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

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

Predictive Modeling to Study the Treatment-Shortening Potential of Novel Tuberculosis Drug Regimens, Toward Bundling of Preclinical Data.

BACKGROUND: Given the persistently high global burden of tuberculosis, effective and shorter treatment options are needed. We explored the relationship between relapse and treatment length as well as interregimen differences for 2 novel antituberculosis drug regimens using a mouse model of tuberculosis 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 achieve cure in 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 to occur at 1.6, 4.3, and 7.9 months for BPaMZ, BPaL, and HRZE, respectively. CONCLUSION: This study provides additional evidence for the treatment-shortening capacity of BPaMZ over BPaL and HRZE. To optimally use 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 Tuberculosis Model.

BACKGROUND: The treatment success rate of drug-resistant (DR) tuberculosis is alarmingly low. Therefore, more effective and less complex regimens are urgently required. METHODS: We compared the efficacy of an all oral DR tuberculosis 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 tuberculosis-infected mice during a treatment period of 24 weeks. This treatment was compared with the standard regimen of isoniazid, rifampicin, pyrazinamide, and ethambutol (HRZE). Relapse was assessed 12 weeks after 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 1 mouse had relapse 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 tuberculosis.

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.

Drug Effect of Clofazimine on Persisters Explains an Unexpected Increase in Bacterial Load in Patients.

Antituberculosis (anti-TB) drug development is dependent on informative trials to secure the development of new antibiotics and combination regimens. Clofazimine (CLO) and pyrazinamide (PZA) are important components of recommended standard multidrug treatments of TB. Paradoxically, in a phase IIa trial aiming to define the early bactericidal activity (EBA) of CLO and PZA monotherapy over the first 14 days of treatment, no significant drug effect was demonstrated for the two drugs using traditional statistical analysis. Using a model-based analysis, we characterized the statistically significant exposure-response relationships for both drugs that could explain the original findings of an increase in the numbers of CFU with CLO treatment and no effect with PZA. Sensitive analyses are crucial for exploring drug effects in early clinical trials to make the right decisions for advancement to further development. We propose that this quantitative semimechanistic approach provides a rational framework for analyzing phase IIa EBA studies and can accelerate anti-TB drug development.

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.

A model-based analysis identifies differences in phenotypic resistance between in vitro and in vivo: implications for translational medicine within tuberculosis.

Proper characterization of drug effects on Mycobacterium tuberculosis relies on the characterization of phenotypically resistant bacteria to correctly establish exposure-response relationships. The aim of this work was to evaluate the potential difference in phenotypic resistance in in vitro compared to murine in vivo models using CFU data alone or CFU together with most probable number (MPN) data following resuscitation with culture supernatant. Predictions of in vitro and in vivo phenotypic resistance i.e. persisters, using the Multistate Tuberculosis Pharmacometric (MTP) model framework was evaluated based on bacterial cultures grown with and without drug exposure using CFU alone or CFU plus MPN data. Phenotypic resistance and total bacterial number in in vitro natural growth observations, i.e. without drug, was well predicted by the MTP model using only CFU data. Capturing the murine in vivo total bacterial number and persisters during natural growth did however require re-estimation of model parameter using both the CFU and MPN observations implying that the ratio of persisters to total bacterial burden is different in vitro compared to murine in vivo. The evaluation of the in vitro rifampicin drug effect revealed that higher resolution in the persister drug effect was seen using CFU and MPN compared to CFU alone although drug effects on the other bacterial populations were well predicted using only CFU data. The ratio of persistent bacteria to total bacteria was predicted to be different between in vitro and murine in vivo. This difference could have implications for subsequent translational efforts in tuberculosis drug development.

Model-Based Relationship between the Molecular Bacterial Load Assay and Time to Positivity in Liquid Culture.

