Evaluation of critical parameters in the hollow-fibre system for tuberculosis: A case study of moxifloxacin

Aims

The hollow‐fibre system for tuberculosis (HFS‐TB) is a preclinical model qualified by the European Medicines Agency to underpin the anti‐TB drug development process. It can mimic in vivo pharmacokinetic (PK)–pharmacodynamic (PD) attributes of selected antimicrobials, which could feed into in silico models to inform the design of clinical trials. However, historical data and published protocols are insufficient and omit key information to allow experiments to be reproducible. Therefore, in this work, we aim to optimize and standardize various HFS‐TB operational procedures.

Methods

First, we characterized bacterial growth dynamics with different types of hollow‐fibre cartridges, Mycobacterium tuberculosis strains and media. Second, we mimicked a moxifloxacin PK profile within hollow‐fibre cartridges, in order to check drug–fibres compatibility. Lastly, we mimicked the moxifloxacin total plasma PK profile in human after once daily oral dose of 400 mg to assess PK–PD after different sampling methods, strains, cartridge size and bacterial adaptation periods before drug infusion into the system.

Results

We found that final bacterial load inside the HFS‐TB was contingent on the studied variables. Besides, we demonstrated that drug–fibres compatibility tests are critical preliminary HFS‐TB assays, which need to be properly reported. Lastly, we uncovered that the sampling method and bacterial adaptation period before drug infusion significantly impact actual experimental conclusions.

Conclusion

Our data contribute to the necessary standardization of HFS‐TB experiments, draw attention to multiple aspects of this preclinical model that should be considered when reporting novel results and warn about critical parameters in the HFS‐TB currently overlooked.

Subcutaneous Marzeptacog Alfa (Activated) for On-Demand Treatment of Bleeding Events in Subjects With Hemophilia A or B With Inhibitors

Marzeptacog alfa (MarzAA) is under development for subcutaneous treatment of episodic bleeds in patients with hemophilia A/B and was studied in a phase III trial evaluating MarzAA compared with standard-of-care (SoC) for on-demand use. The work presented here aimed to evaluate MarzAA and SoC treatment of bleeding events on a standardized four-point efficacy scale (poor, fair, good, and excellent). Two continuous-time Markov modeling approaches were explored; a four-state model analyzing all four categories of bleeding improvement and a two-state model analyzing a binarized outcome (treatment failure (poor/fair), and treatment success (good/excellent)). Different covariates impacting improvement of bleeding episodes as well as a putative relationship between MarzAA exposure and improvement of bleeding episodes were evaluated. In the final four-state model, higher baseline diastolic blood pressure and higher age (> 33 years of age) were found to negatively and positively impact improvement of bleeding condition, respectively. Bleeding events occurring in knees and ankles were found to improve faster than bleeding events at other locations. The covariate effects had most impact on early treatment success (≤ 3 hours) whereas at later timepoints (> 12 hours), treatment success was similar for all patients indicating that these covariates might be clinically relevant for early treatment response. A statistically significant relationship between MarzAA zero-order absorption and improvement of bleedings (P < 0.05) were identified albeit with low precision. No statistically significant difference in treatment response between MarzAA and intravenous SoC was identified, indicating the potential of MarzAA for treatment of episodic bleeding events with a favorable subcutaneous administration route.

Derivation and Clinical Utility of Safety Targets for Linezolid-Related Adverse Events in Drug-Resistant Tuberculosis Treatment

Long-term usage of linezolid can result in adverse events such as peripheral neuropathy, anemia and thrombocytopenia. Therapeutic drug monitoring data from 75 drug-resistant tuberculosis patients treated with linezolid were analyzed using a time-to-event (TTE) approach for peripheral neuropathy and anemia and indirect response modelling for thrombocytopenia. Different time-varying linezolid pharmacokinetic exposure indices (AUC0-24h,ss, Cav, Cmax and Cmin) and patient characteristics were investigated as risk factors. A treatment duration shorter than 3 months was considered dropout and was modelled using a TTE approach. An exposure-response relationship between linezolid Cmin and both peripheral neuropathy and anemia was found. The exposure index which best described the development of thrombocytopenia was AUC0-24h. The final TTE dropout model indicated an association between linezolid Cmin and dropout. New safety targets for each adverse event were proposed which can be used for individualized linezolid dosing. According to the model predictions at 6 months of treatment, a Cmin of 0.11 mg/L and 1.4 mg/L should not be exceeded to keep the cumulative probability to develop anemia and peripheral neuropathy below 20%. The AUC0-24h should be below 111 h·mg/L or 270 h·mg/L to prevent thrombocytopenia and severe thrombocytopenia, respectively. A clinical utility assessment showed that the currently recommended dose of 600 mg once daily is safer compared to a 300 mg BID dosing strategy considering all four safety endpoints.

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.

Model-Informed Support of Dose Selection for Prophylactic Treatment with Dalcinonacog Alfa in Adult and Paediatric Hemophilia B Patients

INTRODUCTION

Dalcinonacog alfa (DalcA), a novel subcutaneously administered recombinant human factor IX (FIX) variant is being developed for adult and paediatric patients with hemophilia B (HB). DalcA has been shown to raise FIX to clinically meaningful levels in adults with HB. This work aimed to support dosing regimen selection in adults and perform first-in-paediatric dose extrapolations using a model-based pharmacokinetic (PK) approach.

METHODS

A population PK model was built using adult data from two clinical trials (NCT03186677, NCT03995784). With allometry in the model, clinical trial simulations were performed to study alternative dosing regimens in adults and children. Steady-state trough levels and the time-to-reach target were derived to inform dose selection.

RESULTS

Almost 90% of the adults were predicted to achieve desirable FIX levels, i.e. 10% FIX activity, following daily 100 IU/kg dosing, with 90% of the subjects reaching target within 1.6-7.1 days. No every-other-day regimen met the target. A dose of 125 IU/kg resulted in adequate FIX levels down to 6 years, whereas a 150 IU/kg dose was needed below 6 down to 2 years of age. For subjects down to 6 years that did not reach target with 125 IU/kg, a dose escalation to 150 IU/kg was appropriate. The children below 6 to 2 years were shown to need a dose escalation to 200 IU/kg if 150 IU/kg given daily was insufficient.

CONCLUSION

This study supported the adult dose selection for DalcA in the presence of sparse data and enabled first-in-paediatric dose selection to achieve FIX levels that reduce risk of spontaneous bleeds.

Clinical standards for the management of adverse effects during treatment for TB

BACKGROUND: Adverse effects (AE) to TB treatment cause morbidity, mortality and treatment interruption. The aim of these clinical standards is to encourage best practise for the diagnosis and management of AE.METHODS: 65/81 invited experts participated in a Delphi process using a 5-point Likert scale to score draft standards.RESULTS: We identified eight clinical standards. Each person commencing treatment for TB should: Standard 1, be counselled regarding AE before and during treatment; Standard 2, be evaluated for factors that might increase AE risk with regular review to actively identify and manage these; Standard 3, when AE occur, carefully assessed and possible allergic or hypersensitivity reactions considered; Standard 4, receive appropriate care to minimise morbidity and mortality associated with AE; Standard 5, be restarted on TB drugs after a serious AE according to a standardised protocol that includes active drug safety monitoring. In addition: Standard 6, healthcare workers should be trained on AE including how to counsel people undertaking TB treatment, as well as active AE monitoring and management; Standard 7, there should be active AE monitoring and reporting for all new TB drugs and regimens; and Standard 8, knowledge gaps identified from active AE monitoring should be systematically addressed through clinical research.CONCLUSION: These standards provide a person-centred, consensus-based approach to minimise the impact of AE during TB treatment.

