Risk Factors for COVID-19 and Respiratory Tract Infections during the Coronavirus Pandemic.

(1) Background: Some individuals are more susceptible to developing respiratory tract infections (RTIs) or coronavirus disease (COVID-19) than others. The aim of this work was to identify risk factors for symptomatic RTIs including COVID-19 and symptomatic COVID-19 during the coronavirus pandemic by using infection incidence, participant baseline, and regional COVID-19 burden data. (2) Methods: Data from a prospective study of 1000 frontline healthcare workers randomized to Bacillus Calmette-Guérin vaccination or placebo, and followed for one year, was analyzed. Parametric time-to-event analysis was performed to identify the risk factors associated with (a) non-specific symptomatic respiratory tract infections including COVID-19 (RTIs+COVID-19) and (b) symptomatic RTIs confirmed as COVID-19 using a polymerase chain reaction or antigen test (COVID-19). (3) Results: Job description of doctor or nurse (median hazard ratio [HR] 1.541 and 95% confidence interval [CI] 1.299-1.822), the reported COVID-19 burden (median HR 1.361 and 95% CI 1.260-1.469 for 1.4 COVID-19 cases per 10,000 capita), or a BMI > 30 kg/m2 (median HR 1.238 and 95% CI 1.132-1.336 for BMI of 35.4 kg/m2) increased the probability of RTIs+COVID-19, while positive SARS-CoV-2 serology at enrollment (median HR 0.583 and 95% CI 0.449-0.764) had the opposite effect. The reported COVID-19 burden (median HR 2.372 and 95% CI 2.116-2.662 for 1.4 COVID-19 cases per 10,000 capita) and a job description of doctor or nurse (median HR 1.679 and 95% CI 1.253-2.256) increased the probability of developing COVID-19, while smoking (median HR 0.428 and 95% CI 0.284-0.648) and positive SARS-CoV-2 serology at enrollment (median HR 0.076 and 95% CI 0.026-0.212) decreased it. (4) Conclusions: Nurses and doctors with obesity had the highest probability of developing RTIs including COVID-19. Non-smoking nurses and doctors had the highest probability of developing COVID-19 specifically. The reported COVID-19 burden increased the event probability, while positive SARS-CoV-2 IgG serology at enrollment decreased the probability of RTIs including COVID-19, and COVID-19 specifically.

A first-in-class leucyl-tRNA synthetase inhibitor, ganfeborole, for rifampicin-susceptible tuberculosis: a phase 2a open-label, randomized trial.

New tuberculosis treatments are needed to address drug resistance, lengthy treatment duration and adverse reactions of available agents. GSK3036656 (ganfeborole) is a first-in-class benzoxaborole inhibiting the Mycobacterium tuberculosis leucyl-tRNA synthetase. Here, in this phase 2a, single-center, open-label, randomized trial, we assessed early bactericidal activity (primary objective) and safety and pharmacokinetics (secondary objectives) of ganfeborole in participants with untreated, rifampicin-susceptible pulmonary tuberculosis. Overall, 75 males were treated with ganfeborole (1/5/15/30 mg) or standard of care (Rifafour e-275 or generic alternative) once daily for 14 days. We observed numerical reductions in daily sputum-derived colony-forming units from baseline in participants receiving 5, 15 and 30 mg once daily but not those receiving 1 mg ganfeborole. Adverse event rates were comparable across groups; all events were grade 1 or 2. In a participant subset, post hoc exploratory computational analysis of 18F-fluorodeoxyglucose positron emission tomography/computed tomography findings showed measurable treatment responses across several lesion types in those receiving ganfeborole 30 mg at day 14. Analysis of whole-blood transcriptional treatment response to ganfeborole 30 mg at day 14 revealed a strong association with neutrophil-dominated transcriptional modules. The demonstrated bactericidal activity and acceptable safety profile suggest that ganfeborole is a potential candidate for combination treatment of pulmonary tuberculosis.ClinicalTrials.gov identifier: NCT03557281 .

