Estimated glomerular filtration rate as a tool for early identification of patients with insufficient exposure to beta-lactam antibiotics in intensive care units

BACKGROUND

Only about 50% of intensive care unit (ICU) patients reach a free trough concentration above MIC (100% fT > MIC) of beta-lactam antibiotics. Although dose adjustments based on therapeutic drug monitoring (TDM) could be beneficial, TDM is not widely available. We investigated serum creatinine-based estimated GFR (eGFR) as a rapid screening tool to identify ICU patients at risk of insufficient exposure.

METHOD

Ninety-three adult patients admitted to four ICUs in southeast Sweden treated with piperacillin/tazobactam, meropenem, or cefotaxime were included. Beta-lactam trough concentrations were measured. The concentration target was set to 100% fT > MICECOFF (2, 4, and 16 mg/L based on calculated free levels for meropenem, cefotaxime, and piperacillin, respectively). eGFR was primarily determined via Chronic Kidney Disease-Epidemiology Collaboration (CKD-EPI) and compared to three other eGFR equations. Data was analysed using logistic regression and receiver operative characteristic (ROC) curves.

RESULTS

With intermittent standard dosing, insufficient exposure was common in patients with a relative eGFR ≥48mL/min/1.73m2 [85%, (45/53)], particularly when treated with cefotaxime [96%, (24/25)]. This eGFR cut-off had a sensitivity of 92% and specificity of 82% (AUC 0.871, p < 0.001) in identifying insufficient exposure. In contrast, patients with eGFR <48mL/min/1.73m2 had high target attainment [90%, (36/40)] with a wide variability in drug exposure. There was no difference between the four eGFR equations (AUC 0.866-0.872, cut-offs 44-51 ml/min/1.73m2).

CONCLUSION

Serum creatinine-based eGFR is a simple and widely available surrogate marker with potential for early identification of ICU patients at risk of insufficient exposure to piperacillin, meropenem, and cefotaxime.

Synergy of polymyxin B and minocycline against KPC-3- and OXA-48-producing Klebsiella pneumoniae in dynamic time-kill experiments: agreement with in silico predictions

OBJECTIVES

Combination therapy is often used for carbapenem-resistant Gram-negative bacteria. We previously demonstrated synergy of polymyxin B and minocycline against carbapenem-resistant Klebsiella pneumoniae in static time-kill experiments and developed an in silico pharmacokinetic/pharmacodynamic (PK/PD) model. The present study assessed the synergistic potential of this antibiotic combination in dynamic experiments.

METHODS

Two clinical K. pneumoniae isolates producing KPC-3 and OXA-48 (polymyxin B MICs 0.5 and 8 mg/L, and minocycline MICs 1 and 8 mg/L, respectively) were included. Activities of the single drugs and the combination were assessed in 72 h dynamic time-kill experiments mimicking patient pharmacokinetics. Population analysis was performed every 12 h using plates containing antibiotics at 4× and 8× MIC. WGS was applied to reveal resistance genes and mutations.

RESULTS

The combination showed synergistic and bactericidal effects against the KPC-3-producing strain from 12 h onwards. Subpopulations with decreased susceptibility to polymyxin B were frequently detected after single-drug exposures but not with the combination. Against the OXA-48-producing strain, synergy was observed between 4 and 8 h and was followed by regrowth. Subpopulations with decreased susceptibility to polymyxin B and minocycline were detected throughout experiments. For both strains, the observed antibacterial activities showed overall agreement with the in silico predictions.

CONCLUSIONS

Polymyxin B and minocycline in combination showed synergistic effects, mainly against the KPC-3-producing K. pneumoniae. The agreement between the experimental results and in silico predictions supports the use of PK/PD models based on static time-kill data to predict the activity of antibiotic combinations at dynamic drug concentrations.

Therapeutic drug monitoring of vancomycin and meropenem: Illustration of the impact of inaccurate information in dose administration time

OBJECTIVES

To illustrate the impact of errors in documented dose administration time on therapeutic drug monitoring (TDM)-based target attainment evaluation for vancomycin and meropenem, and to explore the influence of drug and patient characteristics, and TDM sampling strategies.

METHODS

Bedside observations of errors in documented dose administration times were collected. Population pharmacokinetic simulations were performed for vancomycin and meropenem, evaluating different one- and two-sampling strategies for populations with estimated creatinine clearance (CLcr) of 30, 80 or 130 mL/min. The impact of errors was evaluated as the proportion of individuals incorrectly considered to have reached the target.

RESULTS

Of 143 observed dose administrations, 97% of doses were given within ±30 min of the documented time. For vancomycin, a +30 min error was predicted to result in a 0.1-3.9 percentage point increase of cases incorrectly evaluated as reaching area under the concentration-time curve during a 24-hour period (AUC24)/minimum inhibitory concentration (MIC) >400, with the largest increase for patients with augmented renal clearance and peak and trough sampling. For meropenem, a +30 min error resulted in a 1.3-6.4 and 0-20 percentage point increase of cases incorrectly evaluated as reaching 100% T>MIC, and 50% T>MIC, respectively. Overall, mid-dose and trough sampling was most favourable for both antibiotics.

CONCLUSIONS

For vancomycin, simulations indicate that TDM-based target attainment evaluation is robust with respect to the observed errors in dose administration time of ±30 min; however, the errors had a potentially clinically important impact in patients with augmented renal clearance. For meropenem, extra measures to promote correct documentation are warranted when using TDM, as the impact of errors was evident even in patients with normal renal function.

Model-based assessment of neutrophil-mediated phagocytosis and digestion of bacteria across in vitro and in vivo studies

Neutrophil granulocytes are key components of the host response against pathogens, and severe neutropenia, with neutrophil counts below 0.5 × 106 cells/mL, renders patients increasingly vulnerable to infections. Published in vitro (n = 7) and in vivo (n = 5) studies with time-course information on bacterial and neutrophil counts were digitized to characterize the kinetics of neutrophil-mediated bacterial killing and inform on the immune systems' contribution to the clearance of bacterial infections. A mathematical model for the in vitro dynamics of bacteria and the kinetics of neutrophil-mediated phagocytosis and digestion was developed, which was extended to in vivo studies in immune-competent and immune-compromised mice. Neutrophil-mediated bacterial killing was described by two first-order processes-phagocytosis and digestion-scaled by neutrophil concentration, where 50% of the maximum was achieved at neutrophil counts of 1.19 × 106 cells/mL (phagocytosis) and 6.55 × 106 cells/mL (digestion). The process efficiencies diminished as the phagocytosed bacteria to total neutrophils ratio increased (with 50% reduction at a ratio of 3.41). Neutrophil in vivo dynamics were captured through the characterization of myelosuppressive drug effects and postinoculation neutrophil influx into lungs and by system differences (27% bacterial growth and 9.3% maximum capacity, compared with in vitro estimates). Predictions showed how the therapeutically induced reduction of neutrophil counts enabled bacterial growth, especially when falling below 0.5 × 106 cells/mL, whereas control individuals could deal with all tested bacterial burdens (up to 109  colony forming units/g lung). The model-based characterization of neutrophil-mediated bacterial killing simultaneously predicted data across in vitro and in vivo studies and may be used to inform the capacity of host-response at the individual level.

The complexities of communication at hospital discharge of older patients: a qualitative study of healthcare professionals' views

BACKGROUND

Hospital discharge of older patients is a high-risk situation in terms of patient safety. Due to the fragmentation of the healthcare system, communication and coordination between stakeholders are required at discharge. The aim of this study was to explore communication in general and medication information transfer in particular at hospital discharge of older patients from the perspective of healthcare professionals (HCPs) across different organisations within the healthcare system.