Model-informed pediatric dose selection of marzeptacog alfa (activated): an exposure matching strategy

Marzeptacog alfa (activated) (MarzAA) is an activated recombinant human rFVII variant intended for subcutaneous (SC) administration to treat or prevent bleeding in individuals with hemophilia A (HA) or B (HB) with inhibitors, and other rare bleeding disorders. Subcutaneous administration provides benefits over IV injections. The objective of the study was to support the first-in-pediatric dose selection for SC MarzAA to treat episodic bleeding episodes in children up through 11 years in a registrational Phase-III trial. Assuming the same exposure-response relationship as in adults, an exposure matching strategy was employed using a population pharmacokinetics model. A sensitivity analysis evaluating impact of doubling in absorption rate and age-dependent allometric exponents on dose selection was performed. Subsequently, the probability of trial success, defined as number of successful trials for a given pediatric dose divided by number of simulated trials (n=1000) was studied. A successful trial was defined as outcome where four, three or two out of 24 pediatric subjects per trial were allowed to fall outside the adult exposures after SC administration of 60 μg/kg. A dose of 60 μg/kg in children with HA/HB was supported by the clinical trial simulations to match exposures in adults. The sensitivity analyses further supported selection of the 60 μg/kg dose level in all age groups. Moreover, the probability of trial success evaluations given a plausible design confirmed the potential of a 60 μg/kg dose level. Taken together, this work demonstrates the utility of model-informed drug development and could be helpful for other pediatric development programs for rare diseases.

Combined quantitative tuberculosis biomarker model for time-to-positivity and colony forming unit to support tuberculosis drug development

Biomarkers are quantifiable characteristics of biological processes. In Mycobacterium tuberculosis, common biomarkers used in clinical drug development are colony forming unit (CFU) and time-to-positivity (TTP) from sputum samples. This analysis aimed to develop a combined quantitative tuberculosis biomarker model for CFU and TTP biomarkers for assessing drug efficacy in early bactericidal activity studies. Daily CFU and TTP observations in 83 previously patients with uncomplicated pulmonary tuberculosis after 7 days of different rifampicin monotherapy treatments (10–40 mg/kg) from the HIGHRIF1 study were included in this analysis. The combined quantitative tuberculosis biomarker model employed the Multistate Tuberculosis Pharmacometric model linked to a rifampicin pharmacokinetic model in order to determine drug exposure-response relationships on three bacterial sub-states using both the CFU and TTP data simultaneously. CFU was predicted from the MTP model and TTP was predicted through a time-to-event approach from the TTP model, which was linked to the MTP model through the transfer of all bacterial sub-states in the MTP model to a one bacterial TTP model. The non-linear CFU-TTP relationship over time was well predicted by the final model. The combined quantitative tuberculosis biomarker model provides an efficient approach for assessing drug efficacy informed by both CFU and TTP data in early bactericidal activity studies and to describe the relationship between CFU and TTP over time.

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

A milestone in the development of novel anti-tuberculosis drugs is demonstrating early bactericidal activity (EBA) in a phase IIa clinical trial. The significant variability in measurements of bacterial load complicates the data analysis in these trials. We performed a systematic review and evaluation of methods for determination of EBA in pulmonary tuberculosis studies. Bacterial load quantification biomarkers, reporting intervals, calculation methods, statistical testing, and handling of negative culture result were extracted. We identified 79 studies in which EBA was determined. Colony-forming units on solid culture media and/or time-to-positivity in liquid media were the most often used biomarkers, reported in 72 (91%) and 34 (43%) studies, respectively. Twenty-two different reporting intervals have been presented and twelve different calculation methods for the EBA were identified. Statistical testing for a significantly EBA compared to 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. There is notable variation 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 in generalization of study results and facilitate comparison between drugs/regimens.

Implementing best practises on data generation and reporting of Mycobacterium tuberculosis in vitro assays within the ERA4TB consortium

Tuberculosis (TB) is the historical leading cause of death by a single infectious agent. The European Regimen Accelerator for Tuberculosis (ERA4TB) is a public-private partnership of 30+ institutions with the objective to progress new anti-TB regimens into the clinic. Thus, robust and replicable results across independent laboratories are essential for reliable interpretation of treatment efficacy. A standardization workgroup unified in vitro protocols and data reporting templates. Time-kill assays provide essential input data for pharmacometric model-informed translation of single agents and regimens activity from in vitro to in vivo and the clinic. Five conditions were assessed by time-kill assays in six independent laboratories using four bacterial plating methods. Baseline bacterial burden varied between laboratories but variability was limited in net drug effect, confirming 2.5 μL equally robust as 100 μL plating. This exercise establishes the foundations of collaborative data generation, reporting, and integration within the overarching Antimicrobial Resistance Accelerator program.

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-EBA_0-14 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.

Pharmacokinetics and pharmacodynamics of anti-tuberculosis drugs: An evaluation of in vitro, in vivo methodologies and human studies

There has been an increased interest in pharmacokinetics and pharmacodynamics (PKPD) of anti-tuberculosis drugs. A better understanding of the relationship between drug exposure, antimicrobial kill and acquired drug resistance is essential not only to optimize current treatment regimens but also to design appropriately dosed regimens with new anti-tuberculosis drugs. Although the interest in PKPD has resulted in an increased number of studies, the actual bench-to-bedside translation is somewhat limited. One of the reasons could be differences in methodologies and outcome assessments that makes it difficult to compare the studies. In this paper we summarize most relevant in vitro, in vivo, in silico and human PKPD studies performed to optimize the drug dose and regimens for treatment of tuberculosis. The in vitro assessment focuses on MIC determination, static time-kill kinetics, and dynamic hollow fibre infection models to investigate acquisition of resistance and killing of Mycobacterium tuberculosis populations in various metabolic states. The in vivo assessment focuses on the various animal models, routes of infection, PK at the site of infection, PD read-outs, biomarkers and differences in treatment outcome evaluation (relapse and death). For human PKPD we focus on early bactericidal activity studies and inclusion of PK and therapeutic drug monitoring in clinical trials. Modelling and simulation approaches that are used to evaluate and link the different data types will be discussed. We also describe the concept of different studies, study design, importance of uniform reporting including microbiological and clinical outcome assessments, and modelling approaches. We aim to encourage researchers to consider methods of assessing and reporting PKPD of anti-tuberculosis drugs when designing studies. This will improve appropriate comparison between studies and accelerate the progress in the field.

Phase III dose selection of marzeptacog alfa (activated) informed by population pharmacokinetic modeling: A novel hemostatic drug

Marzeptacog alfa (activated) (MarzAA) is an activated recombinant human FVII (rFVIIa) variant developed as subcutaneous (s.c.) administration for the treatment or prevention of bleeding episodes in patients with hemophilia A (HA) or hemophilia B (HB) with inhibitors and other rare bleeding disorders. Population pharmacokinetic (PK) modeling was applied for dose selection for a pivotal phase III clinical trial evaluating s.c. MarzAA for episodic treatment of spontaneous or traumatic bleeding episodes. The population PK model used MarzAA intravenous and s.c. data from previously completed clinical trials in patients with HA/HB with or without inhibitors. Based on the model, clinical trial simulations were performed to predict MarzAA exposure after different dosing regimens. The exposure target was identified using an exposure-matching strategy with a wild-type rFVIIa but adjusting for the difference in potency between the two compounds. Simulations demonstrated a sufficient absorption rate and prolonged exposure following a single 60 μg/kg dose leading to 51% and 70% of the population reaching levels above the target after 3 and 6 h, respectively. According to the phase III protocol, if a second dose was required after 3 h because of a lack of efficacy, 90% of the population was observed to be above target 6 h after the initial dose. The model-informed drug development approach integrated information from several trials and guided dose selection in the pivotal phase III clinical trial for episodic treatment of an acute bleeding event in individuals with HA or HB with inhibitors without the execution of a phase II trial for that indication.