The molecular bacterial load (MBL) assay is a new tuberculosis biomarker which provides results in ∼4 hours. The relationship between MBL and time-to-positivity (TTP) has not been thoroughly studied, and predictive models do not exist. We aimed to develop a model for MBL and identify the MBL-TTP relationship in patients. The model was developed on data from 105 tuberculosis patients from Malawi, Mozambique, and Tanzania with joint MBL and TTP observations quantified from patient sputum collected for 12 weeks. MBL was quantified using PCR of mycobacterial RNA and TTP using the mycobacterial growth indicator tube (MGIT) 960 system. Treatment consisted of isoniazid, pyrazinamide, and ethambutol in standard doses together with rifampin 10 or 35 mg/kg of body weight. The developed MBL-TTP model included several linked submodels, a component describing decline of bacterial load in sputum, another component describing growth in liquid culture, and a hazard model translating bacterial growth into a TTP signal. Additional components for contaminated and negative TTP samples were included. Visual predictive checks performed using the developed model gave good description of the observed data. The model predicted greater total sample loss for TTP than MBL due to contamination and negative samples. The model detected an increase in bacterial killing for 35 versus 10 mg/kg rifampin (P = 0.002). In conclusion, a combined model for MBL and TTP was developed that described the MBL-TTP relationship. The full MBL-TTP model or each submodel was used separately. Second, the model can be used to predict biomarker response for MBL given TTP data or vice versa in historical or future trials.

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 (AUC0-24h ). 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 AUC0-24h 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 AUC0-24h -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.

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

AIMS: The hollow­fibre system for tuberculosis (HFS­TB) is a preclinical model qualified by the European Medicines Agency to underpin the anti­TB 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 HFS­TB operational procedures. METHODS: First, we characterized bacterial growth dynamics with different types of hollow­fibre cartridges, Mycobacterium tuberculosis strains and media. Second, we mimicked a moxifloxacin PK profile within hollow­fibre cartridges, in order to check drug­fibres compatibility. Lastly, we mimicked the moxifloxacin total plasma PK profile in human after once daily oral dose of 400 mg to assess PK­PD 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 HFS­TB was contingent on the studied variables. Besides, we demonstrated that drug­fibres compatibility tests are critical preliminary HFS­TB 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 HFS­TB 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 HFS­TB currently overlooked.

Greater Early Bactericidal Activity at Higher Rifampicin Doses Revealed by Modeling and Clinical Trial Simulations.

Background: The currently recommended rifampicin dose (10 mg/kg) for treating tuberculosis is suboptimal. The PanACEA HIGHRIF1 trial evaluated the pharmacokinetics and early bactericidal activity of rifampicin doses of up to 40 mg/kg. Conventional statistical analyses revealed no significant exposure-response relationship. Our objectives were to explore the exposure-response relationship for high-dose rifampicin by using pharmacokinetic-pharmacodynamic modeling and to predict the early bactericidal activity of 50 mg/kg rifampicin. Methods: Data included time to Mycobacterium tuberculosis positivity of liquid cultures of sputum specimens from 83 patients with tuberculosis who were treated with 10 mg/kg rifampicin (n = 8; reference arm) or 20, 25, 30, 35, or 40 mg/kg rifampicin (n = 15/arm) for 7 days. We used a semimechanistic time-to-event approach to model the time-to-positivity data. Rifampicin exposure and baseline time to culture positivity were explored as covariates. Results: The baseline time to culture positivity was a significant covariate on the predicted initial bacterial load, and rifampicin exposure was a significant covariate on the bacterial kill rate in sputum resulting in increased early bactericidal activity. The 90% prediction interval for the predicted median day 7 increase in time to positivity for 50 mg/kg rifampicin was 7.25-10.3 days. Conclusions: A significant exposure-response relationship was found between rifampicin exposure and early bactericidal activity. Clinical trial simulations showed greater early bactericidal activity for 50 mg/kg rifampicin. Clinical Trials Registration: NCT01392911.

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.

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.

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.

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.

Analysis of opioid consumption in clinical trials: a simulation based analysis of power of four approaches.