METHODS

We conducted a qualitative study using focus group and individual or group interviews with HCPs (physicians, nurses and pharmacists) across different healthcare organisations in Sweden. Data were collected from September to October 2021. A semi-structured interview guide including questions on current medication communication practices, possible improvements and feedback on suggestions for alternative processes was used. The data were analysed thematically, guided by the systematic text condensation method.

RESULTS

In total, four focus group and three semi-structured interviews were conducted with 23 HCPs. Three main themes were identified: 1) Support systems that help and hinder describes the use of support systems in the discharge process to compensate for the fragmentation of the healthcare system and the impact of these systems on HCPs' communication; 2) Communication between two separate worlds depicts the difficulties in communication experienced by HCPs in different healthcare organisations and how they cope with them; and 3) The large number of medically complex patients disrupts the communication reveals how the highly pressurised healthcare system impacts on HCPs' communication at hospital discharge.

CONCLUSIONS

Communication at hospital discharge is hindered by the fragmented, highly pressurised healthcare system. HCPs are at risk of moral distress when coping with communication difficulties. Improved communication methods at hospital discharge are needed for the benefit of both patients and HCPs.

Predicting cytokine kinetics during sepsis; a modelling framework from a porcine sepsis model with live Escherichia coli

BACKGROUND

Describing the kinetics of cytokines involved as biomarkers of sepsis progression could help to optimise interventions in septic patients. This work aimed to quantitively characterise the cytokine kinetics upon exposure to live E. coli by developing an in silico model, and to explore predicted cytokine kinetics at different bacterial exposure scenarios.

METHODS

Data from published in vivo studies using a porcine sepsis model were analysed. A model describing the time courses of bacterial dynamics, endotoxin (ETX) release, and the kinetics of TNF and IL-6 was developed. The model structure was extended from a published model that quantifies the ETX-cytokines relationship. An external model evaluation was conducted by applying the model to literature data. Model simulations were performed to explore the sensitivity of the host response towards differences in the input rate of bacteria, while keeping the total bacterial burden constant.

RESULTS

The analysis included 645 observations from 30 animals. The blood bacterial count was well described by a one-compartment model with linear elimination. A scaling factor was estimated to quantify the ETX release by bacteria. The model successfully described the profiles of TNF, and IL-6 without a need to modify the ETX-cytokines model structure. The kinetics of TNF, and IL-6 in the external datasets were well predicted. According to the simulations, the ETX tolerance development results in that low initial input rates of bacteria trigger the lowest cytokine release.

CONCLUSION

The model quantitively described and predicted the cytokine kinetics triggered by E. coli exposure. The host response was found to be sensitive to the bacterial exposure rate given the same total bacterial burden.

Risk factors for and preventability of drug‐related hospital revisits in older patients: a post‐hoc analysis of a randomised clinical trial

AIM

The aims of this study were (1) to identify older patients' risk factors for drug-related readmissions and (2) to assess the preventability of older patients' drug-related revisits.

METHODS

Post hoc analysis of a randomized clinical trial with patients aged ≥65 years at eight wards within four hospitals in Sweden. (1) The primary outcome was risk factors for drug-related readmission within 12 months post-discharge. A Cox proportional hazards model was made with sociodemographic and clinical baseline characteristics. (2) Four hundred trial participants were randomly selected and their revisits (admissions and emergency department visits) were assessed to identify potentially preventable drug-related revisits, related diseases and causes.

RESULTS

(1) Among 2637 patients (median age 81 years), 582 (22%) experienced a drug-related readmission within 12 months. Sixteen risk factors (hazard ratio >1, P < 0.05) related to age, previous hospital visits, medication use, multimorbidity and cardiovascular, liver, lung and peptic ulcer disease were identified. (2) The 400 patients experienced a total of 522 hospital revisits, of which 85 (16%) were potentially preventable drug-related revisits. The two most prevalent related diseases were heart failure (n = 24, 28%) and chronic obstructive pulmonary disease (n = 13, 15%). The two most prevalent causes were inadequate treatment (n = 23, 27%) and insufficient or no follow-up (n = 22, 26%).

CONCLUSION

(1) Risk factors for drug-related readmissions in older hospitalized patients were age, previous hospital visits, medication use and multiple diseases. (2) Potentially preventable drug-related hospital revisits are common and might be prevented through adequate pharmacotherapy and continuity of care in older patients with cardiovascular or lung disease.

Research priorities towards precision antibiotic therapy to improve patient care

Antibiotic resistance presents an incessant threat to our drug armamentarium that necessitates novel approaches to therapy. Over the past several decades, investigation of pharmacokinetic and pharmacodynamic (PKPD) principles has substantially improved our understanding of the relationships between the antibiotic, pathogen, and infected patient. However, crucial gaps in our understanding of the pharmacology of antibacterials and their optimal use in the care of patients continue to exist; simply attaining antibiotic exposures that are considered adequate based on traditional targets can still result in treatment being unsuccessful and resistance proliferation for some infections. It is this salient paradox that points to key future directions for research in antibiotic therapeutics. This Personal View discusses six priority areas for antibiotic pharmacology research: (1) antibiotic-pathogen interactions, (2) antibiotic targets for combination therapy, (3) mechanistic models that describe the time-course of treatment response, (4) understanding and modelling of host response to infection, (5) personalised medicine through therapeutic drug management, and (6) application of these principles to support development of novel therapies. Innovative approaches that enhance our understanding of antibiotic pharmacology and facilitate more accurate predictions of treatment success, coupled with traditional pharmacology research, can be applied at the population level and to individual patients to improve outcomes.

Imitation of β-lactam binding enables broad-spectrum metallo-β-lactamase inhibitors

Carbapenems are vital antibiotics, but their efficacy is increasingly compromised by metallo-β-lactamases (MBLs). Here we report the discovery and optimization of potent broad-spectrum MBL inhibitors. A high-throughput screen for NDM-1 inhibitors identified indole-2-carboxylates (InCs) as potential β-lactamase stable β-lactam mimics. Subsequent structure-activity relationship studies revealed InCs as a new class of potent MBL inhibitor, active against all MBL classes of major clinical relevance. Crystallographic studies revealed a binding mode of the InCs to MBLs that, in some regards, mimics that predicted for intact carbapenems, including with respect to maintenance of the Zn(II)-bound hydroxyl, and in other regards mimics binding observed in MBL-carbapenem product complexes. InCs restore carbapenem activity against multiple drug-resistant Gram-negative bacteria and have a low frequency of resistance. InCs also have a good in vivo safety profile, and when combined with meropenem show a strong in vivo efficacy in peritonitis and thigh mouse infection models.

Continuous infusion of piperacillin-tazobactam significantly improves target attainment in children with cancer and fever

Background

Children with febrile neutropenia commonly exhibit alterations of pharmacokinetic (PK) parameters, leading to decreased β‐lactam concentrations.

Aims

This study evaluated piperacillin PK and probability of target attainment (PTA) with continuous infusion of piperacillin‐tazobactam, in order to optimize the dosing regimen.

Methods

This prospective PK study included children with cancer, aged 1–17 years, who were treated with piperacillin‐tazobactam for suspected or verified infection. A piperacillin‐tazobactam loading dose (100 mg/kg) was administered followed by continuous infusion (300 mg/kg/day). The unbound fraction of piperacillin was quantified by high‐performance liquid chromatography and PK were described using population PK modeling. PK data was used to update and extend a previous PK model built on data following intermittent administration. Monte Carlo simulations were performed to assess PTA for targets of 100% time above the minimum inhibitory concentration (100% fT > MIC) and 50% fT > 4xMIC.