Study protocol for locoregional precision treatment of hepatocellular carcinoma with transarterial chemoembolisation (TACTida), a clinical study: idarubicin dose selection, tissue response and survival

INTRODUCTION

Hepatocellular carcinoma (HCC) is a common cause of cancer-related death, often detected in the intermediate stage. The standard of care for intermediate-stage HCC is transarterial chemoembolisation (TACE), where idarubicin (IDA) is a promising drug. Despite the fact that TACE has been used for several decades, treatment success is unpredictable. This clinical trial has been designed believing that further improvement might be achieved by increasing the understanding of interactions between local pharmacology, tumour targeting, HCC pathophysiology, metabolomics and molecular mechanisms of drug resistance.

METHODS AND ANALYSIS

The study population of this single-centre clinical trial consists of adults with intermediate-stage HCC. Each tumour site will receive TACE with two different IDA doses, 10 and 15 mg, on separate occasions. Before and after each patient's first TACE blood samples, tissue and liquid biopsies, and positron emission tomography (PET)/MRI will be performed. Blood samples will be used for pharmacokinetics (PK) and liver function evaluation. Tissue biopsies will be used for histopathology analyses, and culturing of primary organoids of tumour and non-tumour tissue to measure cell viability, drug response, multiomics and gene expression. Multiomics analyses will also be performed on liquid biopsies. PET/MRI will be used to evaluate tumour viability and liver metabolism. The two doses of IDA will be compared regarding PK, antitumour effects and safety. Imaging, molecular biology and multiomics data will be used to identify HCC phenotypes and their relation to drug uptake and metabolism, treatment response and survival.

ETHICS AND DISSEMINATION

Participants give informed consent. Personal data are deidentified. A patient will be withdrawn from the study if considered medically necessary, or if it is the wish of the patient. The study has been approved by the Swedish Ethical Review Authority (Dnr. 2021-01928) and by the Medical Product Agency, Uppsala, Sweden.

TRIAL REGISTRATION NUMBER

EudraCT number: 2021-001257-31.

Finding the right hazard function for time‐to‐event modeling: A tutorial and Shiny application

Parametric time‐to‐event analysis is an important pharmacometric method to predict the probability of an event up until a certain time as a function of covariates and/or drug exposure. Modeling is performed at the level of the hazard function describing the instantaneous rate of an event occurring at that timepoint. We give an overview of the parametric time‐to‐event analysis starting with graphical exploration by Kaplan–Meier plotting for the event data including censoring and nonparametric hazard estimators such as the kernel‐based visual hazard comparison for the underlying hazard. The most common hazard functions including the exponential, Gompertz, Weibull, log‐normal, log‐logistic, and circadian functions are described in detail. A Shiny application was developed to graphically guide the modeler which of the most common hazard functions presents a similar shape compared to the data in order to guide which hazard functions to test in the parametric time‐to‐event analysis. For the chosen hazard function(s), the Shiny application can additionally be used to explore corresponding parameter values to inform on suitable initial estimates for parametric modeling as well as on possible covariate or treatment relationships to certain parameters. Moreover, it can be used for the dissemination of results as well as communication, training, and workshops on time‐to‐event analysis. By guiding the modeler on which functions and what parameter values to test and compare as well as to assist in dissemination, the Shiny application developed here greatly supports the modeler in complicated parametric time‐to‐event modeling.

Machine Learning and Pharmacometrics for Prediction of Pharmacokinetic Data: Differences, Similarities and Challenges Illustrated with Rifampicin

Pharmacometrics (PM) and machine learning (ML) are both valuable for drug development to characterize pharmacokinetics (PK) and pharmacodynamics (PD). Pharmacokinetic/pharmacodynamic (PKPD) analysis using PM provides mechanistic insight into biological processes but is time- and labor-intensive. In contrast, ML models are much quicker trained, but offer less mechanistic insights. The opportunity of using ML predictions of drug PK as input for a PKPD model could strongly accelerate analysis efforts. Here exemplified by rifampicin, a widely used antibiotic, we explore the ability of different ML algorithms to predict drug PK. Based on simulated data, we trained linear regressions (LASSO), Gradient Boosting Machines, XGBoost and Random Forest to predict the plasma concentration-time series and rifampicin area under the concentration-versus-time curve from 0–24 h (AUC_0–24h) after repeated dosing. XGBoost performed best for prediction of the entire PK series (R²: 0.84, root mean square error (RMSE): 6.9 mg/L, mean absolute error (MAE): 4.0 mg/L) for the scenario with the largest data size. For AUC_0–24h prediction, LASSO showed the highest performance (R²: 0.97, RMSE: 29.1 h·mg/L, MAE: 18.8 h·mg/L). Increasing the number of plasma concentrations per patient (0, 2 or 6 concentrations per occasion) improved model performance. For example, for AUC_0–24h prediction using LASSO, the R² was 0.41, 0.69 and 0.97 when using predictors only (no plasma concentrations), 2 or 6 plasma concentrations per occasion as input, respectively. Run times for the ML models ranged from 1.0 s to 8 min, while the run time for the PM model was more than 3 h. Furthermore, building a PM model is more time- and labor-intensive compared with ML. ML predictions of drug PK could thus be used as input into a PKPD model, enabling time-efficient analysis.

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) (EBA_CFU0-14) 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 EBA_CFU0-14 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).

Safety and pharmacokinetics-pharmacodynamics of a shorter tuberculosis treatment with high-dose pyrazinamide and rifampicin: a study protocol of a phase II clinical trial (HighShort-RP)

INTRODUCTION

Increased dosing of rifampicin and pyrazinamide seems a viable strategy to shorten treatment and prevent relapse of drug-susceptible tuberculosis (TB), but safety and efficacy remains to be confirmed. This clinical trial aims to explore safety and pharmacokinetics-pharmacodynamics of a high-dose pyrazinamide-rifampicin regimen.

METHODS AND ANALYSIS

Adult patients with pulmonary TB admitted to six hospitals in Sweden and subjected to receive first-line treatment are included. Patients are randomised (1:3) to either 6-month standardised TB treatment or a 4-month regimen based on high-dose pyrazinamide (40 mg/kg) and rifampicin (35 mg/kg) along with standard doses of isoniazid and ethambutol. Plasma samples for measurement of drug exposure determined by liquid chromatography tandem-mass spectrometry are obtained at 0, 1, 2, 4, 6, 8, 12 and 24 hours, at day 1 and 14. Maximal drug concentration (C_max) and area under the concentration-time curve (AUC_0-24h) are estimated by non-compartmental analysis. Conditions for early model-informed precision dosing of high-dose pyrazinamide-rifampicin are pharmacometrically explored. Adverse drug effects are monitored throughout the study and graded according to Common Terminology Criteria for Adverse Events V.5.0. Early bactericidal activity is assessed by time to positivity in BACTEC MGIT 960 of induced sputum collected at day 0, 5, 8, 15 and week 8. Minimum inhibitory concentrations of first-line drugs are determined using broth microdilution. Disease severity is assessed with X-ray grading and a validated clinical scoring tool (TBscore II). Clinical outcome is registered according to WHO definitions (2020) in addition to occurrence of relapse after end of treatment. Primary endpoint is pyrazinamide AUC_0-24h and main secondary endpoint is safety.

ETHICS AND DISSEMINATION

The study is approved by the Swedish Ethical Review Authority and the Swedish Medical Products Agency. Informed written consent is collected before study enrolment. The study results will be submitted to a peer-reviewed journal.

TRIAL REGISTRATION NUMBER

NCT04694586.

