLCO1B1, AADAC, and CYP3A5) that affect antitubercular drug metabolism offer the promise of an acceleration of pharmacogenomic profiling in patients with TB [67]. Pharmacogenomic-testing-based stratified isoniazid dosing could be a cost-effective strategy, as patients are less likely to need additional months of ATT and to experience ADRs, which could lower morbidity and mortality rates and the additional costs incurred for clinic visits, laboratory testing, and therapy modifications [68].

Gut Microbiome

A preclinical report suggested that gut microbiota composition might mediate isoniazid-induced DILI via immune regulation [69]. Disruption of the intestinal microbiota has been reported to reduce the isoniazid-mediated clearance of Mycobacterium tuberculosis (p < 0.01) via an in vivo mouse model [70]. Further studies, especially in patients with TB, are required to establish potential links between host gut microbiota and pharmacological effects of isoniazid.

Epigenomics, Proteomics, Metabolomics, and Lipidomics

Mongolian patients who had PTB and developed AT-DILI were reported to have a hypermethylated pattern at CpG5, CpG10, and CpG11.12 and total methylation of the promoter region of NAT2 as compared to those who did not develop AT-DILI. As the total methylation level in the NAT2 promoter region increased, a gradual increase in the risk of developing AT-DILI was observed (OR: 8.37, 95% CI 2.39–29.31) [71]. In silico, in vitro, and in vivo analyses exploring epigenetic regulatory mechanisms concerning isoniazid-induced DILI reported that the microRNA (miRNA) hsa-miR-15a-3p directly interacted with the NAT2 3′-untranslated region (UTR), suppressed endogenous NAT2 expression, and inhibited the isoniazid-induced overexpression of NAT2 as well as liver injury [72]. Another study in rats reported that hypermethylation of CpG islands in the miRNA gene promoter region probably regulated the downregulation of miR-122, miR-106b, and miR-125b expression observed in isoniazid-induced liver injury [73].

Reports from an integrated mass-spectrum-based proteomics, metabolomics, and lipidomics analysis among mice showed a relative loss of glutathione (GSH) in the liver upon co-administration of isoniazid and rifampin, and this decreased GSH level could be a central factor in isoniazid/rifampin-mediated hepatotoxicity [74]. An integrated proteomics and metabolomics study reported changes in several metabolites, lipids, and peptides in the mouse brain after exposure to isoniazid and rifampicin for 14 days, with the peroxisome proliferator-activated receptors (PPAR) pathway being the major disruptive pathway associated with brain injury. Hence, PPAR-α and -γ activation might be a key target for the alleviation of isoniazid- and rifampin-induced neurotoxicity [75]. Metabolomic reports for the urine samples of 74 patients with TB, including 33 patients who developed AT-DILI (cases) and 41 patients who did not develop AT-DILI (controls), revealed that the metabolites creatine (p < 0.001), lactulose (p = 0.004), melibiose (p = 0.010), diglycerol (p = 0.000), and 4-hydroxy-3-methoxybenzoic acid (p = 0.007) were significantly increased among the cases. On the other hand, aminomalonic acid (p = 0.020), nicotinic acid (p = 0.014), lactobionic acid (p = 0.005), d-glucoheptose (p < 0.001), ornithine (p = 0.031), and N-acetyl-l-glutamic acid (p = 0.016) were significantly increased in the control group [76].