Results

We included 68 fever episodes among 38 children with a median (IQR) age of 6.5 years and body weight of 27.4 kg (15.1–54.0). A three‐compartment model adequately described the concentration‐time data. Median (95% confidence interval) estimates for clearance and piperacillin concentration at steady state were 14.2 L/h/70 kg (13.0; 15.3) and 47.6 mg/L (17.2; 129.5), respectively. Body weight or lean body weight was significantly associated with the PK parameters, and body weight was integrated in the final PK model. Based on piperacillin exposure, continuous infusion was the only dosing regimen to achieve optimal PTA for the P. aeruginosa breakpoint (16 mg/L) with the target of 100% fT > MIC, and a daily dose of 300 mg/kg reached optimal PTA. The strict target of 50% fT > 4xMIC (64 mg/L) was not feasibly attained by any dosing regimen at recommended doses.

Conclusion

Unlike conventional piperacillin intermittent administration and extended infusion regimens, continuous infusion allows the target of 100% fT > MIC to be reached for children with febrile neutropenia.

Population pharmacokinetics of cefotaxime in intensive care patients

PURPOSE

To characterise the pharmacokinetics and associated variability of cefotaxime in adult intensive care unit (ICU) patients and to assess the impact of patient covariates.

METHODS

This work was based on data from cefotaxime-treated patients included in the ACCIS (Antibiotic Concentrations in Critical Ill ICU Patients in Sweden) study. Clinical data from 51 patients at seven different ICUs in Sweden, given cefotaxime (1000-3000 mg given 2-6 times daily), were collected from the first day of treatment for up to three consecutive days. In total, 263 cefotaxime samples were included in the population pharmacokinetic analysis.

RESULTS

A two-compartment model with linear elimination, proportional residual error and inter-individual variability (IIV) on clearance and central volume of distribution best described the data. The typical individual was 64 years, with body weight at ICU admission of 92 kg and estimated creatinine clearance of 94 mL/min. The resulting typical value of clearance was 11.1 L/h, central volume of distribution 5.1 L, peripheral volume of distribution 18.2 L and inter-compartmental clearance 14.5 L/h. The estimated creatinine clearance proved to be a significant covariate on clearance (p < 0.001), reducing IIV from 68 to 49%.

CONCLUSION

A population pharmacokinetic model was developed to describe cefotaxime pharmacokinetics and associated variability in adult ICU patients. The estimated creatinine clearance partly explained the IIV in cefotaxime clearance. However, the remaining unexplained IIV is high and suggests a need for dose individualisation using therapeutic drug monitoring where the developed model, after evaluation of predictive performance, may provide support.

A novel mechanism-based pharmacokinetic-pharmacodynamic (PKPD) model describing ceftazidime/avibactam efficacy against β-lactamase-producing Gram-negative bacteria

BACKGROUND

Diazabicyclooctanes (DBOs) are an increasingly important group of non β-lactam β-lactamase inhibitors, employed clinically in combinations such as ceftazidime/avibactam. The dose finding of such combinations is complicated using the traditional pharmacokinetic/pharmacodynamic (PK/PD) index approach, especially if the β-lactamase inhibitor has an antibiotic effect of its own.

OBJECTIVES

To develop a novel mechanism-based pharmacokinetic-pharmacodynamic (PKPD) model for ceftazidime/avibactam against Gram-negative pathogens, with the potential for combination dosage simulation.

METHODS

Four β-lactamase-producing Enterobacteriaceae, covering Ambler classes A, B and D, were exposed to ceftazidime and avibactam, alone and in combination, in static time-kill experiments. A PKPD model was developed and evaluated using internal and external evaluation, and combined with a population PK model and applied in dosage simulations.

RESULTS

The developed PKPD model included the effects of ceftazidime alone, avibactam alone and an 'enhancer' effect of avibactam on ceftazidime in addition to the β-lactamase inhibitory effect of avibactam. The model could describe an extensive external Pseudomonas aeruginosa data set with minor modifications to the enhancer effect, and the utility of the model for clinical dosage simulation was demonstrated by investigating the influence of the addition of avibactam.

CONCLUSIONS

A novel mechanism-based PKPD model for the DBO/β-lactam combination ceftazidime/avibactam was developed that enables future comparison of the effect of avibactam with other DBO/β-lactam inhibitors in simulations, and may be an aid in translating PKPD results from in vitro to animals and humans.

Effects of Hospital-Based Comprehensive Medication Reviews Including Postdischarge Follow-up on Older Patients' Use of Health Care: A Cluster Randomized Clinical Trial

Importance

Suboptimal use of medications is a leading cause of health care-related harm. Medication reviews improve medication use, but evidence of the possible benefit of inpatient medication review for hard clinical outcomes after discharge is scarce.

Objective

To study the effects of hospital-based comprehensive medication reviews (CMRs), including postdischarge follow-up of older patients' use of health care resources, compared with only hospital-based reviews and usual care.

Design, Setting, and Participants

The Medication Reviews Bridging Healthcare trial is a cluster randomized crossover trial that was conducted in 8 wards with multiprofessional teams at 4 hospitals in Sweden from February 6, 2017, to October 19, 2018, with 12 months of follow-up completed December 6, 2019. The study was prespecified in the trial protocol. Outcome assessors were blinded to treatment allocation. In total, 2644 patients aged 65 years or older who had been admitted to 1 of the study wards for at least 1 day were included. Data from the modified intention-to-treat population were analyzed from December 10, 2019, to September 9, 2020.

Interventions

Each ward participated in the trial for 6 consecutive 8-week periods. The wards were randomized to provide 1 of 3 treatments during each period: CMR, CMR plus postdischarge follow-up, and usual care without a clinical pharmacist.

Main Outcomes and Measures

The primary outcome measure was the incidence of unplanned hospital visits (admissions plus emergency department visits) within 12 months. Secondary outcomes included medication-related admissions, visits with primary care clinicians, time to first unplanned hospital visit, mortality, and costs of hospital-based care.

Results

Of the 2644 participants, 7 withdrew after inclusion, leaving 2637 for analysis (1357 female [51.5%]; median age, 81 [interquartile range, 74-87] years; median number of medications, 9 [interquartile range, 5-13]). In the modified intention-to-treat analysis, 922 patients received CMR, 823 received CMR plus postdischarge follow-up, and 892 received usual care. The crude incidence rate of unplanned hospital visits was 1.77 per patient-year in the total study population. The primary outcome did not differ between the intervention groups and usual care (adjusted rate ratio, 1.04 [95% CI, 0.89-1.22] for CMR and 1.15 [95% CI, 0.98-1.34] for CMR plus postdischarge follow-up). However, CMR plus postdischarge follow-up was associated with an increased incidence of emergency department visits within 12 months (adjusted rate ratio, 1.29; 95% CI, 1.05-1.59) compared with usual care. There were no differences between treatment groups regarding other secondary outcomes.

Conclusions and Relevance

In this study of older hospitalized patients, CMR plus postdischarge follow-up did not decrease the incidence of unplanned hospital visits. The findings do not support the performance of hospital-based CMRs as conducted in this trial. Alternative forms of medication reviews that aim to improve older patients' health outcomes should be considered and subjected to randomized clinical trials.

Trial Registration

ClinicalTrials.gov Identifier: NCT02986425.

From Therapeutic Drug Monitoring to Model-Informed Precision Dosing for Antibiotics

Therapeutic drug monitoring (TDM) and model-informed precision dosing (MIPD) have evolved as important tools to inform rational dosing of antibiotics in individual patients with infections. In particular, critically ill patients display altered, highly variable pharmacokinetics and often suffer from infections caused by less susceptible bacteria. Consequently, TDM has been used to individualize dosing in this patient group for many years. More recently, there has been increasing research on the use of MIPD software to streamline the TDM process, which can increase the flexibility and precision of dose individualization but also requires adequate model validation and re-evaluation of existing workflows. In parallel, new minimally invasive and noninvasive technologies such as microneedle-based sensors are being developed, which-together with MIPD software-have the potential to revolutionize how patients are dosed with antibiotics. Nonetheless, carefully designed clinical trials to evaluate the benefit of TDM and MIPD approaches are still sparse, but are critically needed to justify the implementation of TDM and MIPD in clinical practice. The present review summarizes the clinical pharmacology of antibiotics, conventional TDM and MIPD approaches, and evidence of the value of TDM/MIPD for aminoglycosides, beta-lactams, glycopeptides, and linezolid, for which precision dosing approaches have been recommended.