Standard therapy of Mycobacterium avium complex pulmonary disease shows limited efficacy in an open source hollow fibre system that simulates human plasma and epithelial lining fluid pharmacokinetics

OBJECTIVES

Mycobacterium avium complex (MAC) bacteria can cause chronic pulmonary disease (PD). Current treatment regimens of azithromycin, ethambutol and rifampicin have culture conversion rates of around 65%. Dynamic, preclinical models to assess the efficacy of treatment regimens are important to guide clinical trial development. The hollow fibre system (HFS) has been applied but reports lack experimental details.

METHODS

We simulated the human pharmacokinetics of azithromycin, ethambutol and rifampicin both in plasma and epithelial lining fluid (ELF) in a HFS, exposing THP-1 cells infected with M. avium to the triple-drug regimen for 3 weeks. We accounted for drug-drug interactions and protein-binding and provide all laboratory protocols. We differentiated the effects on the intracellular and extracellular mycobacterial population.

RESULTS

The antibiotic concentrations in the HFS accurately reflected the time to peak concentration (T_max), the peak concentration (C_max) and half-life of azithromycin, rifampicin and ethambutol in plasma and ELF reported in literature. We find that plasma drug concentrations fail to hold the MAC bacterial load static (ΔLog10 CFU/mL_{Control:Regimen} = 0.66 ± 0.76 and 0.45 ± 0.28 at 3 and 21 days); ELF concentrations do hold the bacterial load static for 3 days and inhibit bacterial growth for the duration of the experiment (ΔLog10 CFU/mL_{Control:Regimen} = 1.1 ± 0.1 and 1.64 ± 0.59 at 3 and 21 days).

DISCUSSION

In our model, the current therapy against MAC is ineffective, even when accounting for antibiotic accumulation at the site of infection and intracellularly. New treatment regimens need to be developed and be compared with currently recommended regimens in dynamic models prior to clinical evaluation. With the publication of all protocols we aim to open this technology to new users.

Rifampicin Can Be Given as Flat-Dosing Instead of Weight-Band Dosing

BACKGROUND

The weight-band dosing in tuberculosis treatment regimen has been implemented in clinical practice for decades. Patients will receive different number of fixed dose combination tablets according to their weight-band. However, some analysis has shown that weight was not the best covariate to explain variability of rifampicin exposure. Furthermore, the rationale for using weight-band dosing instead of flat-dosing becomes questionable. Therefore, this study aimed to compare the average and the variability of rifampicin exposure after weight-band dosing and flat-dosing.

METHODS

Rifampicin exposure were simulated using previously published population pharmacokinetics model at dose 10-40 mg/kg for weight-band dosing and dose 600-2400 mg for flat-dosing. The median area under the curve (AUC0-24 h) after day 7 and 14 were compared as well as the variability of each dose group between weight-band and flat-dosing.

RESULTS

The difference of median AUC0-24 h of all dose groups between flat-dosing and weight-band dosing were considered low (< 20%) except for the lowest dose. At the dose of 10 mg/kg (600 mg for flat-dosing), flat-dosing resulted in higher median AUC0-24h compared to the weight-band dosing. A marginal decrease in between-patient variability was predicted for weight-band dosing compared to flat-dosing.

CONCLUSIONS

Weight-band dosing yields a small and non-clinically relevant decrease in variability of AUC0-24h.

Predictive modeling to study the treatment-shortening potential of novel tuberculosis drug regimens, towards bundling of preclinical data

BACKGROUND

Given the persistently high global burden of tuberculosis (TB), effective and shorter treatment options are needed. Here, we explore the relationship between relapse and treatment length as well as inter-regimen differences for two novel anti-TB drug regimens using a mouse model of TB infection and mathematical modeling.

METHODS

Mycobacterium tuberculosis-infected mice were treated for up to 13 weeks with bedaquiline and pretomanid combined with moxifloxacin and pyrazinamide (BPaMZ) or linezolid (BPaL). Cure rates were evaluated 12 weeks after treatment completion. The standard regimen of isoniazid, rifampicin, pyrazinamide, and ethambutol (HRZE) was evaluated as a comparator.

RESULTS

Six weeks of BPaMZ was sufficient to cure all mice. In contrast, 13 weeks of BPaL and 24 weeks of HRZE did not achieve 100% cure rates. Based on mathematical model predictions, 95% probability of cure was predicted for BPaMZ, BPaL and HRZE to occur at 1.6, 4.3, and 7.9 months, respectively.

CONCLUSION

This study provides additional evidence for the treatment-shortening capacity of BPaMZ over BPaL and HRZE. To optimally utilize preclinical data for predicting clinical outcomes, and to overcome the limitations that hamper such extrapolation, we advocate bundling of available published preclinical data into mathematical models.

Superior efficacy of a bedaquiline, delamanid and linezolid combination regimen in a mouse-TB model

BACKGROUND

The treatment success rate of drug-resistant tuberculosis (DR-TB) is alarmingly low. Therefore, more effective and less complex regimens are urgently required.

METHODS

We compared the efficacy of an all oral DR-TB drug regimen consisting of bedaquiline (25 mg/kg), delamanid (2.5 mg/kg) and linezolid (100 mg/kg) (BDL) on the mycobacterial load in the lungs and spleen of TB infected mice during a treatment period of 24 weeks. This treatment was compared to the standard regimen of isoniazid, rifampicin, pyrazinamide and ethambutol (HRZE). Relapse was assessed 12 weeks post-treatment. Two logistic regression models were developed to compare the efficacy of both regimens.

RESULTS

Culture negativity in the lungs was achieved at 8 and 20 weeks of treatment with BDL and HRZE, respectively. After 14 weeks of treatment only one mouse relapsed in the BDL group, while in the HRZE group relapse was still observed at 24 weeks of treatment. Predictions from the final mathematical models showed that a 95% cure rate was reached after 20.5 and 28.5 weeks of treatment with BDL and HRZE, respectively.

CONCLUSION

The BDL regimen was observed to be more effective than HRZE and could be a valuable option for the treatment of DR-TB.

Anti-tuberculosis effect of isoniazid scales accurately from zebrafish to humans

Background and Purpose

There is a clear need for innovation in anti‐tuberculosis drug development. The zebrafish larva is an attractive disease model in tuberculosis research. To translate pharmacological findings to higher vertebrates, including humans, the internal exposure of drugs needs to be quantified and linked to observed response.

Experimental Approach

In zebrafish studies, drugs are usually dissolved in the external water, posing a challenge to quantify internal exposure. We developed experimental methods to quantify internal exposure, including nanoscale blood sampling, and to quantify the bacterial burden, using automated fluorescence imaging analysis, with isoniazid as the test compound. We used pharmacokinetic–pharmacodynamic modelling to quantify the exposure–response relationship responsible for the antibiotic response. To translate isoniazid response to humans, quantitative exposure–response relationships in zebrafish were linked to simulated concentration–time profiles in humans, and two quantitative translational factors on sensitivity to isoniazid and stage of infection were included.

Key Results

Blood concentration was only 20% of the external drug concentration. The bacterial burden increased exponentially, and an isoniazid dose corresponding to 15 mg·L⁻¹ internal concentration (minimum inhibitory concentration) leads to bacteriostasis of the mycobacterial infection in the zebrafish. The concentration–effect relationship was quantified, and based on that relationship and the translational factors, the isoniazid response was translated to humans, which correlated well with observed data.

Conclusions and Implications

This proof of concept study confirmed the potential of zebrafish larvae as tuberculosis disease models in translational pharmacology and contributes to innovative anti‐tuberculosis drug development, which is very clearly needed.

