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 Table of Contents  
Year : 2021  |  Volume : 10  |  Issue : 4  |  Page : 457-462

Pharmacodynamic biomarkers for quantifying the mycobacterial effect of high doses of rifampin in patients with rifampin-susceptible pulmonary tuberculosis

1 Kibong'oto Infectious Diseases Hospital (KIDH), Research Department, Siha, Kilimanjaro, Tanzania; Center for Innovative Drug Development and Therapeutic Trials for Africa (CDT-Africa), College of Health Sciences, Addis Ababa University, Charlottesville, Virginia, USA
2 Division of Infectious Diseases and International Health, University of Virginia, Charlottesville, Virginia, USA
3 Center for Innovative Drug Development and Therapeutic Trials for Africa (CDT-Africa), College of Health Sciences, Addis Ababa University, Charlottesville, Virginia; Global One Health initiative, Office of International Affairs, The Ohio State University, Columbus, Ohio, USA
4 Radboud Institute for Health Sciences, Radboud University Medical Center, Nijmegen, the, Netherlands
5 Kilimanjaro Clinical Research Institute, Kilimanjaro Christian Medical Centre, Tumaini University, Moshi, Tanzania
6 Kibong'oto Infectious Diseases Hospital (KIDH), Research Department, Siha, Kilimanjaro, Tanzania
7 Kibong'oto Infectious Diseases Hospital (KIDH), Research Department, Siha, Kilimanjaro; Department of Global Health and Biomedical Sciences, School of Life Sciences and Bioengineering, Nelson Mandela African Institution of Science and Technology (NM-AIST), Arusha, Tanzania

Date of Submission01-Sep-2021
Date of Decision18-Sep-2021
Date of Acceptance20-Oct-2021
Date of Web Publication13-Dec-2021

Correspondence Address:
Bibie N Said
Kibong'oto Infectious Diseases Hospital, P.O BOX 12, Siha, Kilimanjaro

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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/ijmy.ijmy_178_21

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Background: Suboptimal drug exposure in patients with drug-susceptible tuberculosis (DS-TB) can drive treatment failure. Pharmacodynamics (PD) biomarkers such as the plasma TB drug-activity (TDA) assay may guide dose finding studies and predict microbiological outcomes differently than conventional indices. Methods: A study was nested from phase 2b randomized double-blind controlled trial of Tanzanian patients who received a 600 mg, 900 mg, or 1200 mg with a standard dose for DS-TB. Serum at 6 weeks collected over 24-h at 2-h intervals was collected for rifampin area under the concentration–time curve relative to minimum inhibitory concentration (AUC0-24/MIC) or peak concentration and MIC (Cmax/MIC). TDA was the ratio of time-to-positive growth of the patient's Mycobacterium tuberculosis isolates with and without coculture of patient's plasma collected at Cmax. Spearman's rank correlation (r) between PD parameters and culture convention on both liquid and solid culture media. Results: Among 10 patients, 600 mg (3), 900 mg (3), and 1200 mg (4) of rifampin dosages. The mean ± standard deviation (SD) of AUC0-24/MIC for patients on 600 mg was 168 ± 159 mg·h/L, on 900 mg was 169 ± 166 mg·h/L, and on 1200 mg was 308 ± 238 mg·h/L. The mean-TDA (SD) was 2.56 (±0.75), 1.5 (±0.59), and 2.29 (±1.08) for patients on 600 mg, 900 mg, and 1200 mg rifampin doses, respectively. Higher TDA values correlated with faster time to culture convention on both liquid (r = −0.55, P = 0.099) and solid media (r = −0.65, P = 0.04). Conclusions: TDA and rifampin AUC0-24/MIC did not trend as expected with rifampin dose, but TDA better predicted the time to sputum culture conversion. TDA may provide additional discrimination in predicting treatment response for some regimens distinct from plasma exposure relative to MIC or mg/kg dose.