TDM, Pharmacokinetics and Pharmacodynamics, PopPK, and PBPK

TDM is the clinical practice of measuring the concentrations of drugs in various biological fluids at designated time intervals for the optimization of individual dosage regimens [77]. TDM is mainly used for monitoring drugs with marked pharmacokinetic variability [77]. Isoniazid has been reported to exhibit large inter-individual pharmacokinetic variability [78, 79]. Measurements of the isoniazid concentration that are clinically related to Cmax and AUC0–24 h have been the pharmacokinetic parameters most commonly used to correlate to TB treatment outcomes. The TDM of isoniazid usually involves the estimation of C2 h or C3 h after isoniazid intake [80–83]. The isoniazid C2 h is often used as the estimated Cmax [80, 84]. A recent systematic review reported that the average (mean ± SD) isoniazid C2 h (µg/mL) for NAT2 slow, intermediate, and rapid acetylators was 6.82 ± 3.56, 4.66 ± 2.69, and 3.59 ± 3.01, respectively, whereas the average (mean ± SD) isoniazid C3 h (µg/mL) of NAT2 slow, intermediate, and rapid acetylators was 4.84 ± 1.31, 2.14 ± 0.09, and 1.57 ± 0.73, respectively [52]. The average (mean ± SD) isoniazid Cmax (µg/mL) of NAT2 slow, intermediate, and rapid acetylators was 7.16 ± 4.85, 5.11 ± 2.78, and 4.84 ± 3.60, respectively, suggesting that isoniazid C2 h may be a better sampling point than isoniazid C3 h due to the isoniazid C2 h having closer values to Cmax than C3 h [52]. A Cmax of 3–6 μg/ml after a 300-mg daily dose of isoniazid is usually targeted [80, 82]. A two-sampling-time scheme involving the measurement of C2 h to estimate Cmax and the measurement of the concentration at 6 h post-isoniazid dose (C6 h) to account for delayed absorption and malabsorption was proposed by Alsultan et al. [82]. A study by Saktiawati et al. reported that the optimal sampling strategy, based on sampling at 2, 4, and 8 h post-dose, provided an accurate and precise AUC0–24 h prediction for all the first-line ATTs, including isoniazid [85]. Results of pharmacokinetic simulations using isoniazid population models for patients infected with both human immunodeficiency virus (HIV) and TB indicated that the measurement of isoniazid C2 h alone has a TDM sensitivity (% sensitivity of TDM [95% CI]: 65.5 [62.41–69.09]) that is sufficient to identify patients with a Cmax exceeding the target threshold and is almost comparable to the TBM sensitivity obtained by measuring both isoniazid C2 h and C6 h (% sensitivity of TDM [95% CI]: 65.5 [62.41–68.86]) [86]. A multivariate analysis reported that a lower isoniazid C2 h was the most important predictor for microbiological failure in patients with TB with a slow response (p = 0.009) [87]. However, a study by Lee et al. showed that concentration at 4 h post-isoniazid dose (C4 h ) (adjusted r2 = 0.95, p < 0.001) correlates more strongly with the measured AUC0–24 h than the conventional sampling point of C2 h (adjusted r2 = 0.75, p < 0.001) and other single sampling points do for all the NAT2 genotypes in isoniazid TDM [88]. A limited sampling strategy involving sampling at 1, 2.5, and 6 h post-dose to achieve the best prediction of AUC0–24 h was proposed by Magis-Escurra et al. [89]. Implementing optimal limited isoniazid-sampling strategies for TDM is crucial for precision dosing implementation and requires validation in larger clinical settings with a broader population using different sampling strategies during the first 1–6 h after isoniazid intake, and an international consensus regarding this is warranted.

When an early TDM service was introduced for patients with TB who were diabetic, it was observed that a high frequency of patients (65% and 75% for patients on a daily dose and intermittent isoniazid doses, respectively) had isoniazid C2 h values below the expected range. However, when these patients had a single dose increment for increasing the isoniazid C2 h to the expected range (3–6 μg/mL for patients on a daily dose of isoniazid and 9–18 μg/mL for patients on intermittent dosing of isoniazid), a better treatment response (the sputum culture turned negative in < 2 months) was observed [90]. An open-label pharmacokinetic study conducted in Indian children with TB or LTBI in the age group of 1 to 15 years who were randomized to receive isoniazid 5 mg/kg/day,or 10 mg/kg/day reported a higher mean isoniazid C2 h among those who received 10 mg/kg/day (8.86 µg/mL (10 mg/kg/day) vs. 2.68 µg/mL (5 mg/kg/day); p value ≤ 0.05). About 66% of the children who received 5 mg/kg/day of isoniazid failed to achieve the target C2 h range, whereas 91% who received 10 mg/kg/day of isoniazid had an isoniazid C2 h higher than the targeted range, and none of them were below the targeted range [91]. A lower isoniazid exposure was reported among children with TB who were in the lowest weight band of 4.0–7.9 kg (median AUC0–24 h [IQR]: 11.9 [8.4–22.4] mg·h/L) and the highest weight band of ≥ 25 kg (median AUC0–24 h [IQR]: 5.8 [3.5–8.8] mg·h/L) [92]. Reports from Babalik et al. showed that 13 of 15 (87%) patients with PTB had a lower isoniazid C2 h. A substantial increase in isoniazid dose in these patients, averaging about a 61% increment over the initial dose, resulted in a 127% mean increase in drug levels. A lower isoniazid concentration was significantly associated with the presence of comorbid illnesses such as HIV, liver disease, chronic renal insufficiency, and diabetes (p = 0.03) [93]. A higher isoniazid AUC0–24 h has been correlated with increased bacillary killing in sputum (p < 0.01) [94]. Results from a study conducted by Cojutti et al. suggested that an isoniazid AUC0–24 h of ≥ 55.0 mg·h/L may be used as a predictor of hepatotoxicity in adult patients with TB [95]. A multivariate analysis by Zheng et al. showed that patients with TB who had an isoniazid AUC > 21.78 mg·h/L were at higher risk of developing an acute kidney injury or DILI during TB treatment [96]. Due to the high variability of isoniazid exposure and the existence of a threshold associated with treatment outcomes, conducting systematic TDM may aid in the optimization of isoniazid therapy as well as the monitoring of medication adherence and TB treatment outcomes. However, TDM will only be beneficial if sufficient access and a short turnaround time for results are available to all levels of TB treatment centers [97].