Power to identify exposure-response relationships in phase IIa pulmonary tuberculosis trials with multi-dimensional bacterial load modeling.

Adequate power to identify an exposure-response relationship in a phase IIa clinical trial for pulmonary tuberculosis (TB) is important for dose selection and design of follow-up studies. Currently, it is not known what response marker provides the pharmacokinetic-pharmacodynamic (PK-PD) model more power to identify an exposure-response relationship. We simulated colony-forming units (CFU) and time-to-positivity (TTP) measurements for four hypothetical drugs with different activity profiles for 14 days. The power to identify exposure-response relationships when analyzing CFU, TTP, or combined CFU + TTP data was determined at 60 total participants, or with 25 out of 60 participants in the lowest and highest dosing groups (unbalanced design). For drugs with moderate bactericidal activity, power was low (<59%), irrespective of the data analyzed. Power was 1.9% to 29.4% higher when analyzing TTP data compared to CFU data. Combined analysis of CFU and TTP further improved the power, on average by 4.2%. For a drug with a medium-high activity, the total sample size needed to achieve 80% power was 136 for CFU, 72 for TTP, and 68 for combined CFU + TTP data. The unbalanced design improved the power by 16% over the balanced design. In conclusion, the power to identify an exposure-response relationship is low for TB drugs with moderate bactericidal activity or with a slow onset of activity. TTP provides the PK-PD model with more power to identify exposure-response relationships compared to CFU, and combined analysis or an unbalanced dosing group study design offers modest further improvement.

Transrenal Mycobacterium tuberculosis DNA in pulmonary tuberculosis patients during the first 14 days of treatment.

IMPORTANCE: This study presents the results of the evaluation of a novel method for the detection of Mycobacterium tuberculosis, the causative agent of tuberculosis, in urine. Detecting parts of the mycobacteria in urine is of particular interest as it allows us to use a sample that is easy to obtain and that does not require uncomfortable procedures or safety precautions like obtaining sputum for culture, which is the most commonly used sample in the diagnosis of tuberculosis. In certain groups of individuals who cannot produce sputum, for example, children, non-sputum-based methods have particular importance. We found that the method tested was able to detect bacterial killing by active antibiotics that disrupt the cell wall and lead to fragmentation of bacteria. However, the assay can't detect inactive bacteria or bacteria that are active with an intact cell wall.

Reproducibility in pharmacometrics applied in a phase III trial of BCG-vaccination for COVID-19.

Large clinical trials often generate complex and large datasets which need to be presented frequently throughout the trial for interim analysis or to inform a data safety monitory board (DSMB). In addition, reliable and traceability are required to ensure reproducibility in pharmacometric data analysis. A reproducible pharmacometric analysis workflow was developed during a large clinical trial involving 1000 participants over one year testing Bacillus Calmette-Guérin (BCG) (re)vaccination in coronavirus disease 2019 (COVID-19) morbidity and mortality in frontline health care workers. The workflow was designed to review data iteratively during the trial, compile frequent reports to the DSMB, and prepare for rapid pharmacometric analysis. Clinical trial datasets (n = 41) were transferred iteratively throughout the trial for review. An RMarkdown based pharmacometric processing script was written to automatically generate reports for evaluation by the DSMB. Reports were compiled, reviewed, and sent to the DSMB on average three days after the data cut-off, reflecting the trial progress in real-time. The script was also utilized to prepare for the trial pharmacometric analyses. The same source data was used to create analysis datasets in NONMEM format and to support model script development. The primary endpoint analysis was completed three days after data lock and unblinding, and the secondary endpoint analyses two weeks later. The constructive collaboration between clinical, data management, and pharmacometric teams enabled this efficient, timely, and reproducible pharmacometrics workflow.

Seasonal influence on respiratory tract infection severity including COVID-19 quantified through Markov Chain modeling.