Keywords: Mycobacterial activity, pharmacodynamic biomarkers, tuberculosis, tuberculosis drug activity

How to cite this article:
Said BN, Heysell SK, Yimer G, Aarnoutse RE, Kibiki GS, Mpagama S, Mbelele PM. Pharmacodynamic biomarkers for quantifying the mycobacterial effect of high doses of rifampin in patients with rifampin-susceptible pulmonary tuberculosis. Int J Mycobacteriol 2021;10:457-62

How to cite this URL:
Said BN, Heysell SK, Yimer G, Aarnoutse RE, Kibiki GS, Mpagama S, Mbelele PM. Pharmacodynamic biomarkers for quantifying the mycobacterial effect of high doses of rifampin in patients with rifampin-susceptible pulmonary tuberculosis. Int J Mycobacteriol [serial online] 2021 [cited 2022 Aug 16];10:457-62. Available from: https://www.ijmyco.org/text.asp?2021/10/4/457/332349

  Introduction Top

Tuberculosis (TB) is still a major chronic infectious disease of humankind, caused by Mycobacterium tuberculosis.[1] For the past 10 years, the annual estimates of TB incidence rate remained at 10 million people worldwide.[2] TB remains the leading cause of death from a single bacteria accounting for approximately 1.4 million deaths in 2019.[3],[4],[5] In resource-limited settings like Tanzania, TB is treated based on an adapted “one-size fits all” regimen for all patients with weight-based stratifications of dosages.[6] Such strategies may not account for the considerable pharmacokinetic (PK) variability observed in people with common comorbidities such as human immunodeficiency virus (HIV), diabetes mellitus, or malnutrition, which can impact drug absorption, distribution, metabolism, and excretion. PK variability, particularly failure to reach minimal exposure targets, may result in unfavorable TB treatment outcomes including clinical or microbiological treatment failures, relapse of disease after treatment completion, and acquired drug resistance.[7],[8]

Globally, unfavorable treatment outcomes occur in 15% of all cases.[3],[9] Most anti-TB drugs are concentration dependent in their activity, whereby higher concentrations relative to the M. tuberculosis minimum inhibitory concentration (MIC) result in improved killing.[10],[11],[12] Improving exposures, such as with higher milligram per kilogram (mg/kg) dosages, may not only prevent treatment failure but also lead to regimens of significantly shorter treatment duration.[13]

Conventional pharmacodynamics (PD) indices such as the 24-hour area under the concentration–time curve (AUC0-24) or maximum achieved concentration (Cmax) can be measured in the serum, and for some critical anti-TB drugs such as rifampin, have been associated with declines in sputum M. tuberculosis bacterial count over time on treatment.[14] In addition, bacterial killing can also be measured by coculture of M. tuberculosis with a patient's whole blood or plasma while on TB treatment.[13] The use of plasma collected at the time of estimated Cmax for an anti-TB drug has been termed the TB drug activity (TDA) assay and calculated as the ratio of the time to detection (TTD) of plasma cocultured with a standardized inoculum of the patient's own M. tuberculosis to the TTD of M. tuberculosis inoculum alone without first coculturing with plasma.[15] TDA values >1 indicate killing of bacteria with drug present in the plasma. To date, TDA has been performed in observational settings in people treated with traditional doses of rifampin at the minimal efficacious dose (~10 mg/kg or 600 mg maximum). To compare TDA to other conventional PD indices, we studied a subset of patients enrolled in a trial of higher dosages of rifampin in Tanzania.