Population pharmacokinetics of piperacillin in febrile children receiving cancer chemotherapy: the impact of body weight and target on an optimal dosing regimen

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 > 1×MIC and 50% fT > 4×MIC) 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 15.4 L/h (70 kg) combined with high glomerular filtration rate (GFR) values indicated rapid elimination and hyperfiltration. The target of 50% fT > 4×MIC was achieved for an MIC of 4.0 mg/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 100 mg/kg/dose for q6h and q8h, respectively). Higher doses or continuous infusion were needed to achieve 100% fT > 1×MIC due to the rapid piperacillin elimination.

CONCLUSIONS

The licensed dose for children with febrile neutropenia (80 mg/kg q6h as a 30 min 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 > 1×MIC) or prolonged infusions (50% fT > 4×MIC).

Pharmacodynamics of immune response biomarkers of interest for evaluation of treatment effects in bacterial infections

This mini-review discusses the pharmacodynamics of immune-related biomarkers in the area of bacterial infectious diseases that could be of interest from a pharmacokinetic (PK) and pharmacokinetic/pharmacodynamic (PK/PD) perspective in the evaluation of treatment effects. The host response to an infection is often poorly defined both in preclinical assessments and in clinical practice when it comes to characterisation of PK and PK/PD relationships. Through population modelling, the time courses and variability of immune response variables can be quantified. Incorporation of such biomarker information into PK and PK/PD models may guide the evaluation of individual response to treatment (right antibiotic, more antibiotic, less antibiotic) and when to stop treatment. Furthermore, translation of results from preclinical systems to clinical scenarios may be improved with the incorporation of biomarker information. Potential biomarkers for these purposes are discussed and a few modelling examples are provided.

Intervention fidelity and process outcomes of medication reviews including post-discharge follow-up in older hospitalized patients: Process evaluation of the MedBridge trial

WHAT IS KNOWN AND OBJECTIVE

Drug-related problems (DRPs) are a growing healthcare burden worldwide. In an ongoing cluster-randomized controlled trial in Sweden (MedBridge), comprehensive medication reviews (CMRs) including post-discharge follow-up have been conducted in older hospitalized patients to prevent and solve DRPs. As part of a process evaluation of the MedBridge trial, this study aimed to assess the intervention fidelity and process outcomes of the trial's interventions.

METHODS

For intervention delivery, the percentage of patients that received intervention components was calculated per study group. Process outcomes, measured in about one-third of all intervention patients, included the following: the number of identified medication discrepancies, DRPs and recommendations to solve DRPs, correction rate of discrepancies, and implementation rate of recommendations.

RESULTS AND DISCUSSION

The MedBridge trial included 2637 patients (mean age: 81 years). The percentage of intervention patients (n = 1745) that received the intended intervention components was 94%-98% during admission, and 40%-81% upon and after discharge. The percentage of control patients (n = 892) that received at least one unintended intervention component was 15%. On average, 1.1 discrepancies and 2.0 DRPs were identified in 652 intervention patients. The correction and implementation rates were 79% and 73%, respectively. Stop medication was the most frequently implemented recommendation (n = 293) and 77% of the patients had at least one corrected discrepancy or implemented recommendation.

WHAT IS NEW AND CONCLUSION

The intervention fidelity within the MedBridge trial was high for CMRs during hospital stay and lower for intervention components upon and after discharge. The high prevalence of corrected discrepancies and implemented recommendations may explain potential effects of CMRs in the MedBridge trial.

Combination of polymyxin B and minocycline against multidrug-resistant Klebsiella pneumoniae: interaction quantified by pharmacokinetic/pharmacodynamic modelling from in vitro data

Lack of effective treatment for multidrug-resistant Klebsiella pneumoniae (MDR-Kp) necessitates finding and optimising combination therapies of old antibiotics. The aims of this study were to quantify the combined effect of polymyxin B and minocycline by building an in silico semi-mechanistic pharmacokinetic/pharmacodynamic (PKPD) model and to predict bacterial kinetics when exposed to the drugs alone and in combination at clinically achievable unbound drug concentration-time profiles. A clinical K. pneumoniae strain resistant to polymyxin B [minimum inhibitory concentration (MIC) = 16 mg/L] and minocycline (MIC = 16 mg/L) was selected for extensive in vitro static time-kill experiments. The strain was exposed to concentrations of 0.0625-48 × MIC, with seven samples taken per experiment for viable counts during 0-28 h. These observations allowed the development of the PKPD model. The final PKPD model included drug-induced adaptive resistance for both drugs. Both the minocycline-induced bacterial killing and resistance onset rate constants were increased when polymyxin B was co-administered, whereas polymyxin B parameters were unaffected. Predictions at clinically used dosages from the developed PKPD model showed no or limited antibacterial effect with monotherapy, whilst combination therapy kept bacteria below the starting inoculum for >20 h at high dosages [polymyxin B 2.5 mg/kg + 1.5 mg/kg every 12 h (q12h); minocycline 400 mg + 200 mg q12h, loading + maintenance doses]. This study suggests that polymyxin B and minocycline in combination may be of clinical benefit in the treatment of infections by MDR-Kp and for isolates that are non-susceptible to either drug alone.

A Cross-Sectional Study Assessing Appropriateness Of Inhaled Corticosteroid Treatment In Primary And Secondary Care Patients With COPD In Sweden

Purpose

Inhaled corticosteroids (ICS) are often more widely prescribed in the treatment of chronic obstructive pulmonary disease (COPD) than what is recommended in the guidelines. The aim of this study was to evaluate the appropriateness of ICS treatment in COPD patients using the algorithm proposed by the International Primary Care Respiratory Group (IPCRG) and to identify factors associated with ICS treatment.

Patients and methods

Appropriateness of ICS therapy was studied with respect to concomitant asthma, history of exacerbations and blood eosinophils (B-Eos) in a Swedish cohort of primary and secondary care patients with COPD. Factors associated with ICS were investigated using multivariable logistic regression.

Results

Triple treatment was found to be the most common treatment combination, used by 46% of the 561 included patients, and in total 63% were using ICS. When applying the IPCRG algorithm, there was a possible indication for discontinuation of ICS in 55% of the patients with ICS treatment. Of the patients not using ICS, 18% had an indication for starting such treatment. The strongest factors associated with ICS therapy were frequent exacerbations (aOR 8.61, 95% CI 4.06, 20.67), secondary care contacts (aOR 6.99, 95% CI 2.48, 25.28) and very severe airflow limitation (aOR 5.91, 95% CI 1.53, 26.58).

Conclusion

More than half of the COPD patients on ICS met the criteria where withdrawal of the treatment could be tried. There was, however, also a subgroup of patients not using ICS for whom there was an indication for starting ICS treatment. Patients using ICS were characterized by more frequent exacerbations and lower lung function.