The development of an isoniazid PopPK model has aided personalized isoniazid dosing [44]. PopPK modeling is advantageous because it allows sparse sampling at random time points, it identifies and explains the sources of variability (such as inter- and intra-subject, and inter-occasion variability), and it can be used to quantitatively estimate the magnitude of the unexplained variability in the patient population [98]. Both parametric and nonparametric approaches have been utilized for building PopPK models for isoniazid, with the parametric approach being the most used [44, 99, 100]. PopPK modeling has emerged as a potent tool for delineating isoniazid pharmacokinetic variability, with the NAT2 genotype found to be the most significant covariate influencing isoniazid disposition. Among parametric-approach-based PopPK models, a two-compartment model with first-order absorption and linear elimination has been the most used to describe the disposition of isoniazid. A trimodal clearance pattern for isoniazid was observed among patients with TB. NAT2 rapid acetylators had a multi-fold increase in isoniazid clearance compared to slow acetylators [101]. An isoniazid PopPK model developed for Chinese patients with TB recommended isoniazid doses of approximately 800 mg/day, 500 mg/day, and 300 mg/day for NAT2 rapid, intermediate, and slow acetylators, respectively, to reach the targeted indicators, such as a Cmax of 3–6 μg/ml, an area under the concentration–time curve from 0 h to infinity (AUC0–∞) of ≥ 10.52 μg·h/mL, or a serum C2 h of ≥ 2.19 μg/mL [44]. A PopPK study assessing both plasma and intrapulmonary drug levels in patients with TB reported that a higher isoniazid Cmax or AUC in the epithelial lining fluid achieved more rapid bacillary clearance (p < 0.05). However, the isoniazid drug concentrations in both plasma and alveolar cells were not significantly associated with sputum bacillary elimination rates [102]. Dose fractionation studies showed that AUC0–24 h/MIC (r2 = 0.83) was the best pharmacokinetic–pharmacodynamic parameter to describe the isoniazid bactericidal activity in the mouse model, followed by Cmax/MIC (r2 = 0.73) [103]. Another study has reported that 400, 300, and 200 mg of isoniazid was required by Korean patients with TB who were NAT2 rapid, intermediate, and slow acetylators, respectively, to attain the target ratio of free area under the concentration-versus-time curve to minimal inhibitory concentration (fAUC/MIC, which is an explanatory pharmacokinetic/pharmacodynamic index for early bactericidal activity (EBA) of isoniazid) of 61.6 (EC50) or 567 (EC90) for efficacy and a Cmax of ≤ 6 μg/mL for toxicity [104]. Results from a study conducted by Fredj et al. reported that initial isoniazid daily doses of at least 225 mg for NAT2 slow acetylators and 450 mg for rapid/intermediate acetylators allowed therapeutic concentration (C3 h target of 1.5 μg/mL) attainment in more than 80% of Tunisian patients with TB [105]. Monte Carlo simulation based on a nonparametric isoniazid PopPK study of Colombian patients with TB indicated that it is possible to attain the pharmacodynamic target of AUC0–24 h/MIC > 567 in all patients infected with Mycobacterium tuberculosis strains with an MIC of up to 0.03 mg/L. However, an isoniazid dose of 900 mg/day would be required to cover Mycobacterium tuberculosis strains with an MIC of up to 0.125 mg/L (which accounts for the majority of the clinical isolates) [99]. A pharmacokinetic/pharmacodynamic analysis of the administration of even higher isoniazid doses (10–15 mg/kg/day) to Indonesian rifampin-resistant (RR)/multi-drug-resistant (MDR) patients with TB for 9–11 months reported that only a few percent of the patients achieved the proposed targets of 85 and 17.5 for AUC0–24 h/MIC (23.1%) and Cmax/MIC (19.2%), respectively. NAT2 non-slow acetylators showed a 63% decrease in AUC0–24 h values compared with NAT2 slow acetylators, and delayed sputum culture conversion (> 2 months of treatment) was observed among those who had lower isoniazid AUC0–24 h values (adjusted OR: 0.18, 95% CI 0.04–0.89) [106]. A PBPK/pharmacodynamic analysis recommends bisecting the standard isoniazid dose of NAT2 slow acetylators to 150 mg QD and increasing the dose to 900 mg and 1200 mg for NAT2 intermediate and fast acetylators, respectively, with a BID administration schedule due to a trade-off between toxicity and treatment efficacy [107].