  Subjects and Methods Top

Designs and patients

This was a secondary data analysis for patients who were consented to participate in a clinical phase trial IIb of 600 mg, rifampin at 900 mg, or 1,200 mg with a standard background regimen of isoniazid, pyrazinamide, and ethambutol for streptomycin, in a drug- susceptible pulmonary TB patients from July 2010 to September 2013 in Tanzania. The study was approved by the Kilimanjaro Christian Medical College Research Ethics and Review Committee (CRERC), the Ifakara Health Institute Institutional Review Board (IHI-IRB), and the Tanzanian National Health Research Ethics Subcommittee (NatHREC). The trial was registered at ClinicalTrials.gov under identifier NCT00760149 (https://clinicaltrials.gov/ct2/show/NCT00760149). This secondary analysis was additionally approved by the Scientific and Ethics Review Committee of CDT-Africa by ref no. CDT/0278/21 and the administrations of the study sites including the Kibong'oto Infectious Diseases Hospital and Mawenzi Regional Hospital in the Kilimanjaro region and IHI/Bagamoyo Research and Training Centre.

Source data and variables collected

Datasets for this secondary analysis were sought from the corresponding author of the primary study.[16] From these datasets, we abstracted (i) clinical and demographic data such as gender, age, weight, and height and (ii) 6-week PK/PD data including drug dosage, rifampin Cmax, rifampin time to maximum concentration (Tmax), rifampin AUC0-24, and TDA. Plasma samples for TDA were collected at 2 h after a directly observed dose. Cmax and Tmax were observed values, and AUC0-24 was calculated. All were using non-compartmental analysis with software WinNonLin version 6.3 software (Pharsight Corp, Mountain View, CA, USA). PK performed from samples collected at 1, 1.5, 2, 2.5, 3, 4, 6, 8, 10, and 24 hours after the directly observed dose. Plasma was separated within 1 h of collection of blood and was frozen at 20°C, transferred to 80°C within 72 h, and transported on dry ice to the Radboud University Medical Center, Nijmegen, the Netherlands, for bioanalysis by ultraperformance liquid chromatographic. TDA was performed onsite at the Kilimanjaro Clinical Research Institute. Sputum culture results of both solid Lowenstein-Jensen (LJ) and liquid media in the mycobacteria growth indicator tube (MGIT, Bactec), from pretreatment, 4, 6, 8, 10, and 12 weeks were used to determine the time to sputum culture conversion to negative (no growth). The MIC for rifampin from the M. tuberculosis pretreatment isolate was measured by Sensititre MycoTB MIC plate as described previously using serial 2-fold dilutions of antibiotics.[17] The M. tuberculosis H37Rv strain was included as an internal control in MGIT, and the MIC of a drug was considered the lowest concentration able to inhibit visible growth.

Data management and statistical analysis

Variables were recorded in Excel and involved constructing conventional PD parameters (AUC0-24 h/MIC, Cmax/MIC), by dividing PK values by the rifampin MIC. For continuous data, mean and standard deviation (SD) among the three rifampin arms were compared using ANOVA. Nonparametric data variables were presented using median and interquartile range (IQR). PD parameters (AUC0-24 h/MIC or Cmax/MIC) were compared among the different drug dosage groups using Kruskal–Wallis test. Spearman's rank correlation tested correlation coefficient (r) between plasma drug activity (TDA) and sputum culture conversion on both MGIT and LJ and correlation between TDA and rifampin Cmax/MIC. All statistical calculations were performed using R version 4.0.5 (2021-03-31) (https://www.r-project.org/).

  Results Top

Patients characteristics

In total, 37 patients were enrolled and had plasma collected for PK testing at 6 weeks. However, of these, only 10 patients met full inclusion criteria with MIC testing available [Figure 1]. Of the 10 patients, 3 received 600 mg, 3 received 900 mg, and 4 received 1200 mg of rifampin. In total, 9 (90%) of the patients were male and had a mean (± SD) age of 40.1 ± 7.9 years. All patients were above 50 kg and their mean body weight was 55.6 ± 3.3. The mean Cmax concentration for patients receiving the standard dosage of 600 mg of rifampin was below the recommended minimum reference value of at least 8 mg/liter, but there was a significant increase in Cmax concentration (P = 0.04) and AUC0-24 (P = 0.02) with dose increase [Table 1].
Table 1: Demographic and pharmacokinetic values within the rifampin dose categories for participants with pulmonary tuberculosis after 6 weeks of treatment