Individualized Dosing With High Inter-Occasion Variability Is Correctly Handled With Model-Informed Precision Dosing-Using Rifampicin as an Example

Rifampicin exhibits complexities in its pharmacokinetics (PK), including high inter-occasion variability (IOV), which is challenging for dose individualization. Model-informed precision dosing (MIPD) can be used to optimize individual doses. In this simulation-based study we investigated the magnitude of IOV in rifampicin PK on an exposure level, the impact of not acknowledging IOV when performing MIPD, and the number of sampling occasions needed to forecast the dose. Subjects with drug-susceptible tuberculosis (TB) were simulated from a previously developed population PK model. To explore the magnitude of IOV, the area under the plasma concentration-time curve from time zero up to 24 h (AUC_0–24h) after 35 mg/kg in the typical individual was simulated for 1,000 sampling occasions at steady-state. The impact of ignoring IOV for dose predictions was investigated by comparing the prediction error of a MIPD approach including IOV to an approach ignoring IOV. Furthermore, the number of sampling occasions needed to predict individual doses using a MIPD approach was assessed. The AUC_0–24h in the typical individual varied substantially between simulated sampling occasions [95% prediction interval (PI): 122.2 to 331.2 h mg/L], equivalent to an IOV in AUC_0–24h of 25.8%, compared to an inter-individual variability of 25.4%. The median of the individual prediction errors using a MIPD approach incorporating IOV was 0% (75% PI: −14.6% to 0.0%), and the PI for the individual prediction errors was narrower with than without IOV (median: 0%, 75% PI: −14.6% to 20.0%). The most common target dose in this population was forecasted correctly in 95% of the subjects when IOV was included in MIPD. In subjects where doses were not predicted optimally, a lower dose was predicted compared to the target, which is favorable from a safety perspective. Moreover, the imprecision (relative root mean square error) and bias in predicted doses using MIPD with IOV decreased statistically significant when a second sampling occasion was added (difference in imprecision: −9.1%, bias: −7.7%), but only marginally including a third (difference in imprecision: −0.1%, bias: −0.1%). In conclusion, a large variability in exposure of rifampicin between occasions was shown. In order to forecast the individual dose correctly, IOV must be acknowledged which can be achieved using a MIPD approach with PK information from at least two sampling occasions.

Quantification of Natural Growth of Two Strains of Mycobacterium Marinum for Translational Antituberculosis Drug Development

The zebrafish infected with Mycobacterium marinum (M. marinum) is an attractive tuberculosis disease model, showing similar pathogenesis to Mycobacterium tuberculosis (M. tuberculosis) infections in humans. To translate pharmacological findings from this disease model to higher vertebrates, a quantitative understanding of the natural growth of M. marinum in comparison to the natural growth of M. tuberculosis is essential. Here, the natural growth of two strains of M. marinum, E11 and M^USA, is studied over an extended period using an established model‐based approach, the multistate tuberculosis pharmacometric (MTP) model, for comparison to that of M. tuberculosis. Poikilotherm‐derived strain E11 and human‐derived strain M^USA were grown undisturbed up to 221 days and viability of cultures (colony forming unit (CFU)/mL) was determined by plating at different time points. Nonlinear mixed effects modeling using the MTP model quantified the bacterial growth, the transfer among fast, slow, and non‐multiplying states, and the inoculi. Both strains showed initial logistic growth, reaching a maximum after 20–25 days for E11 and M^USA, respectively, followed by a decrease to a new plateau. Natural growth of both E11 and M^USA was best described with Gompertz growth functions. For E11, the inoculum was best described in the slow‐multiplying state, for M^USA in the fast‐multiplying state. Natural growth of E11 was most similar to that of M. tuberculosis, whereas M^USA showed more aggressive growth behavior. Characterization of natural growth of M. marinum and quantitative comparison with M. tuberculosis brings the zebrafish tuberculosis disease model closer to the quantitative translational pipeline of antituberculosis drug development.

Translational Model-Informed Approach for Selection of Tuberculosis Drug Combination Regimens in Early Clinical Development

The development of optimal treatment regimens in tuberculosis (TB) remains challenging due to the need of combination therapy and possibility of pharmacodynamic (PD) interactions. Preclinical information about PD interactions needs to be used more optimally when designing early bactericidal activity (EBA) studies. In this work, we developed a translational approach which can allow for forward translation to predict efficacy of drug combination in EBA studies using the Multistate Tuberculosis Pharmacometric (MTP) and the General Pharmacodynamic Interaction (GPDI) models informed by in vitro static time-kill data. These models were linked with translational factors to account for differences between the in vitro system and humans. Our translational MTP-GPDI model approach was able to predict the EBA_{0-2 days} , EBA_{0-5 days} , and EBA_{0-14 days} from different EBA studies of rifampicin and isoniazid in monotherapy and combination. Our translational model approach can contribute to an optimal dose selection of drug combinations in early TB clinical trials.

Rotational thromboelastometry can predict the probability of bleeding events in a translational rat model of haemophilia A following gene-based FVIIa prophylaxis

INTRODUCTION

Monitoring of clinical effectiveness of bypassing agents in haemophilia patients is hampered by the lack of validated laboratory assays. Thromboelastography (TEG) and rotational thromboelastometry (ROTEM) have been evaluated for predicting clinical effectiveness of bypassing agents, however, with limited success.

AIM

Application of a longitudinal model-based approach may allow for a quantitative characterization of the link between ROTEM parameters and the probability of bleeding events.

METHODS

We analyse longitudinal data from haemophilia A rats receiving gene-based FVIIa prophylaxis in terms of total circulatory levels of FVII/FVIIa, clotting time (CT) measured using ROTEM and the probability of bleeding events.

RESULTS

Using population pharmacokinetic-pharmacodynamic (PKPD) modelling, a PK-CT-repeated time-to-event (RTTE) model was developed composed of three submodels (a) a FVII/FVIIa PK model, (b) a PK-CT model describing the relationship between predicted FVIIa expression and CT and (c) a RTTE model describing the probability of bleeding events as a function of CT. The developed PK-CT-RTTE model accurately described the vector dose-dependent plasma concentration-time profile of total FVII/FVIIa and the exposure-response relationship between AAV-derived FVIIa expression and CT. Importantly, the developed model accurately described the occurrence of bleeding events over time in a quantitative manner, revealing a linear relationship between predicted change from baseline CT and the probability of bleeding events.

CONCLUSION

Using PK-CT-RTTE modelling, we demonstrated that ROTEM parameters can accurately predict the probability of bleeding events in a translational animal model of haemophilia A.

The Potential for Treatment Shortening With Higher Rifampicin Doses: Relating Drug Exposure to Treatment Response in Patients With Pulmonary Tuberculosis

Background

Tuberculosis remains a huge public health problem and the prolonged treatment duration obstructs effective tuberculosis control. Higher rifampicin doses have been associated with better bactericidal activity, but optimal dosing is uncertain. This analysis aimed to characterize the relationship between rifampicin plasma exposure and treatment response over 6 months in a recent study investigating the potential for treatment shortening with high-dose rifampicin.

Methods

Data were analyzed from 336 patients with pulmonary tuberculosis (97 with pharmacokinetic data) treated with rifampicin doses of 10, 20, or 35 mg/kg. The response measure was time to stable sputum culture conversion (TSCC). We derived individual exposure metrics with a previously developed population pharmacokinetic model of rifampicin. TSCC was modeled using a parametric time-to-event approach, and a sequential exposure-response analysis was performed.

Results

Higher rifampicin exposures increased the probability of early culture conversion. No maximal limit of the effect was detected within the observed range. The expected proportion of patients with stable culture conversion on liquid medium at week 8 was predicted to increase from 39% (95% confidence interval, 37%-41%) to 55% (49%-61%), with the rifampicin area under the curve increasing from 20 to 175 mg/L·h (representative for 10 and 35 mg/kg, respectively). Other predictors of TSCC were baseline bacterial load, proportion of culture results unavailable, and substitution of ethambutol for either moxifloxacin or SQ109.

