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Background Data on piperacillin-tazobactam pharmacokinetics and optimal dosing in children with cancer and fever are limited. Our objective was to investigate piperacillin pharmacokinetics and the probability of target attainment (PTA) with standard intermittent administration (IA), and to simulate PTA in other dosing regimens. Procedure This prospective pharmacokinetic study was conducted from April 2016 to January 2018. Children with cancer receiving empiric piperacillin-tazobactam to treat infections were included. Piperacillin-tazobactam 100 mg/kg was infused over 5 min every 8 hours (IA). An optimized sample schedule provided six blood samples per subject for piperacillin concentration determination. The evaluated targets included: (1) 100% time of free piperacillin concentration above the minimum inhibitory concentration (fT > MIC) and (2) 50% fT > 4x MIC. MIC50 and MIC90 were defined based on an intrainstitutional MIC range. Results A total of 482 piperacillin concentrations were obtained from 43 children (aged 1-18 years) during 89 fever episodes. Standard IA resulted in insufficient target attainment, with significant differences in piperacillin pharmacokinetics for different body weights. Median fT > MIC was 61.2%, 53.5%, and 36.3% for MIC50 (2.0 mg/L), MIC90 (4.0 mg/L), and breakpoint for Pseudomonas aeruginosa (16.0 mg/L), respectively. Correspondingly, the median fT > 4x MIC was 43%, 36.3%, and 20.1%. Simulations showed that only continuous infusion reached a PTA of 95% for MIC = 16.0 mg/L, while extended infusion lasting half of the dosing interval reached a PTA of 95% for MIC <= 8 mg/L. Conclusions Our data revealed insufficient PTA with standard IA of piperacillin-tazobactam in children with cancer and fever. Alternative dosing strategies, preferably continuous infusion, are required to ensure adequate PTA.

Background The β-lactam antibiotic piperacillin (in combination with tazobactam) is commonly chosen for empirical treatment of suspected bacterial infections. However, pharmacokinetic variability among patient populations and across ages leads to uncertainty when selecting a dosing regimen to achieve an appropriate pharmacodynamic target. Objectives To guide dosing by establishing a population pharmacokinetic model for unbound piperacillin in febrile children receiving cancer chemotherapy, and to assess pharmacokinetic/pharmacodynamic target attainment (100% fT>1xMIC and 50% fT>4xMIC) and resultant exposure, across body weights. Methods Forty-three children admitted for 89 febrile episodes contributed 482 samples to the pharmacokinetic analysis. The typical doses required for target attainment were compared for various dosing regimens, in particular prolonged infusions, across MICs and body weights. Results A two-compartment model with inter-fever-episode variability in CL, and body weight included through allometry, described the data. A high CL of 15.4L/h (70kg) combined with high glomerular filtration rate (GFR) values indicated rapid elimination and hyperfiltration. The target of 50% fT>4xMIC was achieved for an MIC of 4.0mg/L in a typical patient with extended infusions of 2-3 (q6h) or 3-4 (q8h)h, at or below the standard adult dose (75 and 100mg/kg/dose for q6h and q8h, respectively). Higher doses or continuous infusion were needed to achieve 100% fT>1xMIC due to the rapid piperacillin elimination. Conclusions The licensed dose for children with febrile neutropenia (80mg/kg q6h as a 30min infusion) performs poorly for attainment of fT>MIC pharmacokinetic/pharmacodynamic targets. Given the population pharmacokinetic profile, feasible dosing regimens with reasonable exposure are continuous infusion (100% fT>1xMIC) or prolonged infusions (50% fT>4xMIC).

Aims Cladribine tablets have shown significant efficacy for the treatment of relapsing multiple sclerosis, a chronic and debilitating immune-mediated disorder. This study was conducted to examine acute and/or cumulative effects of cladribine tablets 10 mg (3.5 or 5.25 mg/kg cumulative dose over 2 years) on heart rate, AV conduction and cardiac repolarization in patients with relapsing-remitting multiple sclerosis (RRMS). Methods CLARITY was a 96-week, double-blind, placebo-controlled, multicentre trial which evaluated the safety and efficacy of cladribine tablets 3.5 and 5.25 mg/kg body weight in patients with RRMS. A total of 135 patients were included in the ECG substudy, providing a total of 1534 post-dose ECGs. ECG data were collected 15 minutes pre-dose and between 0.5 and 3 hours post-dose at pre-study evaluation, study Day 1 and Weeks 5, 9, 13, 48 and 52. Results For cladribine tablets 3.5 mg/kg, the maximum change in placebo-adjusted post-dose QTcF vs. visit-baseline (BL) was -0.42 ms (90% CI: -3.61-4.44) at Week 1 (acute effects), and 3.20 ms (90% CI: -0.08-6.33) for cladribine tablets 5.25 mg/kg. The greatest observed differences in post-dose QTcF vs. study BL occurred at Week 48 for both the 3.5 and 5.25 mg/kg doses of cladribine tablets with 5.99 ms (90% CI: 0.53-11.44) and 8.74 ms (90% CI: 3.18-14.31), respectively. No significant changes were observed in T-wave morphology in either treatment group. Conclusions Cladribine tablets 3.5 mg/kg (approved dose in Europe/other regions) did not confer clinically meaningful effects on heart rate, AV conduction and ventricular repolarization.