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Figure 1: Study flow diagram showing the participants selection during extraction of data from the main database

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The overall mean ± SD AUC0-24/MIC was 224.7 ± 188.4, which only increased in the 1200 mg rifampin dosage group [Table 2]. Furthermore, the overall median (interquartile-range) rifampin of Cmax/MIC was 37.7 (1.2 – 75.9) and it showed a non-statistically significant increase in median value (p= 0.689), with 26.7(13.4 – 52.1) for those receiving 600 mg rifampin, 38.5 (19.7 – 57.2) for those receiving 900 mg, and 57.5 (36.8 –91.0) for receiving 1200 mg [[Table 2], P = 0.762]. [Table 2] demonstrates the importance of MIC whereby Cmax and AUC0-24 increased significantly with dose category [Table 1]; this was also observed slightly when including MIC [Table 2] for which even a two-dilution μg/mL increase in MIC within an otherwise susceptible range can dramatically lower the AUC0-24/MIC value.
Table 2: Pharmacodynamics parameters on different rifampin dosages

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Pharmacodynamic indices and sputum culture conversion

While the mean TDA values did not consistently increase with increasing dose category from 600mg, 900 to 1200mg (2.2 ±0.75, 1.36 ± 0.59, 3.2 ±1.05) [Table 2] (P = 0.855), this did not mirror the rifampin AUC0-24/MIC changes within the dose categories but both the lowest AUC0-24/MIC and TDA values were observed for the patients in the 600 and 900 mg dosage categories. Previously, a TDA value of 1.5 or greater indicated a non-stasis degree of killing, and in this study 7 (78%) of patients had TDA values of 1.5 or greater (regardless of dosage category). However, we did observe a significant linear correlation with higher 6-week TDA values and faster time to sputum culture conversion in both MGIT and LJ (R = -0.55, P = 0.099) and (R = -0.65, P = 0.04) by Spearman's-rank correlation test in [Figure 2]. This is contrary to the lack of correlation of rifampin AUC0-24/MIC and time to sputum culture conversion in both MGIT and LJ (R = 0.24, P = 0.5) and (R = 0.0098, P = 0.79) by Spearman's-rank correlation test in [Figure 3]. A similar lack of correlation of rifampin Cmax/MIC and time to sputum culture conversion in MGIT (R = 0.045, P = 0.9) and LJ (R = 0.086, P = 0.81).
Figure 2: (a) Tuberculosis drug-activity versus Time to culture conversion in mycobacteria growth indicator tube and (b) Time to culture conversion in Lowenstein-Jensen

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Figure 3: (a) Rifampin AUC0-24/MIC versus Time to culture conversion in mycobacteria growth indicator tube and (b) Time to culture conversion in Lowenstein-Jensen

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  Discussion Top

In this study of PD biomarkers (Cmax/MIC, AUC0-24/MIC) and TDA with different rifampin dosages, while PK exposure generally increased with increased dose, the effect was blunted when considering MIC. TDA appeared to correlate better with sputum culture conversion in both MGIT and LJ at 12 weeks than with conventional PD biomarkers.

In strains of M. tuberculosis that are susceptible to rifampin, TDA determinations can offer some proof for dose adjustment through increases in Cmax/MIC and enhanced killing by rifampin.[18] The current study included a minimal number of subjects in each dosing and given this small number of participants, there was no significant correlation of rifampin Cmax/MIC and TDA, as would otherwise have been expected. Furthermore, the TDA assay includes plasma containing all administered drugs (rifampin, isoniazid, pyrazinamide, and ethambutol), and therefore individual variability of another drug peak concentration besides rifampin may have accounted for more of the bacterial killing in a given TDA assay that could have obscured trends across rifampin dosage group. Plasma drug concentrations other than rifampin were not available. Patients in the 600 mg and 1200 mg groups did have the highest mean TDA, which were well above the cutoff of 1.5, which previously had been associated with bacterial killing above stasis.[19]