Conclusions

Increasing rifampicin exposure shortened TSCC, and the effect did not plateau, indicating that doses >35 mg/kg could be yet more effective. Optimizing rifampicin dosage while preventing toxicity is a clinical priority.

Distribution of plasma concentrations of first-line anti-TB drugs and individual MICs: a prospective cohort study in a low endemic setting

Background

Therapeutic drug monitoring (TDM) could improve current TB treatment, but few studies have reported pharmacokinetic data together with MICs.

Objectives

To investigate plasma concentrations of rifampicin, isoniazid, pyrazinamide and ethambutol along with MICs.

Methods

Drug concentrations of rifampicin, isoniazid, pyrazinamide and ethambutol were analysed pre-dose and 2, 4 and 6 h after drug intake at week 2 in 31 TB patients and MICs in BACTEC 960 MGIT were determined at baseline. The highest plasma concentrations at 2, 4 and 6 h post-dose (Chigh) were determined, as well as estimates of Chigh/MIC and area under the concentration-time curve (AUC0-6)/MIC including the corresponding ratios based on calculated free-drug concentrations. This trial was registered at www.clinicaltrials.gov (NCT02042261).

Results

After 2 weeks of treatment, the median Chigh values for rifampicin, isoniazid, pyrazinamide and ethambutol were 10.0, 5.3, 41.1 and 3.3 mg/L respectively. Lower than recommended drug concentrations were detected in 42% of the patients for rifampicin (<8 mg/L), 19% for isoniazid (<3 mg/L), 27% for pyrazinamide (<35 mg/L) and 16% for ethambutol (<2 mg/L). The median Chigh/MIC values for rifampicin, isoniazid, pyrazinamide and ethambutol were 164, 128, 1.3 and 2.5, respectively, whereas the AUC0-6/MIC was 636 (range 156-2759) for rifampicin and 351 (range 72-895) for isoniazid.

Conclusions

We report low levels of first-line TB drugs in 16%-42% of patients, in particular for rifampicin. There was a wide distribution of the ratios between drug exposures and MICs. The future use of MIC determinations in TDM is dependent on the development of a reference method and clinically validated pharmacokinetic/pharmacodynamic targets.

Individualised dosing algorithm and personalised treatment of high-dose rifampicin for tuberculosis

AIMS

To propose new exposure targets for Bayesian dose optimisation suited for high-dose rifampicin and to apply them using measured plasma concentrations coupled with a Bayesian forecasting algorithm allowing predictions of future doses, considering rifampicin's auto-induction, saturable pharmacokinetics and high interoccasion variability.

METHODS

Rifampicin exposure targets for Bayesian dose optimisation were defined based on literature data on safety and anti-mycobacterial activity in relation to rifampicin's pharmacokinetics i.e. highest plasma concentration up to 24 hours and area under the plasma concentration-time curve up to 24 hours (AUC_0-24h ). Targets were suggested with and without considering minimum inhibitory concentration (MIC) information. Individual optimal doses were predicted for patients treated with rifampicin (10 mg/kg) using the targets with Bayesian forecasting together with sparse measurements of rifampicin plasma concentrations and baseline rifampicin MIC.

RESULTS

The suggested exposure target for Bayesian dose optimisation was a steady state AUC_0-24h of 181-214 h × mg/L. The observed MICs ranged from 0.016-0.125 mg/L (mode: 0.064 mg/L). The predicted optimal dose in patients using the suggested target ranged from 1200-3000 mg (20-50 mg/kg) with a mode of 1800 mg (30 mg/kg, n = 24). The predicted optimal doses when taking MIC into account were highly dependent on the known technical variability of measured individual MIC and the dose was substantially lower compared to when using the AUC_0-24h -only target.

CONCLUSIONS

A new up-to-date exposure target for Bayesian dose optimisation suited for high-dose rifampicin was derived. Using measured plasma concentrations coupled with Bayesian forecasting allowed prediction of the future dose whilst accounting for the auto-induction, saturable pharmacokinetics and high between-occasion variability of rifampicin.

A model-informed preclinical approach for prediction of clinical pharmacodynamic interactions of anti-TB drug combinations

Background

Identification of pharmacodynamic interactions is not reasonable to carry out in a clinical setting for many reasons. The aim of this work was to develop a model-informed preclinical approach for prediction of clinical pharmacodynamic drug interactions in order to inform early anti-TB drug development.

Methods

In vitro time–kill experiments were performed with Mycobacterium tuberculosis using rifampicin, isoniazid or ethambutol alone as well as in different combinations at clinically relevant concentrations. The multistate TB pharmacometric (MTP) model was used to characterize the natural growth and exposure–response relationships of each drug after mono exposure. Pharmacodynamic interactions during combination exposure were characterized by linking the MTP model to the general pharmacodynamic interaction (GPDI) model with successful separation of the potential effect on each drug’s potency (EC₅₀) by the combining drug(s).

Results

All combinations showed pharmacodynamic interactions at cfu level, where all combinations, except isoniazid plus ethambutol, showed more effect (synergy) than any of the drugs alone. Using preclinical information, the MTP-GPDI modelling approach was shown to correctly predict clinically observed pharmacodynamic interactions, as deviations from expected additivity.

Conclusions

With the ability to predict clinical pharmacodynamic interactions, using preclinical information, the MTP-GPDI model approach outlined in this study constitutes groundwork for model-informed input to the development of new and enhancement of existing anti-TB combination regimens.

Plasma concentrations of second-line antituberculosis drugs in relation to minimum inhibitory concentrations in multidrug-resistant tuberculosis patients in China: a study protocol of a prospective observational cohort study

INTRODUCTION

Individualised treatment through therapeutic drug monitoring (TDM) may improve tuberculosis (TB) treatment outcomes but is not routinely implemented. Prospective clinical studies of drug exposure and minimum inhibitory concentrations (MICs) in multidrug-resistant TB (MDR-TB) are scarce. This translational study aims to characterise the area under the concentration-time curve of individual MDR-TB drugs, divided by the MIC for Mycobacterium tuberculosis isolates, to explore associations with markers of treatment progress and to develop useful strategies for clinical implementation of TDM in MDR-TB.

METHODS AND ANALYSIS

Adult patients with pulmonary MDR-TB treated in Xiamen, China, are included. Plasma samples for measure of drug exposure are obtained at 0, 1, 2, 4, 6, 8 and 10 hours after drug intake at week 2 and at 0, 4 and 6 hours during weeks 4 and 8. Sputum samples for evaluating time to culture positivity and MIC determination are collected at days 0, 2 and 7 and at weeks 2, 4, 8 and 12 after treatment initiation. Disease severity are assessed with a clinical scoring tool (TBscore II) and quality of life evaluated using EQ-5D-5L. Drug concentrations of pyrazinamide, ethambutol, levofloxacin, moxifloxacin, cycloserine, prothionamide and para-aminosalicylate are measured by liquid chromatography tandem-mass spectrometry and the levels of amikacin measured by immunoassay. Dried blood spot on filter paper, to facilitate blood sampling for analysis of drug concentrations, is also evaluated. The MICs of the drugs listed above are determined using custom-made broth microdilution plates and MYCOTB plates with Middlebrook 7H9 media. MIC determination of pyrazinamide is performed in BACTEC MGIT 960.

ETHICS AND DISSEMINATION

This study has been approved by the ethical review boards of Karolinska Institutet, Sweden and Fudan University, China. Informed written consent is given by participants. The study results will be submitted to a peer-reviewed journal.

TRIAL REGISTRATION NUMBER

NCT02816931; Pre-results.