Respiratory tract infections (RTIs) are a burden to global health, but their characterization is complicated by the influence of seasonality on incidence and severity. The Re-BCG-CoV-19 trial (NCT04379336) assessed BCG (re)vaccination for protection from coronavirus disease 2019 (COVID-19) and recorded 958 RTIs in 574 individuals followed over 1 year. We characterized the probability of RTI occurrence and severity using a Markov model with health scores (HSs) for four states of symptom severity. Covariate analysis on the transition probability between HSs explored the influence of demographics, medical history, severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2), or influenza vaccinations, which became available during the trial, SARS-CoV-2 serology, and epidemiology-informed seasonal influence of infection pressure represented as regional COVID-19 pandemic waves, as well as BCG (re)vaccination. The infection pressure reflecting the pandemic waves increased the risk of RTI symptom development, whereas the presence of SARS-CoV-2 antibodies protected against RTI symptom development and increased the probability of symptom relief. Higher probability of symptom relief was also found in participants with African ethnicity and with male biological gender. SARS-CoV-2 or influenza vaccination reduced the probability of transitioning from mild to healthy symptoms. Model diagnostics over calendar-time indicated that COVID-19 cases were under-reported during the first wave by an estimated 2.76-fold. This trial was performed during the initial phase of the COVID-19 pandemic in South Africa and the results reflect that situation. Using this unique clinical dataset of prospectively studied RTIs over the course of 1 year, our Markov Chain model was able to capture risk factors for RTI development and severity, including epidemiology-informed infection pressure.

Standards for model-based early bactericidal activity analysis and sample size determination in tuberculosis drug development.

Background: A critical step in tuberculosis (TB) drug development is the Phase 2a early bactericidal activity (EBA) study which informs if a new drug or treatment has short-term activity in humans. The aim of this work was to present a standardized pharmacometric model-based early bactericidal activity analysis workflow and determine sample sizes needed to detect early bactericidal activity or a difference between treatment arms. Methods: Seven different steps were identified and developed for a standardized pharmacometric model-based early bactericidal activity analysis approach. Non-linear mixed effects modeling was applied and different scenarios were explored for the sample size calculations. The sample sizes needed to detect early bactericidal activity given different TTP slopes and associated variability was assessed. In addition, the sample sizes needed to detect effect differences between two treatments given the impact of different TTP slopes, variability in TTP slope and effect differences were evaluated. Results: The presented early bactericidal activity analysis approach incorporates estimate of early bactericidal activity with uncertainty through the model-based estimate of TTP slope, variability in TTP slope, impact of covariates and pharmacokinetics on drug efficacy. Further it allows for treatment comparison or dose optimization in Phase 2a. To detect early bactericidal activity with 80% power and at a 5% significance level, 13 and 8 participants/arm were required for a treatment with a TTP-EBA0-14 as low as 11 h when accounting for variability in pharmacokinetics and when variability in TTP slope was 104% [coefficient of variation (CV)] and 22%, respectively. Higher sample sizes are required for smaller early bactericidal activity and when pharmacokinetics is not accounted for. Based on sample size determinations to detect a difference between two groups, TTP slope, variability in TTP slope and effect difference between two treatment arms needs to be considered. Conclusion: In conclusion, a robust standardized pharmacometric model-based EBA analysis approach was established in close collaboration between microbiologists, clinicians and pharmacometricians. The work illustrates the importance of accounting for covariates and drug exposure in EBA analysis in order to increase the power of detecting early bactericidal activity for a single treatment arm as well as differences in EBA between treatments arms in Phase 2a trials of TB drug development.

Early bactericidal activity studies for pulmonary tuberculosis: A systematic review of methodological aspects.

A milestone in the development of novel antituberculosis drugs is the demonstration of early bactericidal activity (EBA) in a phase IIa clinical trial. The significant variability in measurements of bacterial load complicates data analysis in these trials. A systematic review and evaluation of methods for determination of EBA in pulmonary tuberculosis studies was undertaken. Bacterial load quantification biomarkers, reporting intervals, calculation methods, statistical testing, and handling of negative culture results were extracted. In total, 79 studies were identified in which EBA was determined. Colony-forming units on solid culture media and/or time-to-positivity in liquid media were the biomarkers used most often, reported in 72 (91%) and 34 (43%) studies, respectively. Twenty-two different reporting intervals were presented, and 12 different calculation methods for EBA were identified. Statistical testing for a significant EBA compared with no change was performed in 54 (68%) studies, and between-group testing was performed in 32 (41%) studies. Negative culture result handling was discussed in 34 (43%) studies. Notable variation was found in the analysis methods and reporting of EBA studies. A standardized and clearly reported analysis method, accounting for different levels of variability in the data, could aid the generalization of study results and facilitate comparison between drugs/regimens.