Physiological changes in pregnancy can alter the pharmacokinetic profile of isoniazid. A pregnancy-mediated increase in renal clearance and non-NAT2 activity (of up to 80%) accounted for an increased isoniazid clearance during pregnancy according to a PBPK modeling study. During pregnancy, the NAT2 enzyme activity appeared to be unchanged [108]. A recent report showed that isoniazid AUC0–24 h and Cmax were 25% and 23% lower, respectively, in the third trimester as compared to postpartum [109]. A PopPK analysis conducted among infants with a birth weight of ≤4000 grams (preterm or full term) who were receiving isoniazid for TB prophylaxis reported that besides NAT2 genotype and weight, postmenstrual age was a covariate that influenced the isoniazid pharmacokinetics. Ninety percent of the NAT2 maturation was attained by 4.4 post-natal months [110]. Recently, Ju et al. developed a parametric isoniazid PopPK model repository for model-informed precision dosage. Researchers may use this repository to simulate different clinical strategies in special patient populations and to perform external evaluations of their data for the identification of suitable models [111]. However, one of the limitations hindering the widespread building and application of PopPK models is that it requires skilled pharmacometricians [98]. To scale the results to clinical implementation, further research examining the generalizability and adaptability of the proposed isoniazid PopPK models to various clinical settings is required [101].

Demographic, Social, and Clinical Covariates to Be Considered

Female patients with TB were reported to have higher isoniazid plasma concentrations when compared to male counterparts [112–114]. A positive correlation was reported between the age of the patient with TB and the isoniazid Cmax and AUC0–24 h values, though it was not statistically significant (p > 0.05). Patients with TB who were older than 60 years had higher Cmax and AUC0–24 h values for isoniazid compared to younger patients (Cmax: 7.8 ± 2.4 μg/mL vs. 4.6 ± 2.0 μg/mL, p = 0.042; AUC0–24 h: 28.65 ± 8.1 μg·h/mL vs. 14.04 ± 8.5 μg·h/mL, p = 0.014). An inverse correlation was reported between isoniazid Cmax and body mass index (BMI) (p = 0.03), with overweight patients showing about 2.7-fold lower Cmax values than underweight patients with TB [115]. The isoniazid Cmax was lower among children with stunting and underweight children compared to normally nourished children (p < 0.05) [116]. A randomized crossover trial conducted among healthy Chinese male volunteers reported a higher mean Cmax when isoniazid was given as a separate formulation compared to when a four-drug fixed-dose combination (FDC) formulation was given (4 μg/mL versus 3.1 μg/mL) [117]. Smokers were reported to have a lower isoniazid Cmax when compared to non-smokers (median (IQR) isoniazid Cmax values of smokers and non-smokers were 9.1 (7.6–11.8) and 11.6 (8.5–13.5) µg/mL, respectively; p = 0.053) [113]. Efavirenz-based antiretroviral therapy (ART) reduced the isoniazid AUC0–24 h by 29% for rapid acetylators (isoniazid AUC0–24 h of patients on efavirenz-based ART was 4.68 mg·h/L, while the value for those not on efavirenz-based ART was 6.73 mg·h/L), but it did not affect the isoniazid AUC0–24 h of slow acetylators [118].