Bayesian Forecasting Utilizing Bleeding Information to Support Dose Individualization of Factor VIII

Bayesian forecasting for dose individualization of prophylactic factor VIII replacement therapy using pharmacokinetic samples is challenged by large interindividual variability in the bleeding risk. A pharmacokinetic‐repeated time‐to‐event model‐based forecasting approach was developed to contrast the ability to predict the future occurrence of bleeds based on individual (i) pharmacokinetic, (ii) bleeding, and (iii) pharmacokinetic, bleeding and covariate information using observed data from the Long‐Term Efficacy Open‐Label Program in Severe Hemophilia A Disease (LEOPOLD) clinical trials (172 severe hemophilia A patients taking prophylactic treatment). The predictive performance assessed by the area under receiver operating characteristic (ROC) curves was 0.67 (95% confidence interval (CI), 0.65–0.69), 0.78 (95% CI, 0.76–0.80), and 0.79 (95% CI, 0.77–0.81) for patients ≥ 12 years when using pharmacokinetics, bleeds, and all data, respectively, suggesting that individual bleed information adds value to the optimization of prophylactic dosing regimens in severe hemophilia A. Further steps to optimize the proposed tool for factor VIII dose adaptation in the clinic are required.

Relationship between factor VIII activity, bleeds and individual characteristics in severe hemophilia A patients

Pharmacokinetic-based prophylaxis of replacement factor VIII (FVIII) products has been encouraged in recent years, but the relationship between exposure (factor VIII activity) and response (bleeding frequency) remains unclear. The aim of this study was to characterize the relationship between FVIII dose, plasma FVIII activity, and bleeding patterns and individual characteristics in severe hemophilia A patients. Pooled pharmacokinetic and bleeding data during prophylactic treatment with BAY 81-8973 (octocog alfa) were obtained from the three LEOPOLD trials. The population pharmacokinetics of FVIII activity and longitudinal bleeding frequency, as well as bleeding severity, were described using non-linear mixed effects modeling in NONMEM. In total, 183 patients [median age 22 years (range, 1-61); weight 60 kg (11-124)] contributed with 1,535 plasma FVIII activity observations, 633 bleeds and 11 patient/study characteristics [median observation period 12 months (3.1-13.1)]. A parametric repeated time-to-categorical bleed model, guided by plasma FVIII activity from a 2-compartment population pharmacokinetic model, described the time to the occurrence of bleeds and their severity. Bleeding probability decreased with time of study, and a bleed was not found to affect the time of the next bleed. Several covariate effects were identified, including the bleeding history in the 12-month pre-study period increasing the bleeding hazard. However, unexplained inter-patient variability in the phenotypic bleeding pattern remained large (111%CV). Further studies to translate the model into a tool for dose individualization that considers the individual bleeding risk are required. Research was based on a post-hoc analysis of the LEOPOLD studies registered at clinicaltrials.gov identifiers: 01029340, 01233258 and 01311648.

Piperacillin pharmacokinetics and target attainment in children with cancer and fever: Can we optimize our dosing strategy?

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 > 4× 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 > 4× 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.

Handling interoccasion variability in model-based dose individualization using therapeutic drug monitoring data

AIMS

This study aims to assess approaches to handle interoccasion variability (IOV) in a model-based therapeutic drug monitoring (TDM) context, using a population pharmacokinetic model of coagulation factor VIII as example.

METHODS

We assessed 5 model-based TDM approaches: empirical Bayes estimates (EBEs) from a model including IOV, with individualized doses calculated based on individual parameters either (i) including or (ii) excluding variability related to IOV; and EBEs from a model excluding IOV by (iii) setting IOV to zero, (iv) summing variances of interindividual variability (IIV) and IOV into a single IIV term, or (v) re-estimating the model without IOV. The impact of varying IOV magnitudes (0-50%) and number of occasions/observations was explored. The approaches were compared with conventional weight-based dosing. Predictive performance was assessed with the prediction error percentiles.

RESULTS

When IOV was lower than IIV, the accuracy was good for all approaches (50^th percentile of the prediction error [P50] <7.4%), but the precision varied substantially between IOV magnitudes (P97.5 61-528%). Approach (ii) was the most precise forecasting method across a wide range of scenarios, particularly in case of sparse sampling or high magnitudes of IOV. Weight-based dosing led to less precise predictions than the model-based TDM approaches in most scenarios.

CONCLUSIONS

Based on the studied scenarios and theoretical expectations, the best approach to handle IOV in model-based dose individualization is to include IOV in the generation of the EBEs but exclude the portion of unexplained variability related to IOV in the individual parameters used to calculate the future dose.

A non-linear mixed effect model for innate immune response: In vivo kinetics of endotoxin and its induction of the cytokines tumor necrosis factor alpha and interleukin-6

Endotoxin, a component of the outer membrane of Gram-negative bacteria, has been extensively studied as a stimulator of the innate immune response. However, the temporal aspects and exposure-response relationship of endotoxin and resulting cytokine induction and tolerance development is less well defined. The aim of this work was to establish an in silico model that simultaneously captures and connects the in vivo time-courses of endotoxin, tumor necrosis factor alpha (TNF-α), interleukin-6 (IL-6), and associated tolerance development. Data from six studies of porcine endotoxemia in anesthetized piglets (n = 116) were combined and used in the analysis, with purified endotoxin (Escherichia coli O111:B4) being infused intravenously for 1–30 h in rates of 0.063–16.0 μg/kg/h across studies. All data were modelled simultaneously by means of importance sampling in the non-linear mixed effects modelling software NONMEM. The infused endotoxin followed one-compartment disposition and non-linear elimination, and stimulated the production of TNF-α to describe the rapid increase in plasma concentration. Tolerance development, observed as declining TNF-α concentration with continued infusion of endotoxin, was also driven by endotoxin as a concentration-dependent increase in the potency parameter related to TNF-α production (EC₅₀). Production of IL-6 was stimulated by both endotoxin and TNF-α, and four consecutive transit compartments described delayed increase in plasma IL-6. A model which simultaneously account for the time-courses of endotoxin and two immune response markers, the cytokines TNF-α and IL-6, as well as the development of endotoxin tolerance, was successfully established. This model-based approach is unique in its description of the time-courses and their interrelation and may be applied within research on immune response to bacterial endotoxin, or in pre-clinical pharmaceutical research when dealing with study design or translational aspects.

The risk of febrile neutropenia in breast cancer patients following adjuvant chemotherapy is predicted by the time course of interleukin-6 and C-reactive protein by modelling

AIMS

Early identification of patients with febrile neutropenia (FN) is desirable for initiation of preventive treatment, such as with antibiotics. In this study, the time courses of two inflammation biomarkers, interleukin (IL)-6 and C-reactive protein (CRP), following adjuvant chemotherapy of breast cancer, were characterized. The potential to predict development of FN by IL-6 and CRP, and other model-derived and clinical variables, was explored.

METHODS

The IL-6 and CRP time courses in cycles 1 and 4 of breast cancer treatment were described by turnover models where the probability for an elevated production following initiation of chemotherapy was estimated. Parametric time-to-event models were developed to describe FN occurrence to assess: (i) predictors available before chemotherapy is initiated; (ii) predictors available before FN occurs; and (iii) predictors available when FN occurs.

RESULTS

The IL-6 and CRP time courses were successfully characterized with peak IL-6 typically occurring 2 days prior to CRP peak. Of all evaluated variables the CRP time course was most closely associated with the occurrence of FN. Since the CRP peak typically occurred at the time of FN diagnosis it will, however, have limited value for identifying the need for preventive treatment. The time course of IL-6 was the predictor that could best forecast FN events. Of the variables available at baseline, age was the best, although in comparison a relatively weak, predictor.

CONCLUSIONS

The developed models add quantitative knowledge about IL-6 and CRP and their relationship to the development of FN. The study suggests that IL-6 may have potential as a clinical predictor of FN if monitored during myelosuppressive chemotherapy.

Semi-mechanistic pharmacokinetic-pharmacodynamic modelling of antibiotic drug combinations

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.