It was identified that concentration not constantly varying as expected in subjects initiating drug-susceptible TB (DS-TB) treatment at different rifampin drug dosages when measured at 6 weeks of treatment, which reinforced prior observations that even with dose increase, rifampin exhibits considerable PK variability.[20] Despite inter-individual PK variability and expected variability of MIC with so few participants, there was still a slightly mean increase in AUC0–24/MIC and at the highest increase in rifampin dosage of the 1200 mg arm there was increase of 1.8-fold above the conventional 600 mg arm (from 168 to 308 mg h/liter), which reflects a dose-proportional increase in the level of exposure with the dose. Other studies have found a greater exposure (AUC0-24) response relative to dose doubling for rifampin and may indicate that in this subset of the population, that 1200 mg may even be on the lower end of the dose–response curve. Further studies should follow the PK-PD guidelines for the development of antimicrobial medicinal products by the Committee for Medicinal Products for Human Use (CHMP).[21]

The main objective of this study was to compare PD parameters for rifampin that describe the mycobactericidal effect of high rifampin dose. In the hollow fiber model, an in vitro system used for dose finding and novel regimen development, rifampin AUC0-6/MIC ratios >24.14 (96.56 in 24 h) were associated with improved killing capacity against M. tuberculosis[22] The overall mean rifampin AUC0-24/MIC in this study was 254 (63.5 in 6 h), thus exceeding the in vitro system threshold. In line with these findings, a study model demonstrated by Kloprogge et al. of MIC-adjusted PK estimates (Cmax/MIC or AUC0-24/MIC) found association with those indices and sterilizing effect of anti-TB drugs at month 2 during treatment.[23] In contrast, our study did not find a correlation with rifampin Cmax/MIC or AUC0-24/MIC and time to sputum culture conversion. It is possible that measurement of a single day of drug exposure at 6 weeks as was done in this study does not fully capture the PD dynamics over the entire 2 months of treatment.

Instead, this study demonstrated the important differences among PD parameters, such as the difference in individual drug AUC0-24/MIC (for in this case, rifampin) and total drug plasma PD (in this case, TDA) in predicting microbiological outcome.[24],[25],[26],[27] The superiority of TDA in predicting time to sputum culture conversion may not only be reflective of the multiple drug concentrations in the plasma but also contributed by the variability of growth mechanisms for the M. tuberculosis plasma co-cultured. While these PD parameters can serve as important targets for dose finding studies and development of novel drug regimens, they may also be used to target individual dose optimization in routine clinical care. Unfortunately, chromatography or mass spectrometry for the measurement of drug concentrations from plasma is not currently available in most TB endemic settings, and MIC testing requires a cultured M. tuberculosis isolate and additional weeks of time for incubation in the presence of drugs. Thus, for some settings, a TDA procedure may be more practical to perform. More definitively, though this study highlights the need to scale up capacity for alternative forms of PK testing such as with dried blood spot which bypasses plasma collection and the cold chain,[28] or spectrophotometric assays which have been performed on saliva and urine.[24],[25] With closer to the point-of-care PK testing coupled with rapid sequencing techniques of M. tuberculosis from direct specimens with an improved bioinformatics pipeline such that specific drug resistance mutations can better predict MIC change, prior equipment intensive procedures may ultimately be rendered unnecessary.

The overall mean value of TDA did not consistently increase with rifampin drug dosages, which is different from previous studies that showed that TDA assay was mainly found to measure the concentration-dependent activity of the rifampin levels and thus TDA values increase as concentrations increase.[18],[26] However, our lack of increase was only observed between the 600 and 900 mg doses and reflected higher MIC values in the few patients in the 900 mg dose category. TDA increased considerably in the 1200 mg category from 600mg doses, and this poses expectation of more consistent trend of TDA increase with all increasing doses that would have been observed with a larger sample size.