Several studies have shown that the intake of food reduces the absorption of isoniazid, though to a varying extent [119–122]. Carbohydrate meals, in particular, have been reported to significantly lower the absorption of isoniazid in slow acetylators (p < 0.01) [120]. The absolute bioavailability of isoniazid in adult patients with TB during the fasting state and the fed state (where the food was a high-carbohydrate breakfast containing 600 kcal was taken 0.5 h before isoniazid dosing) was 93% and 78%, respectively. The food reduced the absolute bioavailability and Cmax of isoniazid by 15% and 42%, respectively [123]. An Indian study reported that the intake of a breakfast containing 115 g of carbohydrate, 25 g of protein, and 15 g of fat caused delayed isoniazid absorption and a substantial lowering of the isoniazid plasma concentration (the geometric mean isoniazid C2 h values with food and under fasting conditions were 3.9 and 11.3 μg/ml, respectively) [124]. Another study reported that a high carbohydrate diet (530 kcal) decreased the isoniazid Cmax and area under the concentration–time curve to 8 h (AUC0-8 h) by 19% and 20%, respectively, whereas a high-protein, high-fat diet (520 kcal) decreased the isoniazid Cmax and AUC0-8 h by 9% and 8%, respectively [125]. However, early food intake at 30 min after isoniazid administration in the fasting state in patients with TB had no significant influence on plasma concentrations [126].

A PopPK study of people living with HIV (PLHIV) who had sepsis and were on first-line ATT reported that only 4.10% and 63.3% attained the minimum isoniazid targets of AUC0–24 h (52 mg·h/L) and Cmax (≥ 3 mg/L), respectively. Simulations suggested that isoniazid doses of ≥ 900 mg were needed to attain the target AUC0–24 h [127]. There is a paucity of studies focusing on the dosage and implications of isoniazid therapy in decompensated cirrhosis and advanced liver disease with complications of cirrhosis and signs of liver failure. Antitubercular regimens have been recommended to ideally contain one of either isoniazid or rifampicin therapy because of their hepatoxic potential for decompensated cirrhosis, and it may not be possible to use even a single antitubercular hepatotoxic drug in patients with advanced liver disease with complications of cirrhosis and signs of liver failure [128]. Isoniazid dosage reduction is generally not warranted for patients with renal impairment, during dialysis, and after transplantation [129]. In a study conducted in patients with end-stage renal disease requiring chronic hemodialysis, the median isoniazid recovery in dialysate was only 9.2% of the administered dose, suggesting that hepatic metabolism remains the primary mechanism of isoniazid clearance and that isoniazid could be administered in a 300-mg daily dose [130]. A pharmacokinetic study reported that isoniazid dosage reduction is not warranted for rapid acetylators but is advised for slow acetylators in renal failure patients [131]. A case report showed the development of severe encephalopathy after isoniazid therapy initiation in a patient on chronic hemodialysis. The patient had NAT2 slow acetylator status with an elevated isoniazid C3 h (2.89 mg/L) [132]. Further well-designed PopPK studies of patients with TB who have comorbid conditions such as HIV, sepsis, and liver and renal diseases are imperative for establishing isoniazid dosage recommendations in these conditions.