IMPLICATIONS

Semi-mechanistic PKPD models allow for integration of knowledge on the interaction between antibiotics for various PK and PD profiles, and can account for associated variability within the population as well as parameter uncertainty. Decisions on suitable combination regimens can thereby be facilitated. We find the application of semi-mechanistic PKPD models to be essential for efficient development of antibiotic combination regimens that optimize bacterial killing and/or suppress resistance development.

Automated time-lapse microscopy a novel method for screening of antibiotic combination effects against multidrug-resistant Gram-negative bacteria

OBJECTIVES

Antibiotic combinations are often used for carbapenemase-producing Enterobacteriaceae (CPE) but more data are needed on the optimal selection of drugs. This study aimed to evaluate the feasibility of a novel automated method based on time-lapse microscopy (the oCelloScope, Philips BioCell A/S, Allerød, Denmark) to determine in vitro combination effects against CPE and to discuss advantages and limitations of the oCelloScope in relation to standard methods.

METHODS

Four Klebsiella pneumoniae and two Escherichia coli were exposed to colistin, meropenem, rifampin and tigecycline, alone and in combination. In the oCelloScope experiments, a background corrected absorption (BCA) value of ≤8 at 24 h was used as a primary cut-off indicating inhibition of bacterial growth. A new approach was used to determine synergy, indifference and antagonism based on the number of objects (bacteria) in the images. Static time-kill experiments were performed for comparison.

RESULTS

The time-kill experiments showed synergy with 12 of 36 regimens, most frequently with colistin plus rifampin. BCA values ≤8 consistently correlated with 24-h bacterial concentrations ≤6 log₁₀ CFU/mL. The classification of combination effects agreed with the time-kill results for 33 of 36 regimens. In three cases, the interactions could not be classified with the microscopy method because of low object counts.

CONCLUSIONS

Automated time-lapse microscopy can accurately determine the effects of antibiotic combinations. The novel method is highly efficient compared with time-kill experiments, more informative than checkerboards and can be useful to accelerate the screening for combinations active against multidrug-resistant Gram-negative bacteria.

Medication Reviews Bridging Healthcare (MedBridge): Study protocol for a pragmatic cluster-randomised crossover trial

BACKGROUND

Mismanaged prescribing and use of medication among elderly puts major pressure on current healthcare systems. Performing a medication review, a structured critical examination of a patient's medications, during hospital stay with active follow-up into primary care could optimise treatment benefit and minimise harm. However, a lack of high quality evidence inhibits widespread implementation. This manuscript describes the rationale and design of a pragmatic cluster-randomised, crossover trial to fulfil this need for evidence.

AIM

To study the effects of hospital-initiated comprehensive medication reviews, including active follow-up, on elderly patients' healthcare utilisation compared to 1) usual care and 2) solely hospital based reviews.

DESIGN

Multicentre, three-treatment, replicated, cluster-randomised, crossover trial.

SETTING

8 wards with a multidisciplinary team within 4 hospitals in 3 Swedish counties.

PARTICIPANTS

Patients aged 65years or older, admitted to one of the study wards.

EXCLUSION CRITERIA

Palliative stage; residing in other than the hospital's county; medication review within the last 30days; one-day admission.

INTERVENTIONS

1, comprehensive medication review during hospital stay; 2, same as 1 with the addition of active follow-up into primary care; 3, usual care.

PRIMARY OUTCOME MEASURE

Incidence of unplanned hospital visits during a 12-month follow-up period.

DATA COLLECTION AND ANALYSES

Extraction and collection from the counties' medical record system into a GCP compliant electronic data capture system. Intention-to-treat-analyses using hierarchical models.

RELEVANCE

This study has a high potential to show a reduction in elderly patients' morbidity, contributing to more sustainable healthcare in the long run.

Model-based prediction of myelosuppression and recovery based on frequent neutrophil monitoring

Purpose

To investigate whether a more frequent monitoring of the absolute neutrophil counts (ANC) during myelosuppressive chemotherapy, together with model-based predictions, can improve therapy management, compared to the limited clinical monitoring typically applied today.

Methods

Daily ANC in chemotherapy-treated cancer patients were simulated from a previously published population model describing docetaxel-induced myelosuppression. The simulated values were used to generate predictions of the individual ANC time-courses, given the myelosuppression model. The accuracy of the predicted ANC was evaluated under a range of conditions with reduced amount of ANC measurements.

Results

The predictions were most accurate when more data were available for generating the predictions and when making short forecasts. The inaccuracy of ANC predictions was highest around nadir, although a high sensitivity (≥90%) was demonstrated to forecast Grade 4 neutropenia before it occurred. The time for a patient to recover to baseline could be well forecasted 6 days (±1 day) before the typical value occurred on day 17.

Conclusions

Daily monitoring of the ANC, together with model-based predictions, could improve anticancer drug treatment by identifying patients at risk for severe neutropenia and predicting when the next cycle could be initiated.

Electronic supplementary material

The online version of this article (doi:10.1007/s00280-017-3366-x) contains supplementary material, which is available to authorized users.

The role of infection models and PK/PD modelling for optimising care of critically ill patients with severe infections

Critically ill patients with severe infections are at high risk of suboptimal antimicrobial dosing. The pharmacokinetics (PK) and pharmacodynamics (PD) of antimicrobials in these patients differ significantly from the patient groups from whose data the conventional dosing regimens were developed. Use of such regimens often results in inadequate antimicrobial concentrations at the site of infection and is associated with poor patient outcomes. In this article, we describe the potential of in vitro and in vivo infection models, clinical pharmacokinetic data and pharmacokinetic/pharmacodynamic models to guide the design of more effective antimicrobial dosing regimens. Individualised dosing, based on population PK models and patient factors (e.g. renal function and weight) known to influence antimicrobial PK, increases the probability of achieving therapeutic drug exposures while at the same time avoiding toxic concentrations. When therapeutic drug monitoring (TDM) is applied, early dose adaptation to the needs of the individual patient is possible. TDM is likely to be of particular importance for infected critically ill patients, where profound PK changes are present and prompt appropriate antibiotic therapy is crucial. In the light of the continued high mortality rates in critically ill patients with severe infections, a paradigm shift to refined dosing strategies for antimicrobials is warranted to enhance the probability of achieving drug concentrations that increase the likelihood of clinical success.

A whole-body physiologically based pharmacokinetic (WB-PBPK) model of ciprofloxacin: a step towards predicting bacterial killing at sites of infection

The purpose of this study was to develop a whole-body physiologically based pharmacokinetic (WB-PBPK) model for ciprofloxacin for ICU patients, based on only plasma concentration data. In a next step, tissue and organ concentration time profiles in patients were predicted using the developed model. The WB-PBPK model was built using a non-linear mixed effects approach based on data from 102 adult intensive care unit patients. Tissue to plasma distribution coefficients (Kp) were available from the literature and used as informative priors. The developed WB-PBPK model successfully characterized both the typical trends and variability of the available ciprofloxacin plasma concentration data. The WB-PBPK model was thereafter combined with a pharmacokinetic-pharmacodynamic (PKPD) model, developed based on in vitro time-kill data of ciprofloxacin and Escherichia coli to illustrate the potential of this type of approach to predict the time-course of bacterial killing at different sites of infection. The predicted unbound concentration-time profile in extracellular tissue was driving the bacterial killing in the PKPD model and the rate and extent of take-over of mutant bacteria in different tissues were explored. The bacterial killing was predicted to be most efficient in lung and kidney, which correspond well to ciprofloxacin's indications pneumonia and urinary tract infections. Furthermore, a function based on available information on bacterial killing by the immune system in vivo was incorporated. This work demonstrates the development and application of a WB-PBPK-PD model to compare killing of bacteria with different antibiotic susceptibility, of value for drug development and the optimal use of antibiotics .