Higher doses of up to 32–35 mg/kg of rifampin have shown to be potential for shortening the total duration of the regimen.[27],[29] In this study the highest dose category (1200mg) of rifampin total dose was closer to 20 mg/kg in and given that most patients attained sputum culture conversion relatively early, the 10mg/kg dose may have been too low to observe differences from the conventional 600 mg category. Further studies of dosages of 30 mg/kg or above may also be better designed to measure PD indices over time. For example, in a study by Ndusilo et al. evaluating a regimen for drug-resistant TB,[30] the majority of patients had a significant increase in TDA from 2 weeks to 4 weeks, and TDA increase was associated with a favorable treatment outcome.

The number of participants in this study is the main limitation and it may be difficult to make more generalized conclusions based on only few cases with available plasma PK, MIC, and TDA results. Second, other host comorbidities that could have influenced drug absorption or metabolism were not considered in comparison of PD parameters and the clinical outcome of time to sputum culture conversion. It may be possible with a larger sample size, for instance, that a PD parameter such as TDA performs differently among people with HIV or another comorbidity. Furthermore, while TDA has been studied for other anti-TB drugs including in MDR-TB regimens with drugs such as the fluoroquinolones,[30] this current study was restricted to different dosages of rifampin.

In a small subset of people with pulmonary TB in Tanzania, a 1200 mg dosage of rifampin produced significantly higher rifampin plasma Cmax and AUC0-24 at 6 weeks of treatment, with improved AUC0-24/MIC and TDA. Plasma TDA, a biomarker of all drug activity, demonstrated the greatest bacterial killing for patients in the 1200 mg rifampin dose category and importantly correlated with time to sputum culture conversion, whereby the patients with the highest TDA values demonstrated the fastest time to microbiological cure. The rifampin dose of 1200 mg appears to be an appropriate starting dose for further studies of higher dose and PK target attainment. TDA may provide further discrimination for understanding multiple drug PD interactions. Larger sample sizes among patients with diverse comorbidities should be employed to further study TDA for not only dose finding studies but practical implementation of individualized dosing in routine practice.

Ethical clearance

A waiver of informed consent was obtained from Scientific and Ethics Review Committee (SERC) of Centre for Innovative Drug Development and Therapeutic Trials for College of Health Sciences, Addis Ababa University.

Financial support and sponsorship

This project is part of the EDCTP2 program supported by the European Union (grant number TMA2016SF-1463-REMODEL-TZ), the Center for Innovative Drug Development and Therapeutic Trials for Africa (CDT-Africa), College of Health Sciences, Addis Ababa University.

Conflicts of interest

There are no conflicts of interest.