Pathogen-Based Isoniazid Dosing

Isoniazid resistance profiling is crucial for achieving successful treatment outcomes in all bacteriological TB cases [34]. Simulations integrating pharmacokinetic and pharmacodynamic data predict that the steeper dose–response curves and faster elimination of isoniazid compared to rifampicin explain why isoniazid-resistant Mycobacterium tuberculosis is more likely to survive treatment than rifampicin-resistant Mycobacterium tuberculosis. These predictions may provide possible mechanisms that lead to isoniazid monoresistance being the widely prevalent form of drug-resistant TB [133, 134]. The inclusion of high-dose isoniazid in ATT regimens requires the identification of molecular markers causing isoniazid resistance [135]. Several World Health Organization (WHO)-endorsed molecular diagnostics for rapid detection of isoniazid genomic drug susceptibility testing (DST) are available, such as Xpert MTB/XDR (Cepheid), RealTime MTB RIF/INH Resistance (Abbott), BD MAX™ MDR-TB (Becton, Dickinson and Company), cobas MTB-RIF/INH (Roche), FluoroType MTBDR (Hain), and GenoType MTBDRplus (Hain), and these have accelerated the development of precision isoniazid therapy [136]. The results of a recent systematic review and metanalysis showed that high-dose isoniazid administration (>300 mg/day or >5 mg/kg/day) for MDR TB treatment was significantly associated with higher treatment success (RR: 1.13, 95% CI 1.04–1.22; p < 0.01) as well as a lower risk of death (RR: 0.45, 95% CI 0.32–0.63; p < 0.01) [137]. Gastrointestinal symptoms were the most common reported events with high-dose isoniazid therapy, with a pooled estimate of 51.5% (95% CI 43.5–59.3%), followed by ototoxicity (20.5%, 95% CI 6.8–38.5%), neurotoxicity (12.4%, 95% CI 5.2–22.0%), hepatoxicity (12.2%, 95% CI 0–39.1%), and nephrotoxicity (10.8%, 95% CI 6.2–16.4%) [137].

When resistance is shown at critical concentrations of 0.1 µg/mL and 0.4 µg/mL, isoniazid resistance is deemed high, whereas when resistance is shown at a critical dose of 0.1 µg/m but susceptibility is observed at a concentration of 0.4 µg/mL, isoniazid resistance is deemed low [138, 139]. katG mutations account for the majority of the phenotypic isoniazid resistance globally, followed by mutations at the inhA promoter, inhA, and the ahpC-oxyR intergenic region [140]. Isoniazid-resistance-conferring mutations in the katG and inhA genes are associated with highly variable phenotypic resistance, which mandates the need for further research into the correlation between genotypic and phenotypic DST [141, 142]. The most frequent mutation occurs at codon 315 of the katG gene, where each of the nucleotides of the codon (AGC) can be mutated to encode for a threonine, asparagine, arginine, isoleucine, glycine, or leucine residue [143, 144]. katG S315T, identified as the most frequent mutation among the isoniazid-resistant isolates, has been reported to be associated with high-level isoniazid resistance [135]. A high level of resistance was reported in MDR TB isolates from China with a combination of ahpC-oxyR and katG non-315 mutations [145]. Also, high-level isoniazid resistance was observed for isolates having both katG and inhA mutations and isolates with both inhA regulatory and inhA coding region mutations [146, 147]. A faster time to sputum culture conversion (adjusted hazard ratio [aHR] = 1.58; 95% CI 1.08–2.31) was observed for strains with wild-type katG relative to those with katG S315T. Further, a slower time to sputum culture conversion (aHR = 0.57, 95% CI 0.39–0.83) was observed for strains having both inhA and katG mutations relative to those with katG mutation only [148].