Inconsistent trial design and analysis is a key reason that few advances in postoperative pain management have been made from clinical trials analyzing opioid consumption data. This study aimed to compare four different approaches to analyze opioid consumption data. A repeated time-to-event (RTTE) model in NONMEM was used to simulate clinical trials of morphine consumption with and without a hypothetical adjuvant analgesic in doses equivalent to 15-62% reduction in morphine consumption. Trials were simulated with duration of 24-96 h. Monte Carlo simulation and re-estimation were performed to determine sample size required to demonstrate efficacy with 80% power using t test, Mann-Whitney rank sum test, time-to-event (TTE) modeling and RTTE modeling. Precision of efficacy estimates for RTTE models were evaluated in 500 simulations. A sample size of 50 patients was required to detect 37% morphine sparing effect with at least 80% power in a 24 h trial with RTTE modeling whereas the required sample size was 200 for Mann-Whitney, 180 for t-test and 76 for TTE models. Extending the trial duration from 24 to 96 h reduced the required sample size by 3.1 fold with RTTE modeling. Precise estimate of potency was obtained with a RTTE model accounting for both morphine effects and time-varying covariates on opioid consumption. An RTTE analysis approach proved better suited for demonstrating efficacy of opioid sparing analgesics than traditional statistical tests as a lower sample size was required due the ability to account for time-varying factors including PK.

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.

A Pharmacokinetic-Pharmacodynamic Model of Morphine Exposure and Subsequent Morphine Consumption in Postoperative Pain.

PURPOSE: To characterize the pharmacokinetic-pharmacodynamic (PK-PD) relationship between exposure of morphine and subsequent morphine consumption and to develop simulation tools for model validation. METHODS: Dose, formulation and time of morphine administration was available from a published study in 63 patients receiving intravenous, oral immediate release or oral controlled release morphine on request after hip surgery. The PK-PD relationship between predicted exposure of morphine and morphine consumption was modeled using repeated time to event (RTTE) modeling in NONMEM. To validate the RTTE model, a visual predictive check method was developed with simulated morphine consumption given the exposure of preceding morphine administration. RESULTS: The probability of requesting morphine was found to be significantly related to the exposure of morphine as well as night/day. Oral controlled release morphine was more effective than intravenous and oral immediate release formulations at equivalent average concentrations. Maximum effect was obtained for 8 h by oral controlled release doses ≥ 15 mg, where probability of requesting a new dose was reduced to 20% for a typical patient. CONCLUSION: This study demonstrates the first quantitative link between exposure of morphine and subsequent morphine consumption and introduces an efficient visual predictive check approach with simulation of adaptive dosing.

Repeated Time-to-event Analysis of Consecutive Analgesic Events in Postoperative Pain.

BACKGROUND: Reduction in consumption of opioid rescue medication is often used as an endpoint when investigating analgesic efficacy of drugs by adjunct treatment, but appropriate methods are needed to analyze analgesic consumption in time. Repeated time-to-event (RTTE) modeling is proposed as a way to describe analgesic consumption by analyzing the timing of consecutive analgesic events. METHODS: Retrospective data were obtained from 63 patients receiving standard analgesic treatment including morphine on request after surgery following hip fracture. Times of analgesic events up to 96 h after surgery were extracted from hospital medical records. Parametric RTTE analysis was performed with exponential, Weibull, or Gompertz distribution of analgesic events using NONMEM, version 7.2 (ICON Development Solutions, USA). The potential influences of night versus day, sex, and age were investigated on the probability. RESULTS: A Gompertz distribution RTTE model described the data well. The probability of having one or more analgesic events within 24 h was 80% for the first event, 55% for the second event, 31% for the third event, and 18% for fourth or more events for a typical woman of age 80 yr. The probability of analgesic events decreased in time, was reduced to 50% after 3.3 days after surgery, and was significantly lower (32%) during night compared with day. CONCLUSIONS: RTTE modeling described analgesic consumption data well and could account for time-dependent changes in probability of analgesic events. Thus, RTTE modeling of analgesic events is proposed as a valuable tool when investigating new approaches to pain management such as opioid-sparing analgesia.