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

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

Abstract 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

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

Abstract 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

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

Abstract 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

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 identi-fied 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, respec-tively. 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

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

Background: Delamanid is a nitroimidazole, a novel class of drug for treating tuberculosis. Delamanid 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 co-administered.  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 was 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. The PK of DM-6705 metabolite, was 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 hours and 7.8 days, respectively. The impact of plasma albumin concentrations on delamanid metabolism was not significant. Bedaquiline co-administration did not affect delamanid PK. Other than allometric scaling with body weight, no patients’ demographics were significant (including HIV).  Conclusions: This is the first published 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 co-administration, and HIV co-infection (dolutegravir co-administration) did not have an effect on delamanid and DM-6705 PK

DataSheet1_Standards for model-based early bactericidal activity analysis and sample size determination in tuberculosis drug development.docx

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.</p

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

Bedaquiline-pretomanid-moxifloxacin-pyrazinamide for drug-sensitive and drug-resistant pulmonary tuberculosis treatment: a phase 2c, open-label, multicentre, partially randomised controlled trial

Background The current tuberculosis (TB) drug development pipeline is being re-populated with candidates, including nitroimidazoles such as pretomanid, that exhibit a potential to shorten TB therapy by exerting a bactericidal effect on non-replicating bacilli. Based on results from preclinical and early clinical studies, a four-drug combination of bedaquiline, pretomanid, moxifloxacin, and pyrazinamide (BPaMZ) regimen was identified with treatment-shortening potential for both drug-susceptible (DS) and drug-resistant (DR) TB. This trial aimed to determine the safety and efficacy of BPaMZ. We compared 4 months of BPaMZ to the standard 6 months of isoniazid, rifampicin, pyrazinamide, and ethambutol (HRZE) in DS-TB. 6 months of BPaMZ was assessed in DR-TB. Methods SimpliciTB was a partially randomised, phase 2c, open-label, clinical trial, recruiting participants at 26 sites in eight countries. Participants aged 18 years or older with pulmonary TB who were sputum smear positive for acid-fast bacilli were eligible for enrolment. Participants with DS-TB had Mycobacterium tuberculosis with sensitivity to rifampicin and isoniazid. Participants with DR-TB had M tuberculosis with resistance to rifampicin, isoniazid, or both. Participants with DS-TB were randomly allocated in a 1:1 ratio, stratified by HIV status and cavitation on chest radiograph, using balanced block randomisation with a fixed block size of four. The primary efficacy endpoint was time to sputum culture-negative status by 8 weeks; the key secondary endpoint was unfavourable outcome at week 52. A non-inferiority margin of 12% was chosen for the key secondary outcome. Safety and tolerability outcomes are presented as descriptive analyses. The efficacy analysis population contained patients who received at least one dose of medication and who had efficacy data available and had no major protocol violations. The safety population contained patients who received at least one dose of medication. This study is registered with ClinicalTrials.gov (NCT03338621) and is completed. Findings Between July 30, 2018, and March 2, 2020, 455 participants were enrolled and received at least one dose of study treatment. 324 (71%) participants were male and 131 (29%) participants were female. 303 participants with DS-TB were randomly assigned to 4 months of BPaMZ (n=150) or HRZE (n=153). In a modified intention-to-treat (mITT) analysis, by week 8, 122 (84%) of 145 and 70 (47%) of 148 participants were culture-negative on 4 months of BPaMZ and HRZE, respectively, with a hazard ratio for earlier negative status of 2·93 (95% CI 2·17–3·96; p&lt;0·0001). Median time to negative culture (TTN) was 6 weeks (IQR 4–8) on 4 months of BPaMZ and 11 weeks (6–12) on HRZE. 86% of participants with DR-TB receiving 6 months of BPaMZ (n=152) reached culture-negative status by week 8, with a median TTN of 5 weeks (IQR 3–7). At week 52, 120 (83%) of 144, 134 (93%) of 144, and 111 (83%) of 133 on 4 months of BPaMZ, HRZE, and 6 months of BPaMZ had favourable outcomes, respectively. Despite bacteriological efficacy, 4 months of BPaMZ did not meet the non-inferiority margin for the key secondary endpoint in the pre-defined mITT population due to higher withdrawal rates for adverse hepatic events. Non-inferiority was demonstrated in the per-protocol population confirming the effect of withdrawals with 4 months of BPaMZ. At least one liver-related treatment-emergent adverse effect (TEAE) occurred among 45 (30%) participants on 4 months of BPaMZ, 38 (25%) on HRZE, and 33 (22%) on 6 months of BPaMZ. Serious liver-related TEAEs were reported by 20 participants overall; 11 (7%) among those on 4 months of BPaMZ, one (1%) on HRZE, and eight (5%) on 6 months of BPaMZ. The most common reasons for discontinuation of trial treatment were hepatotoxicity (ten participants [2%]), increased hepatic enzymes (nine participants [2%]), QTcF prolongation (three participants [1%]), and hypersensitivity (two participants [&lt;1%]).Interpretation For DS-TB, BPaMZ successfully met the primary efficacy endpoint of sputum culture conversion. The regimen did not meet the key secondary efficacy endpoint due to adverse events resulting in treatment withdrawal. Our study demonstrated the potential for treatment-shortening efficacy of the BPaMZ regimen for DS-TB and DR-TB, providing clinical validation of a murine model widely used to identify such regimens. It also highlights that novel, treatment-shortening TB treatment regimens require an acceptable toxicity and tolerability profile with minimal monitoring in low-resource and high-burden settings. The increased risk of unpredictable severe hepatic adverse events with 4 months of BPaMZ would be a considerable obstacle to implementation of this regimen in settings with high burdens of TB with limited infrastructure for close surveillance of liver biochemistry. Future research should focus on improving the preclinical and early clinical detection and mitigation of safety issues together and further efforts to optimise shorter treatments