Comparisons of Analysis Methods for Assessment of Pharmacodynamic Interactions Including Design Recommendations

Quantitative evaluation of potential pharmacodynamic (PD) interactions is important in tuberculosis drug development in order to optimize Phase 2b drug selection and ultimately to define clinical combination regimens. In this work, we used simulations to (1) evaluate different analysis methods for detecting PD interactions between two hypothetical anti-tubercular drugs in in vitro time-kill experiments, and (2) provide design recommendations for evaluation of PD interactions. The model used for all simulations was the Multistate Tuberculosis Pharmacometric (MTP) model linked to the General Pharmacodynamic Interaction (GPDI) model. Simulated data were re-estimated using the MTP-GPDI model implemented in Bliss Independence or Loewe Additivity, or using a conventional model such as an Empirical Bliss Independence-based model or the Greco model based on Loewe Additivity. The GPDI model correctly characterized different PD interactions (antagonism, synergism, or asymmetric interaction), regardless of the underlying additivity criterion. The commonly used conventional models were not able to characterize asymmetric PD interactions, i.e., concentration-dependent synergism and antagonism. An optimized experimental design was developed that correctly identified interactions in ≥ 94% of the evaluated scenarios using the MTP-GPDI model approach. The MTP-GPDI model approach was proved to provide advantages to other conventional models for assessing PD interactions of anti-tubercular drugs and provides key information for selection of drug combinations for Phase 2b evaluation.

Improving treatment outcome assessment in a mouse tuberculosis model

Preclinical treatment outcome evaluation of tuberculosis (TB) occurs primarily in mice. Current designs compare relapse rates of different regimens at selected time points, but lack information about the correlation between treatment length and treatment outcome, which is required to efficiently estimate a regimens’ treatment-shortening potential. Therefore we developed a new approach. BALB/c mice were infected with a Mycobacterium tuberculosis Beijing genotype strain and were treated with rifapentine-pyrazinamide-isoniazid-ethambutol (R_pZHE), rifampicin-pyrazinamide-moxifloxacin-ethambutol (RZME) or rifampicin-pyrazinamide-moxifloxacin-isoniazid (RZMH). Treatment outcome was assessed in n = 3 mice after 9 different treatment lengths between 2–6 months. Next, we created a mathematical model that best fitted the observational data and used this for inter-regimen comparison. The observed data were best described by a sigmoidal E_max model in favor over linear or conventional E_max models. Estimating regimen-specific parameters showed significantly higher curative potentials for RZME and R_pZHE compared to RZMH. In conclusion, we provide a new design for treatment outcome evaluation in a mouse TB model, which (i) provides accurate tools for assessment of the relationship between treatment length and predicted cure, (ii) allows for efficient comparison between regimens and (iii) adheres to the reduction and refinement principles of laboratory animal use.

Improved power for TB Phase IIa trials using a model-based pharmacokinetic-pharmacodynamic approach compared with commonly used analysis methods

Background: The demand for new anti-TB drugs is high, but development programmes are long and costly. Consequently there is a need for new strategies capable of accelerating this process.

Objectives: To explore the power to find statistically significant drug effects using a model-based pharmacokinetic–pharmacodynamic approach in comparison with the methods commonly used for analysing TB Phase IIa trials.

Methods: Phase IIa studies of four hypothetical anti-TB drugs (labelled A, B, C and D), each with a different mechanism of action, were simulated using the multistate TB pharmacometric (MTP) model. cfu data were simulated over 14 days for patients taking once-daily monotherapy at four different doses per drug and a reference (10 mg/kg rifampicin). The simulated data were analysed using t-test, ANOVA, mono- and bi-exponential models and a pharmacokinetic–pharmacodynamic model approach (MTP model) to establish their respective power to find a drug effect at the 5% significance level.

Results: For the pharmacokinetic–pharmacodynamic model approach, t-test, ANOVA, mono-exponential model and bi-exponential model, the sample sizes needed to achieve 90% power were: 10, 30, 75, 20 and 30 (drug A); 30, 75, 245, 75 and 105 (drug B); 70, >1250, 315, >1250 and >1250 (drug C); and 30, 110, 710, 170 and 185 (drug D), respectively.

Conclusions: A model-based design and analysis using a pharmacokinetic–pharmacodynamic approach can reduce the number of patients required to determine a drug effect at least 2-fold compared with current methodologies. This could significantly accelerate early-phase TB drug development.

A general pharmacodynamic interaction model identifies perpetrators and victims in drug interactions

Assessment of pharmacodynamic (PD) drug interactions is a cornerstone of the development of combination drug therapies. To guide this venture, we derive a general pharmacodynamic interaction (GPDI) model for ≥2 interacting drugs that is compatible with common additivity criteria. We propose a PD interaction to be quantifiable as multidirectional shifts in drug efficacy or potency and explicate the drugs’ role as victim, perpetrator or even both at the same time. We evaluate the GPDI model against conventional approaches in a data set of 200 combination experiments in Saccharomyces cerevisiae: 22% interact additively, a minority of the interactions (11%) are bidirectional antagonistic or synergistic, whereas the majority (67%) are monodirectional, i.e., asymmetric with distinct perpetrators and victims, which is not classifiable by conventional methods. The GPDI model excellently reflects the observed interaction data, and hence represents an attractive approach for quantitative assessment of novel combination therapies along the drug development process.

Assessment of pharmacodynamic interactions is at the heart of combination therapy development. Here the authors introduce a general drug interaction scoring model that enables quantification of synergistic and antagonistic interactions and determination of the directionality of the interactions.

Assessing Pharmacodynamic Interactions in Mice Using the Multistate Tuberculosis Pharmacometric and General Pharmacodynamic Interaction Models

The aim of this study was to investigate pharmacodynamic (PD) interactions in mice infected with Mycobacterium tuberculosis using population pharmacokinetics (PKs), the Multistate Tuberculosis Pharmacometric (MTP) model, and the General Pharmacodynamic Interaction (GPDI) model. Rifampicin, isoniazid, ethambutol, or pyrazinamide were administered in monotherapy for 4 weeks. Rifampicin and isoniazid showed effects in monotherapy, whereas the animals became moribund after 7 days with ethambutol or pyrazinamide alone. No PD interactions were observed against fast‐multiplying bacteria. Interactions between rifampicin and isoniazid on killing slow and non‐multiplying bacteria were identified, which led to an increase of 0.86 log₁₀ colony‐forming unit (CFU)/lungs at 28 days after treatment compared to expected additivity (i.e., antagonism). An interaction between rifampicin and ethambutol on killing non‐multiplying bacteria was quantified, which led to a decrease of 2.84 log₁₀ CFU/lungs at 28 days after treatment (i.e., synergism). These results show the value of pharmacometrics to quantitatively assess PD interactions in preclinical tuberculosis drug development.

A Population Pharmacokinetic Model Incorporating Saturable Pharmacokinetics and Autoinduction for High Rifampicin Doses

Accumulating evidence suggests that increasing doses of rifampicin may shorten tuberculosis treatment. The PanACEA HIGHRIF1 trial assessed safety, pharmacokinetics, and antimycobacterial activity of rifampicin at doses up to 40 mg/kg. Eighty-three pulmonary tuberculosis patients received 10, 20, 25, 30, 35, or 40 mg/kg rifampicin daily over 2 weeks, supplemented with standard doses of isoniazid, pyrazinamide, and ethambutol in the second week. This study aimed at characterizing rifampicin pharmacokinetics observed in HIGHRIF1 using nonlinear mixed effects modeling. The final population pharmacokinetic model included an enzyme turnover model accounting for time-dependent elimination due to autoinduction, concentration-dependent clearance, and dose-dependent bioavailability. The relationship between clearance and concentration was characterized by a Michaelis-Menten relationship. The relationship between bioavailability and dose was described using an E_max relationship. The model will be key in determining exposure-response relationships for rifampicin and should be considered when designing future trials and when treating future patients with high-dose rifampicin.