Isoniazid causes a significant reduction in the sputum colony-forming unit count during the initial 2 days of therapy, indicating that the majority of Mycobacterium tuberculosis is killed during this time. Hence, isoniazid's microbial kill in patients with TB is measured using an index termed EBA, which is arbitrarily defined as the fall in log10 colony-forming units (cfu) of Mycobacterium tuberculosis per ml sputum per day during the initial 2 days of therapy [149]. The depletion of bacilli in the exponential phase of growth and the emergence of isoniazid-resistant bacilli are some of the explanations attributed to the decrease in isoniazid bactericidal activity after 2 days [150, 151]. The EBA of isoniazid during the initial 2 days of therapy is critically dependent on the concentration that reaches the bacilli [152]. Reports from the phase 2A AIDS Clinical Trials Group (ACTG) A5312/INHindsight study revealed that higher daily doses of isoniazid of 10–15 mg/kg had an EBA against TB strains with inhA mutations similar to that of standard doses of 5 mg/kg given to isoniazid-sensitive strains. However, longer-term studies are needed to determine the safety and tolerability of these higher doses of isoniazid [153]. A further recent report from ACTG A5312/INHindsight revealed that 10-mg/kg and 15-mg/kg doses of isoniazid are required for inhA-mutated isolates in NAT2 slow and intermediate acetylators, respectively. However, NAT2 fast acetylators underperformed, even with isoniazid doses of 15 mg/kg. Hence, NAT2-genotype-based dosing may be imperative for achieving effective isoniazid exposures against inhA-mutated isolates [154]. A retrospective analysis reported that isoniazid-monoresistant patients (katG S315T strains) with TB who received high-dose isoniazid were associated with increased odds of a favorable TB treatment outcome (OR: 1.87; interaction p = 0.14) [155]. However, a recent phase-2A, randomized, open-label trial reported negligible EBA with high-dose isoniazid (15-20 mg/kg) treatment in the majority of patients with TB who had katG mutation. The potency of isoniazid against katG-mutated Mycobacterium tuberculosis was approximately tenfold lower as compared to those with inhA-mutated Mycobacterium tuberculosis; even the highest dose of 20 mg/kg did not have a measurable EBA, except in a subset of slow NAT2 acetylator patients with TB [156]. After adjusting for potential confounders, patients with MDR TB who received high-dose isoniazid therapy (16–18 mg/kg/day) were reported to have higher odds of presenting a sputum-negative status compared to those who did not receive it (OR: 2.38, 95% CI 1.45–3.91, p = 0.001) [157]. Another study reported a faster time to culture conversion (p < 0.001) and higher odds of a successful outcome (adjusted OR: 2.53, 95% CI 1.08–6.28; p = 0.036) among patients with MDR TB receiving high-dose isoniazid therapy [158]. The pharmacokinetics of other first-line antitubercular drugs such as rifampicin and pyrazinamide could also influence TB treatment outcomes [159]. Hence, analytical techniques focusing on the simultaneous estimation of the concentrations of all these first-line antitubercular drugs may be beneficial for accurately predicting TB treatment outcomes.

An integrative multi-omics research approach involving host pharmacogenomic, epigenomic, metabolomic, lipidomic, gut microbiome, and Mycobacterium tuberculosis genomics profiling and an assessment of its influence on isoniazid pharmacokinetic and pharmacodynamic responses via PopPK or PBPK modeling approaches in patients with TB may provide further insights into interrelationships at multiple molecular levels, which could account for isoniazid pharmacological variabilities. However, most of the biomarkers identified from these omics approaches and population-modeling strategies, except for NAT2-genotype-integrated PopPK approaches to an extent, require validation via multicentric prospective longitudinal studies with larger sample sizes in diverse patient populations with TB, a long-term follow-up, and outcome assessment. Personalized isoniazid dosing warrants a bedside to bench to bedside approach involving a comprehensive investigation of both the Mycobacterium tuberculosis and host pharmacogenomic profiles coupled with isoniazid pharmacokinetic estimation, phenotypic DST, and clinical parameters such as anthropometric measurements, organ functional status, type of food administered along with isoniazid, the time of food administration, and special conditions such as pregnancy and a pediatric population. The reports of these investigations at the bedside and bench can be imput incorporated as covariates to build an isoniazid PopPK model for determining the precise doses of isoniazid (a representative example is shown in Fig. 1).Fig. 1 Considerations for precision isoniazid therapy. Precision isoniazid therapy requires a bedside to bench to bedside research approach that involves investigating the Mycobacterium tuberculosis and host genetic profiles along with the pharmacokinetic estimation of isoniazid concentration, phenotypic drug susceptibility testing, and clinical considerations of the patient’s status, such as their weight, their hepatic and renal function profile, the time of food administration, and special conditions such as pregnancy and a pediatric population. These investigated covariates may be imputed into population-pharmacokinetic modeling for determining the precise doses of isoniazid needed via the estimation of individual clearance for patients with TB (a representative example for individualized dosing is shown). The figure was created using BioRender.com (agreement number:  YD275ALKRG). ADRs adverse drug reactions, B2B2B bedside to bench to bedside, CLi individual clearance, Ct target concentration at time t, Conc. concentration, Dosei individualized dose, exp exponential, F bioavailability, IA intermediate acetylator, INH isoniazid, ka absorption rate constant, ke elimination rate constant, NAT2 N-acetyl transferase, PopPK population pharmacokinetics, Q intercompartmental clearance, RA rapid acetylator, SA slow acetylator, TB tuberculosis, t time, Vd volume of distribution, θ1 population clearance, θ2 effect of body weight on clearance, θ3 effect of gender on clearance, θ4 effect of genotype on clearance, θP coefficient value for different levels of Mycobacterium tuberculosis resistance, η between-subject variability, T dosing interval