Levodopa-entacapone-carbidopa intestinal gel in Parkinson's disease: A randomized crossover study

BACKGROUND

The addition of oral entacapone to levodopa-carbidopa intestinal gel treatment leads to less conversion of levodopa to 3-O-methyldopa, thereby increasing levodopa plasma concentration. The objective of this study was to compare systemic levodopa exposure of the newly developed levodopa-entacapone-carbidopa intestinal gel after a 20% dose reduction with levodopa exposure after the usual levodopa-carbidopa intestinal gel dose in a randomized crossover trial in advanced Parkinson's disease patients.

METHODS

In this 48-hour study, 11 patients treated with levodopa-carbidopa intestinal gel were randomized to a treatment sequence. Blood samples were drawn at prespecified times, and patient motor function was assessed according to the treatment response scale.

RESULTS

Systemic exposure of levodopa did not differ significantly between treatments (ratio, 1.10 [95% confidence interval, 0.951-1.17]). Treatment response scale scores did not significantly differ between treatments (P = 0.84).

CONCLUSIONS

Levodopa-entacapone-carbidopa intestinal gel allowed a lower amount of levodopa administration and was well tolerated. Long-term studies are needed to confirm the results. © 2016 International Parkinson and Movement Disorder Society.

Evaluation of automated time-lapse microscopy for assessment of in vitro activity of antibiotics

This study aimed to evaluate the potential of a new time-lapse microscopy based method (oCelloScope) to efficiently assess the in vitro antibacterial effects of antibiotics. Two E. coli and one P. aeruginosa strain were exposed to ciprofloxacin, colistin, ertapenem and meropenem in 24-h experiments. Background corrected absorption (BCA) derived from the oCelloScope was used to detect bacterial growth. The data obtained with the oCelloScope were compared with those of the automated Bioscreen C method and standard time-kill experiments and a good agreement in results was observed during 6-24h of experiments. Viable counts obtained at 1, 4, 6 and 24h during oCelloScope and Bioscreen C experiments were well correlated with the corresponding BCA and optical density (OD) data. Initial antibacterial effects during the first 6h of experiments were difficult to detect with the automated methods due to their high detection limits (approximately 10⁵CFU/mL for oCelloScope and 10⁷CFU/mL for Bioscreen C), the inability to distinguish between live and dead bacteria and early morphological changes of bacteria during exposure to ciprofloxacin, ertapenem and meropenem. Regrowth was more frequently detected in time-kill experiments, possibly related to the larger working volume with an increased risk of pre-existing or emerging resistance. In comparison with Bioscreen C, the oCelloScope provided additional information on bacterial growth dynamics in the range of 10⁵ to 10⁷CFU/mL and morphological features. In conclusion, the oCelloScope would be suitable for detection of in vitro effects of antibiotics, especially when a large number of regimens need to be tested.

A pharmacokinetic-pharmacodynamic model characterizing the emergence of resistant Escherichia coli subpopulations during ertapenem exposure

OBJECTIVES

Resistant subpopulations with reduced expression of outer membrane porins have been observed in ESBL-producing Escherichia coli during exposure to ertapenem. The aim of this work was to develop a pharmacokinetic-pharmacodynamic (PKPD) model to characterize the emergence of resistant E. coli during exposure to ertapenem and to predict bacterial killing following different dosing regimens of ertapenem.

METHODS

Data from in vitro time-kill experiments were used to develop a mechanism-based PKPD model for three E. coli strains: a native strain, an ESBL-producing strain, and an ESBL-producing strain with reduced expression of porins OmpF and OmpC. Each strain was exposed to static ertapenem concentrations (1-512 × MIC) for 24 h using starting inocula of ∼10(6) and 10(8) cfu/mL.

RESULTS

The developed PKPD model consisted of three bacterial states: susceptible growing, less susceptible non-growing, and non-susceptible non-growing bacteria. A pre-existing bacterial subpopulation was used to describe the emergence of resistance. The PKPD model adequately characterized the data of the three E. coli strains investigated. Results from predictions suggest that the conventional dosage (1 g intravenously once daily) might result in regrowth of resistant subpopulations when used to treat infection caused by ESBL-producing strains.

CONCLUSIONS

Resistant subpopulations frequently emerged in E. coli when exposed to ertapenem, supporting that the time course of emergence of resistance should be taken into consideration when selecting dosing regimens.

Population pharmacokinetics of plasma-derived factor IX: procedures for dose individualization

BACKGROUND

Population pharmacokinetic (POPPK) models describing factor IX (FIX) activity levels in plasma, in combination with individual FIX measurements, may be used to individualize dosing in the treatment of hemophilia B.

OBJECTIVES

The aim was to reevaluate a previously developed POPPK model for FIX activity and to explore the number and timing of FIX samples required in pharmacokinetic (PK) dose individualization.

METHODS

The POPPK model was reevaluated using an extended data set. Several sampling schedules, varying with respect to the timing and number of samples, were evaluated in a simulation study with relative dose errors compared between schedules. The performance of individually calculated doses was compared with commonly prescribed FIX doses with respect to the number of patients with a trough FIX activity > 0.01 U mL(-1) .

RESULTS AND CONCLUSIONS

A three-compartment PK model best described the FIX activity levels. The number and timing of samples greatly influenced imprecision in dose prediction. Schedules with single samples taken on both day 2 and day 3 were identified as being convenient schedules with an acceptable performance level. Individually calculated doses performed better with respect to patient target attainment than a fixed 40 U kg(-1) dose regardless of how many samples were available to calculate individual doses. The results of this study suggest that PK dose tailoring with limited sampling may be applicable for plasma-derived FIX products.

A pharmacokinetic-pharmacodynamic (PKPD) model based on in vitro time-kill data predicts the in vivo PK/PD index of colistin

OBJECTIVES

For antibiotics, extensive animal PKPD studies are often performed to evaluate the PK/PD driver for subsequent use when recommending dosing regimens. The aim of this work was to evaluate a PKPD model, developed based on in vitro time-kill data for colistin, in predicting the relationships between PK/PD indices and the bacterial killing previously observed in mice.

METHODS

An in silico PKPD model for Pseudomonas aeruginosa exposed to colistin was previously developed based on static in vitro time-kill data. The model was here applied to perform an in silico replication of an in vivo study where the effect of colistin on P. aeruginosa was studied in the thigh infection model. Concentration-time profiles of unbound colistin were predicted and used as input to drive the bacterial killing in the PKPD model. The predicted bacterial count at 24 h was related to each of the PK/PD indices and the results were compared with reported observations in vivo.

RESULTS

The model was found to adequately predict in vivo results from mice; both in terms of which PK/PD index best correlates to effect (fAUC/MIC) as well as the magnitude needed for a 2 log kill. The fAUC/MIC needed to achieve a 2 log reduction in bacterial counts after 24 h was here predicted to be 9 compared with 31 previously reported in vivo.

CONCLUSIONS

This study provides further support that PKPD models based on longitudinal data can be a useful tool to make drug development more efficient within the infectious diseases area.

Dynamic interaction of colistin and meropenem on a WT and a resistant strain of Pseudomonas aeruginosa as quantified in a PK/PD model

OBJECTIVES

Combination therapy can be a strategy to ensure effective bacterial killing when treating Pseudomonas aeruginosa, a Gram-negative bacterium with high potential for developing resistance. The aim of this study was to develop a pharmacokinetic/pharmacodynamic (PK/PD) model that describes the in vitro bacterial time-kill curves of colistin and meropenem alone and in combination for one WT and one meropenem-resistant strain of P. aeruginosa.