Liquid chromatography-tandem mass spectrometry analysis of delamanid and its metabolite in human cerebrospinal fluid using protein precipitation and on-line solid-phase extraction.

The penetration of the antituberculosis drug delamanid into the central nervous system is not established. The distribution of delamanid and its major metabolite, DM-6705, into the cerebrospinal fluid requires investigation. A liquid chromatography-tandem mass spectrometry method for the quantification of delamanid and DM-6705 in human cerebrospinal fluid was developed and validated. The calibration range for both analytes was 0.300 - 30.0 ng/mL. The deuterium-labelled analogue of delamanid (delamanid-d4) and OPC-14714 were used as internal standards for delamanid and DM-6705, respectively. Samples were processed by protein precipitation followed by on-line solid-phase extraction and high-performance liquid chromatography on an Agilent 1260 HPLC system. A Phenomenex Gemini-NX C18 (5.0 µm, 50 mm × 2.0 mm) analytical column was used for on-line solid-phase extraction, and a Waters Xterra MS C18 (5.0 µm, 100 mm × 2.1 mm) analytical column for chromatographic separation using gradient elution, at a flow rate of 300 µL/min. The total run time was 7.5 min. Analytes were detected by multiple reaction monitoring on an AB Sciex 5500 triple quadrupole mass spectrometer at unit mass resolution, with electrospray ionization in the positive mode. Accuracy and precision were assessed over three independent validation batches. Extraction recoveries were more than 98% and were consistent across the analytical range. Both analytes in CSF exhibited non-specific adsorption to polypropylene tubes. The method was used to analyse cerebrospinal fluid samples from patients with pulmonary tuberculosis in an exploratory pharmacokinetic study.

Population Pharmacokinetics of Delamanid and its Main Metabolite DM-6705 in Drug-Resistant Tuberculosis Patients Receiving Delamanid Alone or Coadministered with Bedaquiline.

BACKGROUND AND OBJECTIVE: Delamanid is a nitroimidazole, a novel class of drug for treating tuberculosis, and is primarily metabolized by albumin into the metabolite DM-6705. The aims of this analysis were to develop a population pharmacokinetic (PK) model to characterize the concentration-time course of delamanid and DM-6705 in adults with drug-resistant tuberculosis and to explore a potential drug-drug interaction with bedaquiline when coadministered. METHODS: Delamanid and DM-6705 concentrations after oral administration, from 52 participants (of whom 26 took bedaquiline concurrently and 20 were HIV-1 positive) enrolled in the DELIBERATE trial were analyzed using nonlinear mixed-effects modeling. RESULTS: Delamanid PK were described by a one-compartment disposition model with transit compartment absorption (mean absorption time of 1.45 h [95% confidence interval 0.501-2.20]) and linear elimination, while the PK of DM-6705 metabolite were described by a one-compartment disposition model with delamanid clearance as input and linear elimination. Predicted terminal half-life values for delamanid and DM-6705 were 15.1 h and 7.8 days, respectively. The impact of plasma albumin concentrations on delamanid metabolism was not significant. Bedaquiline coadministration did not affect delamanid PK. Other than allometric scaling with body weight, no patients' demographics were significant (including HIV). CONCLUSIONS: This is the first joint PK model of delamanid and its DM-6705 metabolite. As such, it can be utilized in future exposure-response or exposure-safety analyses. Importantly, albumin concentrations, bedaquiline coadministration, and HIV co-infection (dolutegravir coadministration) did not have an effect on delamanid and DM-6705 PK.