As genotyping technologies such as whole genome sequencing (WGS), NAT2 genotyping, and other omics-based biomarkers and analytics technologies for drug estimation are rapidly progressing, a need for heightened deliberation of the potential trade-offs between precision medicine approaches and standardized treatment protocols is arising. This necessitates a comprehensive evaluation of the incremental advantages alongside the judicious allocation of resources [160]. Early TDM initiation after isoniazid therapy with a single dose increment/decrement, if necessary, may reduce the need for the investigation of multiple host biomarkers to achieve the optimal attainment of the therapeutic range. However, pre-emptive pharmacogenomic analysis of host biomarkers such as NAT2 may guide clinicians to perform closer monitoring for ADRs such as AT-DILI in patients with TB or LTBI. With the recent advancement in sequencing technologies, a targeted host SNP sequencing panel coupled with TDM and WGS of Mycobacterium tuberculosis may be cost-effective compared to the high mortality rates, the treatment cost, the increased duration of hospitalization, the treatment interruptions, the poor treatment outcomes, and the decreased quality of life associated with isoniazid/ATT-induced ADRs [161–165]. Challenges such as addressing issues with the accessibility and availability of genomic and analytical technologies at all levels of TB care (particularly in high-burden countries), the standardization of pharmacogenomic testing protocols, the incorporation of genetic data into clinical decision-making algorithms, achieving a consensus on sampling timings for isoniazid pharmacokinetic estimation, and the need for robust clinical validation need to be addressed for future investigation and implementation. PopPK studies coupled with the pharmacodynamics and safety outcomes concerning high-dose isoniazid therapy and NAT2 polymorphisms in adult, pediatric, and other special TB patient populations need to be assessed. Three-dimensional (3D) printing, a rapids prototyping technology, could be a potential option for the personalized production of oral isoniazid dosage forms that would enable adjustable doses and drug-release properties for isoniazid precision therapy in patients with TB [166, 167].

Conclusion

The integration of the host pharmacogenomics, PopPK modeling approaches, and Mycobacterium tuberculosis genomics along with the consideration of clinical covariates could offer a comprehensive approach for personalized isoniazid treatment strategies that could enhance efficacy, minimize toxicity, and combat the emergence of drug resistance in patients with TB. Other omics-based approaches such as gut microbiomes, epigenomics, proteomics, metabolomics, and lipidomics have been reported to influence isoniazid pharmacokinetics and/or ADRs, which, however, require extensive research. Though promising strides have been taken, future research endeavors on the refinement and implementation of these developed approaches in diverse patient populations are warranted to pave the way to more effective and personalized management of TB with isoniazid therapy in clinics.

Supplementary Information

Below is the link to the electronic supplementary material.Supplementary file1 (DOCX 14 KB)

L.T. thanks the Indian Council of Medical Research for providing a senior research fellowship (no. 45/25/2020/PHA/BMS). M.R. is thankful to the Indian Council of Medical Research for grant F. no. 5/8/5/45/multicentric study/2019/ECD-1.

Funding

Open access funding provided by Manipal Academy of Higher Education, Manipal.

Declarations

Funding

No funding was received to assist with the preparation of this manuscript.

Conflicts of Interest

The authors have no competing interests to declare that are relevant to the content of this article.

Ethics Approval

Not applicable.

Consent to Participate

Not applicable.

Consent for Publication

Not applicable.

Code Availability

Not applicable.

Availability of Data and Material

All data reviewed are included in the manuscript.

Author Contributions

M.R. and L.T. were involved in the conceptualization of the study and literature search. L.T. wrote the first draft of the paper. A.P.R., S.M., and M.R. critically revised the manuscript. All authors have read and approved the final manuscript.
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