Inter-individual variability in paclitaxel pharmacokinetics may play a role in the response to chemotherapy. Therefore, we studied the association between paclitaxel clearance and treatment response in patients with esophageal cancer. All patients who received paclitaxel (plus carboplatin) treatment for esophageal cancer between 2007 and 2013 were included. The treatment was given as neoadjuvant chemoradiotherapy (nCRT), induction chemotherapy (iCT), or palliative chemotherapy (pCT). The treatment response was assessed by the tumor regression grade (TRG) or by the RECIST1.1 criteria, respectively. The unbound paclitaxel clearance (CL) was estimated with NONMEM. The log-transformed clearance was related to response with ANOVA and independent sample t-tests. A total of 166 patients were included, of whom 113 received nCRT, 23 iCT and 30 pCT. In patients receiving nCRT, paclitaxel clearance was not associated with tumor regression grade (p-value = 0.25), nor with pathologically complete response (geometric mean 561.6 L/h) and residual disease (geometric mean 566.1 L/h, p-value = 0.90). In patients who underwent iCT or pCT, also no association between paclitaxel clearance and RECIST outcome was identified (iCT: p-value = 0.08 and pCT: p-value = 0.81, respectively). In conclusion, systemic paclitaxel exposure was not associated with response to common paclitaxel-based treatment regimens for esophageal cancer. Future studies should focus on tumor exposure in relation to systemic exposure and treatment outcome.

Inter-individual variability in paclitaxel pharmacokinetics may play a role in the response to chemotherapy. Therefore, we studied the association between paclitaxel clearance and treatment response in patients with esophageal cancer. All patients who received paclitaxel (plus carboplatin) treatment for esophageal cancer between 2007 and 2013 were included. The treatment was given as neoadjuvant chemoradiotherapy (nCRT), induction chemotherapy (iCT), or palliative chemotherapy (pCT). The treatment response was assessed by the tumor regression grade (TRG) or by the RECIST1.1 criteria, respectively. The unbound paclitaxel clearance (CL) was estimated with NONMEM. The log-transformed clearance was related to response with ANOVA and independent sample t-tests. A total of 166 patients were included, of whom 113 received nCRT, 23 iCT and 30 pCT. In patients receiving nCRT, paclitaxel clearance was not associated with tumor regression grade (p-value = 0.25), nor with pathologically complete response (geometric mean 561.6 L/h) and residual disease (geometric mean 566.1 L/h, p-value = 0.90). In patients who underwent iCT or pCT, also no association between paclitaxel clearance and RECIST outcome was identified (iCT: p-value = 0.08 and pCT: p-value = 0.81, respectively). In conclusion, systemic paclitaxel exposure was not associated with response to common paclitaxel-based treatment regimens for esophageal cancer. Future studies should focus on tumor exposure in relation to systemic exposure and treatment outcome.

Sufficient antibiotic dosing in septic patients is essential for reducing mortality. Piperacillin-tazobactam is often used for empirical treatment, but due to the pharmacokinetic (PK) variability seen in septic patients, optimal dosing may be a challenge. We determined the PK profile for piperacillin given at 4 g every 8 h in 22 septic patients admitted to a medical ward. Piperacillin concentrations were compared to the clinical breakpoint MIC for Pseudomonas aeruginosa (16 mg/liter), and the following PK/pharmacodynamic (PD) targets were evaluated: the percentage of the dosing interval that the free drug concentration is maintained above the MIC (fTMIC) of 50% and 100%. A two-compartment population PK model described the data well, with clearance being divided into renal and nonrenal components. The renal component was proportional to the estimated creatinine clearance (eCLCR) and constituted 74% of the total clearance in a typical individual (eCLCR, 83.9 ml/min). Patients with a high eCLCR (>130 ml/min) were at risk of subtherapeutic concentrations for the current regimen, with a 90% probability of target attainment being reached at MICs of 2.0 (50% fTMIC) and 0.125 mg/liter (100% fTMIC). Simulations of alternative dosing regimens and modes of administration showed that dose increment and prolonged infusion increased the chance of achieving predefined PK/PD targets. Alternative dosing strategies may therefore be needed to optimize piperacillin exposure in septic patients. (This study has been registered at ClinicalTrials.gov under identifier NCT02569086.)