Assessing Prolongation of the Corrected QT Interval with Bedaquiline and Delamanid Coadministration to Predict the Cardiac Safety of Simplified Dosing Regimens.

Delamanid and bedaquiline are two drugs approved to treat drug-resistant tuberculosis, and each have been associated with corrected QT interval (QTc) prolongation. We aimed to investigate the relationships between the drugs' plasma concentrations and the prolongation of observed QT interval corrected using Fridericia's formula (QTcF) and to evaluate their combined effects on QTcF, using a model-based population approach. Furthermore, we predicted the safety profiles of once daily regimens. Data were obtained from a trial where participants were randomized 1:1:1 to receive delamanid, bedaquiline, or delamanid + bedaquiline. The effect on QTcF of delamanid and/or its metabolite (DM-6705) and the pharmacodynamic interactions under coadministration were explored based on a published model between bedaquiline's metabolite (M2) and QTcF. The metabolites of each drug were found to be responsible for the drug-related QTcF prolongation. The final drug-effect model included a competitive interaction between M2 and DM-6705 acting on the same cardiac receptor and thereby reducing each other's apparent potency, by 28% (95% confidence interval (CI), 22-40%) for M2 and 33% (95% CI, 24-54%) for DM-6705. The generated combined effect was not greater but close to "additivity" in the analyzed concentration range. Predictions with the final model suggested a similar QT prolonging potential with simplified, once-daily dosing regimens compared with the approved regimens, with a maximum median change from baseline QTcF increase of 20 milliseconds in both regimens. The concentrations-QTcF relationship of the combination of bedaquiline and delamanid was best described by a competitive binding model involving the two main metabolites. Model predictions demonstrated that QTcF prolongation with simplified once daily regimens would be comparable to currently used dosing regimens.

Safety and efficacy of BCG re-vaccination in relation to COVID-19 morbidity in healthcare workers: A double-blind, randomised, controlled, phase 3 trial.

Background: BCG vaccination prevents severe childhood tuberculosis (TB) and was introduced in South Africa in the 1950s. It is hypothesised that BCG trains the innate immune system by inducing epigenetic and functional reprogramming, thus providing non-specific protection from respiratory tract infections. We evaluated BCG for reduction of morbidity and mortality due to COVID-19 in healthcare workers in South Africa. Methods: This randomised, double-blind, placebo-controlled trial recruited healthcare workers at three facilities in the Western Cape, South Africa, unless unwell, pregnant, breastfeeding, immunocompromised, hypersensitivity to BCG, or undergoing experimental COVID-19 treatment. Participants received BCG or saline intradermally (1:1) and were contacted once every 4 weeks for 1 year. COVID-19 testing was guided by symptoms. Hospitalisation, COVID-19, and respiratory tract infections were assessed with Cox proportional hazard modelling and time-to-event analyses, and event severity with post hoc Markovian analysis. This study is registered with ClinicalTrials.gov, NCT04379336. Findings: Between May 4 and Oct 23, 2020, we enrolled 1000 healthcare workers with a median age of 39 years (IQR 30-49), 70·4% were female, 16·5% nurses, 14·4% medical doctors, 48·5% had latent TB, and 15·3% had evidence of prior SARS-CoV-2 exposure. Hospitalisation due to COVID-19 occurred in 15 participants (1·5%); ten (66·7%) in the BCG group and five (33·3%) in the placebo group, hazard ratio (HR) 2·0 (95% CI 0·69-5·9, p = 0·20), indicating no statistically significant protection. Similarly, BCG had no statistically significant effect on COVID-19 (p = 0·63, HR = 1·08, 95% CI 0·82-1·42). Two participants (0·2%) died from COVID-19 and two (0·2%) from other reasons, all in the placebo group. Interpretation: BCG did not protect healthcare workers from SARS-CoV-2 infection or related severe COVID-19 disease and hospitalisation. Funding: Funding provided by EDCTP, grant number RIA2020EF-2968. Additional funding provided by private donors including: Mediclinic, Calavera Capital (Pty) Ltd, Thys Du Toit, Louis Stassen, The Ryan Foundation, and Dream World Investments 401 (Pty) Ltd. The computations were enabled by resources in project SNIC 2020-5-524 provided by the Swedish National Infrastructure for Computing (SNIC) at UPPMAX, partially funded by the Swedish Research Council through grant agreement No. 2018-05,973.