  References Top

Sriwijitalai W, Wiwanitkit V. Drug–drug interaction analysis: Antituberculosis drugs versus antiretroviral drugs. Biomed Biotechnol Res J 2019;3:101.  Back to cited text no. 1
  [Full text]  
MacNeil A, Glaziou P, Sismanidis C, Date A, Maloney S, Floyd K. Global epidemiology of tuberculosis and progress toward meeting global targets – Worldwide, 2018. MMWR Morb Mortal Wkly Rep 2020;69:281-5.  Back to cited text no. 2
World Health Organization. (2020). Global tuberculosis report 2020. World Health Organization. Available from: https://apps.who.int/iris/handle/10665/336069. License: CC BY-NC-SA 3.0 IGO. [Last accessed on 2020 Oct 13]  Back to cited text no. 3
Fukunaga R, Glaziou P, Harris JB, Date A, Floyd K, Kasaeva T. Epidemiology of Tuberculosis and Progress Toward Meeting Global Targets — Worldwide, 2019. MMWR Surveill Summ 2021;70:427-30.  Back to cited text no. 4
MacNeil A, Glaziou P, Sismanidis C, Date A, Maloney S, Floyd K. Global Epidemiology of Tuberculosis and Progress Toward Meeting Global Targets – Worldwide, 2018. MMWR Morb Mortal Wkly Rep 2019;68:263-6.  Back to cited text no. 5
World Health Organization. (2017). Guidelines for treatment of drug-susceptible tuberculosis and patient care, 2017 update. World Health Organization. Available from: https://apps.who.int/iris/handle/10665/255052. License: CC BY-NC-SA 3.0 IGO. [Last accessed on 2017 Apr 24]  Back to cited text no. 6
Ramachandran G, Agibothu Kupparam HK, Vedhachalam C, Thiruvengadam K, Rajagandhi V, Dusthackeer A, et al. Factors influencing tuberculosis treatment outcome in adult patients treated with thrice-weekly regimens in India. Antimicrob Agents Chemother 2017;61:e02464-16.  Back to cited text no. 7
Rashak HA, Sánchez-Pérez HJ, Abdelbary BE, Bencomo-Alerm A, Enriquez-Ríos N, Gómez-Velasco A, et al. Diabetes, undernutrition, migration and indigenous communities: Tuberculosis in Chiapas, Mexico. Epidemiol Infect 2019;147:e71.  Back to cited text no. 8
Arsad FS, Ismail NH. Unsuccessful treatment outcome and associated factors among smear-positive pulmonary tuberculosis patients in Kepong district, Kuala Lumpur, Malaysia. J Heal Res 2021. [ahead-of-print].  Back to cited text no. 9
Holden IK, Lillebaek T, Seersholm N, Andersen PH, Wejse C, Johansen IS. Predictors for Pulmonary tuberculosis treatment outcome in Denmark 2009-2014. Sci Rep 2019;9:12995.  Back to cited text no. 10
Choi R, Jeong BH, Koh WJ, Lee SY. Recommendations for optimizing tuberculosis treatment: Therapeutic drug monitoring, pharmacogenetics, and nutritional status considerations. Ann Lab Med 2017;37:97-107.  Back to cited text no. 11
Diallo A, Dahourou DL, Dah TT, Tassembedo S, Sawadogo R, Meda N. Factors associated with tuberculosis treatment failure in the Central East Health region of Burkina Faso. Pan Afr Med J 2018;30:293.  Back to cited text no. 12
Mollel EW, Todd J, Mahande MJ, Msuya SE. Effect of tuberculosis infection on mortality of HIV-infected patients in Northern Tanzania. Trop Med Health 2020;48:26.  Back to cited text no. 13
Nicolau DP. Optimizing outcomes with antimicrobial therapy through pharmacodynamic profiling. J Infect Chemother 2003;9:292-6.  Back to cited text no. 14
Gehring U, Gruzieva O, Agius RM, Beelen R, Custovic A, Cyrys J, et al. Air pollution exposure and lung function in children: The ESCAPE project. Environ Health Perspect 2013;121:1357-64.  Back to cited text no. 15
Aarnoutse RE, Kibiki GS, Reither K, Semvua HH, Haraka F, Mtabho CM, et al. Pharmacokinetics, tolerability, and bacteriological response of rifampin administered at 600, 900, and 1,200 milligrams daily in patients with pulmonary tuberculosis. Antimicrob Agents Chemother 2017;61:e01054-17.  Back to cited text no. 16