Residual Spinal Cord Compression Following Hemilaminectomy and Mini-Hemilaminectomy in Dogs: A Prospective Randomized Study

The aim of this study was to compare the reduction of spinal cord compression after surgical treatment of dogs with acute thoracolumbar intervertebral disc (IVD) extrusion achieved using hemilaminectomy versus mini-hemilaminectomy techniques. This was a prospective randomized study with client-owned dogs presented with acute IVD extrusion that were allocated to surgical treatment using hemilaminectomy (n = 15) or mini-hemilaminectomy (n = 15) techniques. Plain and intravenous-contrast computed tomography was performed pre- and postoperatively. The preoperative minimal cross-sectional dimension of the spinal cord (MDSC_pre) and the postoperative minimal cross-sectional dimension of the spinal cord (MDSC_post) were measured at the level of greatest compression. The minimal diameter of the uncompressed spinal cord was measured in a similar way both pre- (MDUSC_pre) and postoperatively (MDUSC_post). Dogs in the mini-hemilaminectomy group had significantly greater reduction of compression (RC) (p < 0.01) after surgery compared to dogs in the hemilaminectomy group. The mean RC in the hemilaminectomy group was 34.6% and in the mini-hemilaminectomy group 62.6%. Our results showed a significantly greater reduction of spinal cord compression for mini-hemilaminectomy compared to hemilaminectomy. Additionally, mini-hemilaminectomy could be a preferred method due to its minimal invasiveness and easier access to lateral fenestration.

Population pharmacokinetics, optimised design and sample size determination for rifampicin, isoniazid, ethambutol and pyrazinamide in the mouse

The current first-line therapy for drug-susceptible tuberculosis consists of rifampicin (RIF), isoniazid (INH), pyrazinamide (PZA) and ethambutol (EMB). In this study, we determined the population pharmacokinetics (PopPK) of RIF, INH, EMB and PZA using original experimental sampling designs for single-dose intravenous (IV) and single- and multiple-dose oral administration studies in the mouse model, and used these PopPK models to develop and evaluate new, more informative sampling designs with the aim of reducing the number of animals required for each drug. The RIF, INH, EMB and PZA blood concentrations after single oral and IV doses and multiple-dose oral administrations based on the original designs were used in the PopPK analysis using NONMEM software. The final PopPK models described the data well. Stochastic simulation and estimation were used to optimise the designs. The relative bias and relative imprecision of each pharmacokinetic parameter for each drug were derived and assessed to choose the final designs. The final single-dose IV and oral designs included up to eight samples per mouse with a total of 24 mice required for RIF and EMB and 33 mice for INH and PZA. In the new multiple-dose (zipper) oral designs, the mice were divided into two groups of three per dose, and four samples were taken from each mouse to cover all seven or eight sampling time points. The final number of mice required for the multiple-dose oral designs was 30 for RIF, INH and EMB, 36 for PZA. The number of mice required in the new designs for RIF, INH and EMB was decreased by up to 7-fold and the relative bias and relative imprecision in the parameter estimates were at least similar to those in the original designs.

A multistate tuberculosis pharmacometric model: a framework for studying anti-tubercular drug effects in vitro

OBJECTIVES

Mycobacterium tuberculosis can exist in different states in vitro, which can be denoted as fast multiplying, slow multiplying and non-multiplying. Characterizing the natural growth of M. tuberculosis could provide a framework for accurate characterization of drug effects on the different bacterial states.

METHODS

The natural growth data of M. tuberculosis H37Rv used in this study consisted of viability defined as cfu versus time based on data from an in vitro hypoxia system. External validation of the natural growth model was conducted using data representing the rate of incorporation of radiolabelled methionine into proteins by the bacteria. Rifampicin time-kill curves from log-phase (0.25-16 mg/L) and stationary-phase (0.5-64 mg/L) cultures were used to assess the model's ability to describe drug effects by evaluating different linear and non-linear exposure-response relationships.

RESULTS

The final pharmacometric model consisted of a three-compartment differential equation system representing fast-, slow- and non-multiplying bacteria. Model predictions correlated well with the external data (R(2) = 0.98). The rifampicin effects on log-phase and stationary-phase cultures were separately and simultaneously described by including the drug effect on the different bacterial states. The predicted reduction in log10 cfu after 14 days and at 0.5 mg/L was 2.2 and 0.8 in the log-phase and stationary-phase systems, respectively.

CONCLUSIONS

The model provides predictions of the change in bacterial numbers for the different bacterial states with and without drug effect and could thus be used as a framework for studying anti-tubercular drug effects in vitro.

Population pharmacokinetics of edoxaban in patients with symptomatic deep-vein thrombosis and/or pulmonary embolism--the Hokusai-VTE phase 3 study

AIMS

This study characterized the population pharmacokinetics of edoxaban in patients with symptomatic deep-vein thrombosis and/or pulmonary embolism in the Hokusai-VTE phase 3 study. The impact of the protocol-specified 50% dose reductions applied to patients with body weight ≤ 60 kg, creatinine clearance (CL(cr)) of 30 to 50 ml min(-1) or concomitant P-glycoprotein inhibitor on edoxaban exposure was assessed using simulations.

METHODS

The sparse data from Hokusai-VTE, 9531 concentrations collected from 3707 patients, were pooled with data from 13 phase 1 studies. In the analysis, the covariate relationships used for dose reductions were estimated and differences between healthy subjects and patients as well as additional covariate effects of age, race and gender were explored based on statistical and clinical significance.

RESULTS

A linear two-compartment model with first order absorption preceded by a lag time best described the data. Allometrically scaled body weight was included on disposition parameters. Apparent clearance was parameterized as non-renal and renal. The latter increased non-linearly with increasing CL(cr). Compared with healthy volunteers, inter-compartmental clearance and the CL(cr) covariate effect were different in patients (+64.6% and +274%). Asian patients had a 22.6% increased apparent central volume of distribution. The effect of co-administration of P-glycoprotein inhibitors seen in phase 1 could not be confirmed in the phase 3 data. Model-based simulations revealed lower exposure in dose-reduced compared with non-dose-reduced patients.

CONCLUSIONS

The adopted dose-reduction strategy resulted in reduced exposure compared with non-dose-reduced, thereby overcompensating for covariate effects. The clinical impact of these differences on safety and efficacy remains to be evaluated.

Evaluation of optimized bronchoalveolar lavage sampling designs for characterization of pulmonary drug distribution

Bronchoalveolar lavage (BAL) is a pulmonary sampling technique for characterization of drug concentrations in epithelial lining fluid and alveolar cells. Two hypothetical drugs with different pulmonary distribution rates (fast and slow) were considered. An optimized BAL sampling design was generated assuming no previous information regarding the pulmonary distribution (rate and extent) and with a maximum of two samples per subject. Simulations were performed to evaluate the impact of the number of samples per subject (1 or 2) and the sample size on the relative bias and relative root mean square error of the parameter estimates (rate and extent of pulmonary distribution). The optimized BAL sampling design depends on a characterized plasma concentration time profile, a population plasma pharmacokinetic model, the limit of quantification (LOQ) of the BAL method and involves only two BAL sample time points, one early and one late. The early sample should be taken as early as possible, where concentrations in the BAL fluid ≥ LOQ. The second sample should be taken at a time point in the declining part of the plasma curve, where the plasma concentration is equivalent to the plasma concentration in the early sample. Using a previously described general pulmonary distribution model linked to a plasma population pharmacokinetic model, simulated data using the final BAL sampling design enabled characterization of both the rate and extent of pulmonary distribution. The optimized BAL sampling design enables characterization of both the rate and extent of the pulmonary distribution for both fast and slowly equilibrating drugs.