METHODS

In vitro time-kill curve experiments were conducted with a P. aeruginosa WT (ATCC 27853) (MICs: meropenem 1 mg/L; colistin 1 mg/L) and a meropenem-resistant type (ARU552) (MICs: meropenem 16 mg/L; colistin 1.5 mg/L). PK/PD models characterizing resistance were fitted to the observed bacterial counts in NONMEM. The final model was applied to predict the bacterial killing of ARU552 for different combination dosages of colistin and meropenem.

RESULTS

A model with compartments for growing and resting bacteria, where the bacterial killing by colistin reduced with continued exposure and a small fraction (0.15%) of the start inoculum was resistant to meropenem, characterized the bactericidal effect and resistance development of the two antibiotics. For a typical patient, a loading dose of colistin combined with a high dose of meropenem (2000 mg q8h) was predicted to result in a pronounced kill of the meropenem-resistant strain over 24 h.

CONCLUSIONS

The developed PK/PD model successfully described the time course of bacterial counts following exposures to colistin and meropenem, alone and in combination, for both strains, and identified a dynamic drug interaction. The study illustrates the application of a PK/PD model and supports high-dose combination therapy of colistin and meropenem to overcome meropenem resistance.

Simulation-Based Evaluation of PK/PD Indices for Meropenem Across Patient Groups and Experimental Designs

PURPOSE

Antibiotic dose predictions based on PK/PD indices rely on that the index type and magnitude is insensitive to the pharmacokinetics (PK), the dosing regimen, and bacterial susceptibility. In this work we perform simulations to challenge these assumptions for meropenem and Pseudomonas aeruginosa.

METHODS

A published murine dose fractionation study was replicated in silico. The sensitivity of the PK/PD index towards experimental design, drug susceptibility, uncertainty in MIC and different PK profiles was evaluated.

RESULTS

The previous murine study data were well replicated with fT > MIC selected as the best predictor. However, for increased dosing frequencies fAUC/MIC was found to be more predictive and the magnitude of the index was sensitive to drug susceptibility. With human PK fT > MIC and fAUC/MIC had similar predictive capacities with preference for fT > MIC when short t1/2 and fAUC/MIC when long t1/2.

CONCLUSIONS

A longitudinal PKPD model based on in vitro data successfully predicted a previous in vivo study of meropenem. The type and magnitude of the PK/PD index were sensitive to the experimental design, the MIC and the PK. Therefore, it may be preferable to perform simulations for dose selection based on an integrated PK-PKPD model rather than using a fixed PK/PD index target.

Population pharmacokinetics of daptomycin in patients affected by severe Gram-positive infections

A population pharmacokinetic analysis of daptomycin was performed based on therapeutic drug monitoring (TDM) data from 58 patients receiving doses of 4-12 mg/kg for the treatment of severe Gram-positive infections. At a daily dose of 8 mg/kg, daptomycin plasma concentrations (mean ± S.D.) were 76.9 ± 9.8 mg/L at the end of infusion and 52.7 ± 15.4 mg/L and 11.4 ± 5.4 mg/L at 0.5 h and 23 h after drug administration, respectively. The final model was a one-compartmental model with first-order elimination, with estimated clearance (CL) of 0.80 ± 0.14 L/h and a volume of distribution (V(d)) of 0.19 ± 0.05 L/kg. Creatinine clearance (CL(Cr)) was identified as having a significant influence on daptomycin CL, and a decrease in CL(Cr) of 30 mL/min from the median value (80 mL/min) was associated with a reduction of daptomycin CL from 0.80 L/h to 0.73 L/h. These results confirm that the presence of severe infection may be associated with an altered disposition of daptomycin, with an increased Vd. MICs were available in 41 patients and results showed that 38 and 31 subjects achieved AUC/MIC values associated with bacteriostatic (>400) and bactericidal effects (>800), respectively. Of note, 31 of these 41 subjects experienced a clinical improvement or were cured. Although daptomycin pharmacokinetics may be influenced by infections, effective AUC/MIC values were achieved in the majority of patients. The present model may be applied in clinical settings for a TDM routine on the basis of a sparse blood sampling protocol.

Pharmacokinetic-pharmacodynamic modeling of antibacterial drugs

Pharmacokinetic-pharmacodynamic (PKPD) modeling and simulation has evolved as an important tool for rational drug development and drug use, where developed models characterize both the typical trends in the data and quantify the variability in relationships between dose, concentration, and desired effects and side effects. In parallel, rapid emergence of antibiotic-resistant bacteria imposes new challenges on modern health care. Models that can characterize bacterial growth, bacterial killing by antibiotics and immune system, and selection of resistance can provide valuable information on the interactions between antibiotics, bacteria, and host. Simulations from developed models allow for outcome predictions of untested scenarios, improved study designs, and optimized dosing regimens. Today, much quantitative information on antibiotic PKPD is thrown away by summarizing data into variables with limited possibilities for extrapolation to different dosing regimens and study populations. In vitro studies allow for flexible study designs and valuable information on time courses of antibiotic drug action. Such experiments have formed the basis for development of a variety of PKPD models that primarily differ in how antibiotic drug exposure induces amplification of resistant bacteria. The models have shown promise for efficacy predictions in patients, but few PKPD models describe time courses of antibiotic drug effects in animals and patients. We promote more extensive use of modeling and simulation to speed up development of new antibiotics and promising antibiotic drug combinations. This review summarizes the value of PKPD modeling and provides an overview of the characteristics of available PKPD models of antibiotics based on in vitro, animal, and patient data.

Developmental pharmacokinetics of gentamicin in preterm and term neonates: population modelling of a prospective study

BACKGROUND AND OBJECTIVE

Preterm and term newborn infants show wide interindividual variability (IIV) in pharmacokinetic parameters of gentamicin. More extensive knowledge and use of predictive covariates could lead to faster attainment of therapeutic concentrations and a reduced need for concentration monitoring. This study was performed to characterize the population pharmacokinetics of gentamicin in preterm and term neonates and to identify and quantify relationships between patient characteristics and IIV. A secondary aim was to evaluate cystatin C as a marker for gentamicin clearance in this patient population.

METHODS

Data were collected in a prospective study performed in the Neonatal Intensive Care Unit at the University Children's Hospital, Uppsala, Sweden. Population pharmacokinetic modelling was performed using nonlinear mixed-effects modelling (NONMEM) software. Bodyweight was included as the primary covariate according to an allometric power model. Other evaluated covariates were age (postmenstrual age, gestational age [GA], postnatal age [PNA]), markers for renal function (serum creatinine, serum cystatin C) and concomitant medication with cefuroxime, vancomycin or indometacin. Covariate-parameter relationships were explored using a stepwise covariate model building procedure. The predictive performance of the developed model was evaluated using an independent external dataset for a similar patient population.

RESULTS

Sixty-one newborn infants (GA range 23.3-42.1 weeks, PNA range 0-45 days) were enrolled in the study. In total, 894 serum gentamicin samples were included in the analysis. The concentration-time profile was described using a three-compartment model. Gentamicin clearance increased with the GA and PNA (included in a nonlinear fashion). The GA was also identified as having a significant influence on the central volume of distribution, with a preterm neonate having a larger central volume of distribution per kilogram of bodyweight than a term neonate. Cystatin C and creatinine were not correlated with gentamicin clearance in this study population. The external dataset was well predicted by the developed model.

CONCLUSION

Bodyweight and age (GA and PNA) were found to be major factors contributing to IIV in gentamicin clearance in neonates. Based on these data, cystatin C and serum creatinine were not correlated with gentamicin clearance and therefore not likely to be predictive markers of renal function in this patient population. Based on predictions from the developed model, preterm neonates do not reach targeted peak and trough gentamicin concentrations after a standard dosage regimen of 4 mg/kg given once daily, suggesting a need for higher loading doses and prolonged dosing intervals in this patient population.