Heysell SK, Pholwat S, Mpagama SG, Pazia SJ, Kumburu H, Ndusilo N, et al. Sensititre MycoTB plate compared to Bactec MGIT 960 for first- and second-line antituberculosis drug susceptibility testing in Tanzania: A call to operationalize MICs. Antimicrob Agents Chemother 2015;59:7104-8.  Back to cited text no. 17
Heysell SK, Mtabho C, Mpagama S, Mwaigwisya S, Pholwat S, Ndusilo N, et al. Plasma drug activity assay for treatment optimization in tuberculosis patients. Antimicrob Agents Chemother 2011;55:5819-25.  Back to cited text no. 18
Mpagama SG, Ndusilo N, Stroup S, Kumburu H, Peloquin CA, Gratz J, et al. Plasma drug activity in patients on treatment for multidrug-resistant tuberculosis. Antimicrob Agents Chemother 2014;58:782-8.  Back to cited text no. 19
Abulfathi AA, Decloedt EH, Svensson EM, Diacon AH, Donald P, Reuter H. Clinical pharmacokinetics and pharmacodynamics of rifampicin in human tuberculosis. Clin Pharmacokinet 2019;58:1103-29.  Back to cited text no. 20
Committee for Human Medicinal Products (CHMP). Guideline on the use of pharmacokinetics and pharmacodynamics in the development of antibacterial medicinal products. Eur Med Agency 2016;44:1-21.  Back to cited text no. 21
Jayaram R, Gaonkar S, Kaur P, Suresh BL, Mahesh BN, Jayashree R, et al. Pharmacokinetics-pharmacodynamics of rifampin in an aerosol infection model of tuberculosis. Antimicrob Agents Chemother 2003;47:2118-24.  Back to cited text no. 22
Kloprogge F, Mwandumba HC, Banda G, Kamdolozi M, Shani D, Corbett EL, et al. Longitudinal pharmacokinetic-pharmacodynamic biomarkers correlate with treatment outcome in drug-sensitive pulmonary tuberculosis: A population pharmacokinetic-pharmacodynamic analysis. Open Forum Infect Dis 2020;7:ofaa218.  Back to cited text no. 23
Szipszky C, Van Aartsen D, Criddle S, Rao P, Zentner I, Justine M, et al. Determination of rifampin concentrations by urine colorimetry and mobile phone readout for personalized dosing in tuberculosis treatment. J Pediatric Infect Dis Soc 2021;10:104-11.  Back to cited text no. 24
Mohamed S, Mvungi HC, Sariko M, Rao P, Mbelele P, Jongedijk EM, et al. Levofloxacin pharmacokinetics in saliva as measured by a mobile microvolume UV spectrophotometer among people treated for rifampicin-resistant TB in Tanzania. J Antimicrob Chemother 2021;76:1547-52.  Back to cited text no. 25
Niward K, Ek Blom L, Davies Forsman L, Bruchfeld J, Eliasson E, Schön T, et al. Plasma Levels of rifampin correlate with the tuberculosis drug activity assay. Antimicrob Agents Chemother 2018;62:e00218-18.  Back to cited text no. 26
Boeree MJ, Heinrich N, Aarnoutse R, Diacon AH, Dawson R, Rehal S, et al. High-dose rifampicin, moxifloxacin, and SQ109 for treating tuberculosis: A multi-arm, multi-stage randomised controlled trial. Lancet Infect Dis 2017;17:39-49.  Back to cited text no. 27
Zuur MA, Veenhof H, Aleksa A, Van't Boveneind-Vrubleuskaya N, Darmawan E, Hasnain MG, et al. Quality assessment of dried blood spots from patients with tuberculosis from 4 countries. Ther Drug Monit 2019;41:714-8.  Back to cited text no. 28
Seijger C, Hoefsloot W, Bergsma-de Guchteneire I, Te Brake L, van Ingen J, Kuipers S, et al. High-dose rifampicin in tuberculosis: Experiences from a Dutch tuberculosis centre. PLoS One 2019;14:e0213718.  Back to cited text no. 29
Ndusilo ND, Heysell SK, Mpagama SG, Gratz J, Segesela FH, Pazia SJ, et al. Improvement in plasma drug activity during the early treatment interval among Tanzanian patients with multidrug-resistant tuberculosis. PLoS One 2015;10:e0122769.  Back to cited text no. 30


  [Figure 1], [Figure 2], [Figure 3]

  [Table 1], [Table 2]


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