Early Bactericidal Activity of Meropenem plus Clavulanate (with or without Rifampin) for Tuberculosis: The COMRADE Randomized, Phase 2A Clinical Trial.

Rationale: Carbapenems are recommended for treatment of drug-resistant tuberculosis. Optimal dosing remains uncertain. Objectives: To evaluate the 14-day bactericidal activity of meropenem, at different doses, with or without rifampin. Methods: Individuals with drug-sensitive pulmonary tuberculosis were randomized to one of four intravenous meropenem-based arms: 2 g every 8 hours (TID) (arm C), 2 g TID plus rifampin at 20 mg/kg once daily (arm D), 1 g TID (arm E), or 3 g once daily (arm F). All participants received amoxicillin/clavulanate with each meropenem dose. Serial overnight sputum samples were collected from baseline and throughout treatment. Median daily fall in colony-forming unit (CFU) counts per milliliter of sputum (solid culture) (EBACFU0-14) and increase in time to positive culture (TTP) in liquid media were estimated with mixed-effects modeling. Serial blood samples were collected for pharmacokinetic analysis on Day 13. Measurements and Main Results: Sixty participants enrolled. Median EBACFU0-14 counts (2.5th-97.5th percentiles) were 0.22 (0.12-0.33), 0.12 (0.057-0.21), 0.059 (0.033-0.097), and 0.053 (0.035-0.081); TTP increased by 0.34 (0.21-0.75), 0.11 (0.052-0.37), 0.094 (0.034-0.23), and 0.12 (0.04-0.41) (log10 h), for arms C-F, respectively. Meropenem pharmacokinetics were not affected by rifampin coadministration. Twelve participants withdrew early, many of whom cited gastrointestinal adverse events. Conclusions: Bactericidal activity was greater with the World Health Organization-recommended total daily dose of 6 g daily than with a lower dose of 3 g daily. This difference was only detectable with solid culture. Tolerability of intravenous meropenem, with amoxicillin/clavulanate, though, was poor at all doses, calling into question the utility of this drug in second-line regimens. Clinical trial registered with www.clinicaltrials.gov (NCT03174184).

Pharmacokinetics of bedaquiline in cerebrospinal fluid (CSF) in patients with pulmonary tuberculosis (TB).

BACKGROUND: With current treatment options most patients with CNS TB develop severe disability or die. Drug-resistant tuberculous meningitis is nearly uniformly fatal. Novel treatment strategies are needed. Bedaquiline, a potent anti-TB drug, has been reported to be absent from CSF in a single report. OBJECTIVES: To explore the pharmacokinetics of bedaquiline and its M2 metabolite in the CSF of patients with pulmonary TB. PATIENTS AND METHODS: Individuals with rifampicin-resistant pulmonary TB established on a 24 week course of treatment with bedaquiline underwent a lumbar puncture along with multiple blood sample collections over 24 h for CSF and plasma pharmacokinetic assessment, respectively. To capture the expected low bedaquiline and M2 concentrations (due to high protein binding in plasma) we optimized CSF collection and storage methods in vitro before concentrations were quantified via liquid chromatography with tandem MS. RESULTS: Seven male participants were enrolled, two with HIV coinfection. Using LoBind® tubes lined with a 5% BSA solution, bedaquiline and M2 could be accurately measured in CSF. Bedaquiline and M2 were present in all patients at all timepoints at concentrations similar to the estimated unbound fractions in plasma. CONCLUSIONS: Bedaquiline and M2 penetrate freely into the CSF of pulmonary TB patients with a presumably intact blood-brain barrier. Clinical studies are urgently needed to determine whether bedaquiline can contribute meaningfully to the treatment of CNS TB.