Colistin is a polymyxin antibiotic used to treat patients infected with multidrug-resistant Gram-negative bacteria (MDR-GNB). The objective of this work was to develop a whole-body physiologically based pharmacokinetic (WB-PBPK) model to predict tissue distribution of colistin in rat. The distribution of a drug in a tissue is commonly characterized by its tissue-to-plasma partition coefficient, K-p. Colistin and its prodrug, colistin methanesulfonate (CMS) K-p priors, were measured experimentally from rat tissue homogenates or predicted in silico. The PK parameters of both compounds were estimated fitting invivo their plasma concentration-time profiles from six rats receiving an i.v. bolus of CMS. The variability in the data was quantified by applying a nonlinear mixed effect (NLME) modelling approach. A WB-PBPK model was developed assuming a well-stirred and perfusion-limited distribution in tissue compartments. Prior information on tissue distribution of colistin and CMS was investigated following three scenarios: K-p was estimated using in silico K-p priors (I) or K-p was estimated using experimental K-p priors (II) or K-p was fixed to the experimental values (III). The WB-PBPK model best described colistin and CMS plasma concentration-time profiles in scenario II. Colistin-predicted concentrations in kidneys in scenario II were higher than in other tissues, which was consistent with its large experimental K-p prior. This might be explained by a high affinity of colistin for renal parenchyma and active reabsorption into the proximal tubular cells. In contrast, renal accumulation of colistin was not predicted in scenario I. Colistin and CMS clearance estimates were in agreement with published values. The developed model suggests using experimental priors over in silico K-p priors for kidneys to provide a better prediction of colistin renal distribution. Such models might serve in drug development for interspecies scaling and investigate the impact of disease state

Background: Deriving suitable dosing regimens for antibiotic combination therapy poses several challenges as the drug interaction can be highly complex, the traditional pharmacokinetic-pharmacodynamic (PKPD) index methodology cannot be applied straightforwardly, and exploring all possible dose combinations is unfeasible. Therefore, semi-mechanistic PKPD models developed based on in vitro single and combination experiments can be valuable to suggest suitable combination dosing regimens. Aims: To outline how the interaction between two antibiotics has been characterized in semi-mechanistic PKPD models. We also explain how such models can be applied to support dosing regimens and design future studies. Sources: PubMed search for published semi-mechanistic PKPD models of antibiotic drug combinations. Content: Thirteen publications were identified where ten had applied subpopulation synergy to characterize the combined effect, i.e. independent killing rates for each drug and bacterial subpopulation. We report the various types of interaction functions that have been used to describe the combined drug effects and that characterized potential deviations from additivity under the PKPD model. Simulations from the models had commonly been performed to compare single versus combined dosing regimens and/or to propose improved dosing regimens.

The objectives of this study were to describe meropenem pharmacokinetics (PK) in plasma and/or subcutaneous adipose tissue (SCT) in critically ill patients receiving extracorporeal membrane oxygenation (ECMO) treatment and to develop a population PK model to simulate alternative dosing regimens and modes of administration. We conducted a prospective observational study. Ten patients on ECMO treatment received meropenem (1 or 2 g) intravenously over 5 min every 8 h. Serial SCT concentrations were determined using microdialysis and compared with plasma concentrations. A population PK model of SCT and plasma data was developed using NONMEM. Time above clinical breakpoint MIC for Pseudomonas aeruginosa (8 mg/liter) was predicted for each patient. The following targets were evaluated: time for which the free (unbound) concentration is maintained above the MIC of at least 40% (40% fT>MIC), 100% fT>MIC, and 100% fT>4×MIC. For all dosing regimens simulated in both plasma and SCT, 40% fT>MIC was attained. However, prolonged meropenem infusion would be needed for 100% fT>MIC and 100% fT>4×MIC to be obtained. Meropenem plasma and SCT concentrations were associated with estimated creatinine clearance (eCLCr). Simulations showed that in patients with increased eCLCr, dose increment or continuous infusion may be needed to obtain therapeutic meropenem concentrations. In conclusion, our results show that using traditional targets of 40% fT>MIC for standard meropenem dosing of 1 g intravenously every 8 h is likely to provide sufficient meropenem concentration to treat the problematic pathogen P. aeruginosa for patients receiving ECMO treatment. However, for patients with an increased eCLCr, or if more aggressive targets, like 100% fT>MIC or 100% fT>4×MIC, are adopted, incremental dosing or continuous infusion may be needed.

Background: Colistin-carbapenem combinations are synergistic in vitro against carbapenem-resistant Gram-negative bacteria. We aimed to test whether combination therapy improves clinical outcomes for adults with infections caused by carbapenem-resistant or carbapenemase-producing Gram-negative bacteria. Methods: A randomised controlled superiority trial was done in six hospitals in Israel, Greece, and Italy. We included adults with bacteraemia, ventilator-associated pneumonia, hospital-acquired pneumonia, or urosepsis caused by carbapenem-non-susceptible Gram-negative bacteria. Patients were randomly assigned (1:1) centrally, by computer-generated permuted blocks stratified by centre, to intravenous colistin (9-million unit loading dose, followed by 45 million units twice per day) or colistin with meropenem (2-g prolonged infusion three times per day). The trial was open-label, with blinded outcome assessment. Treatment success was defined as survival, haemodynamic stability, improved or stable Sequential Organ Failure Assessment score, stable or improved ratio of partial pressure of arterial oxygen to fraction of expired oxygen for patients with pneumonia, and microbiological cure for patients with bacteraemia. The primary outcome was clinical failure, defined as not meeting all success criteria by intention-to-treat analysis, at 14 days after randomisation. This trial is registered at ClinicalTrials.gov, number NCT01732250, and is closed to accrual. Findings: Between Oct 1, 2013, and Dec 31, 2016, we randomly assigned 406 patients to the two treatment groups. Most patients had pneumonia or bacteraemia (355/406, 87%), and most infections were caused by Acinetobacter baumannii (312/406, 77%). No significant difference between colistin monotherapy (156/198, 79%) and combination therapy (152/208, 73%) was observed for clinical failure at 14 days after randomisation (risk difference -5.7%, 95% CI -13.9 to 2.4; risk ratio [RR] 0.93, 95% CI 0.83-1.03). Results were simila

Predicting competition between antibiotic-susceptible wild-type (WT) and less susceptible mutant (MT) bacteria is valuable for understanding how drug concentrations influence the emergence of resistance. Pharmacokinetic/pharmacodynamic (PK/PD) models predicting the rate and extent of takeover of resistant bacteria during different antibiotic pressures can thus be a valuable tool in improving treatment regimens. The aim of this study was to evaluate a previously developed mechanism-based PK/PD model for its ability to predict in vitro mixed-population experiments with competition between Escherichia coli (E. coli) WT and three well-defined E. coli resistant MTs when exposed to ciprofloxacin. Model predictions for each bacterial strain and ciprofloxacin concentration were made for in vitro static and dynamic time–kill experiments measuring CFU (colony forming units)/mL up to 24 h with concentrations close to or below the minimum inhibitory concentration (MIC), as well as for serial passage experiments with concentrations well below the MIC measuring ratios between the two strains with flow cytometry. The model was found to reasonably well predict the initial bacterial growth and killing of most static and dynamic time–kill competition experiments without need for parameter re-estimation. With parameter re-estimation of growth rates, an adequate fit was also obtained for the 6-day serial passage competition experiments. No bacterial interaction in growth was observed. This study demonstrates the predictive capacity of a PK/PD model and further supports the application of PK/PD modelling for prediction of bacterial kill in different settings, including resistance selection.

Inadequate dose selection for confirmatory trials is currently still one of the most challenging issues in drug development, as illustrated by high rates of late-stage attritions in clinical development and postmarketing commitments required by regulatory institutions. In an effort to shift the current paradigm in dose and regimen selection and highlight the availability and usefulness of well-established and regulatory-acceptable methods, the European Medicines Agency (EMA) in collaboration with the European Federation of Pharmaceutical Industries Association (EFPIA) hosted a multistakeholder workshop on dose finding (London 4-5 December 2014). Some methodologies that could constitute a toolkit for drug developers and regulators were presented. These methods are described in the present report: they include five advanced methods for data analysis (empirical regression models, pharmacometrics models, quantitative systems pharmacology models, MCP-Mod, and model averaging) and three methods for study design optimization (Fisher information matrix (FIM)-based methods, clinical trial simulations, and adaptive studies). Pairwise comparisons were also discussed during the workshop; however, mostly for historical reasons. This paper discusses the added value and limitations of these methods as well as challenges for their implementation. Some applications in different therapeutic areas are also summarized, in line with the discussions at the workshop. There was agreement at the workshop on the fact that selection of dose for phase III is an estimation problem and should not be addressed via hypothesis testing. Dose selection for phase III trials should be informed by well-designed dosefinding studies; however, the specific choice of method(s) will depend on several aspects and it is not possible to recommend a generalized decision tree. There are many valuable methods available, the methods are not mutually exclusive, and they should be used in conjunction to ensure a scie