The application of population pharmacokinetic modeling to individualized antibiotic therapy

Relationship Between Linezolid Exposure and the Typical Clinical Laboratory Safety and Bacterial Clearance in Chinese Pediatric Patients

Objectives: There have been limited studies concerning the safety and efficacy of linezolid (LZD) in children. This study aimed to evaluate the association between LZD exposure and clinical safety and efficacy in Chinese pediatric patients.

Methods: This retrospective cross-sectional study included patients ≤18 years of age who received ≥3 days of LZD treatment between 31 January 2015, and 31 December 2020. Demographic characteristics, medication information, laboratory test information, and bacterial culture results were collected from the Hospital Information System (HIS). Exposure was defined as AUC₂₄ and calculated by the non-linear mixed-effects modeling program (NONMEM), version 7.2, based on two validated population pharmacokinetic models. Binary logistic regression analyses were performed to analyze the associations between AUC₂₄ and laboratory adverse events, and receiver operating characteristic curves were used to calculate the cut-off values. Efficacy was evaluated by bacterial clearance.

Results: A total of 413 paediatric patients were included, with an LZD median (interquartile range) dose, duration, clearance and AUC₂₄ of 30.0 (28.1-31.6) mg/kg/day, 8 (4‒15) days,1.31 (1.29-1.32) L/h and 81.1 (60.6-108.7) mg/L·h, respectively. Adverse events associated with TBil, AST, ALT, PLT, hemoglobin, WBC, and neutrophil count increased during and after LZD treatment when compared with before medication (p < 0.05), and the most common adverse events were thrombocytopaenia (71/399, 17.8%) and low hemoglobin (61/401, 15.2%) during the LZD treatment. Patients with AUC₂₄ higher than 120.69 mg/L h might be associated with low hemoglobin 1–7 days after the end of the LZD treatment, and those with an AUC₂₄ higher than 92.88 mg/L∙h might be associated with thrombocytopaenia 8–15 days after the end of the LZD treatment. A total of 136 patients underwent bacterial culture both before and after LZD treatment, and the infection was cleared in 92.6% (126/136) of the patients, of whom 69.8% (88/126) had AUC₂₄/MIC values greater than 80.

Conclusion: Hematological indicators should be carefully monitored during LZD treatment, especially thrombocytopaenia and low hemoglobin, and a continuous period of monitoring after LZD withdrawal is also necessary. Since the AUC₂₄ cut-off values for laboratory adverse events were relatively low, a trade-off is necessary between the level of drug exposure required for treatment and safety, and the exposure target (AUC₂₄/MIC) in pediatric patients should be further studied, especially for patients with complications and concomitant medications.

Utilization of Pharmacokinetic/Pharmacodynamic Modeling in Pharmacoepidemiological Studies: A Systematic Review on Antiarrhythmic and Glucose-Lowering Medicines

Introduction: In human pharmacology, there are two important scientific branches: clinical pharmacology and pharmacoepidemiology. Pharmacokinetic/pharmacodynamic (PK/PD) modeling is important in preclinical studies and randomized control trials. However, it is rarely used in pharmacoepidemiological studies on the effectiveness and medication safety where the target population is heterogeneous and followed for longer periods. The objective of this literature review was to investigate how far PK/PD modeling is utilized in observational studies on glucose-lowering and antiarrhythmic drugs.

Method: A systematic literature search of MEDLINE, Embase, and Web of Science was conducted from January 2010 to 21 February 2020. To calculate the utilization of PK/PD modeling in observational studies, we followed two search strategies. In the first strategy, we screened a 1% random set from 95,672 studies on glucose-lowering and antiarrhythmic drugs on inclusion criteria. In the second strategy, we evaluated the percentage of studies in which PK/PD modeling techniques were utilized. Subsequently, we divided the total number of included studies in the second search strategy by the total number of eligible studies in the first search strategy.

Results: The comprehensive search of databases and the manual search of included references yielded a total of 29 studies included in the qualitative synthesis of our systematic review. Nearly all 29 studies had utilized a PK model, whereas only two studies developed a PD model to evaluate the effectiveness of medications. In total, 16 out of 29 studies (55.1%) used a PK/PD model in the observational setting to study effect modification. The utilization of PK/PD modeling in observational studies was calculated as 0.42%.

Conclusion: PK/PD modeling techniques were substantially underutilized in observational studies of antiarrhythmic and glucose-lowering drugs during the past decade.

Meropenem population pharmacokinetics in patients with decompensated cirrhosis and severe infections

OBJECTIVES

Meropenem pharmacokinetics (PK) may be altered in patients with cirrhosis, hampering target attainment. We aimed to describe meropenem PK in patients with decompensated cirrhosis and severe bacterial infections, identify the sources of PK variability and assess the performance of different dosing regimens to optimize the PK/pharmacodynamic (PD) target.

METHODS

Serum concentrations and covariates were obtained from patients with severe infections under meropenem treatment. A population PK analysis was performed using non-linear mixed-effects modelling and the final model was used to simulate meropenem exposure to assess the PTA.

RESULTS

Fifty-four patients were enrolled in the study. Data were best described by a one-compartment linear model. The estimated typical mean value for clearance (CL) was 8.35 L/h and the estimated volume of distribution (V) was 28.2 L. Creatinine clearance (CLCR) and MELD score significantly influenced meropenem CL, and acute-on-chronic liver failure (ACLF) significantly affected V. Monte Carlo simulations showed that a lower meropenem dose would be needed as CLCR decreases and as the MELD score increases. Patients with ACLF would have lower peak meropenem concentrations but similar steady-state concentrations compared with patients with no ACLF.

CONCLUSIONS

Our study identified two new covariates that influence meropenem PK in patients with decompensated cirrhosis in addition to CLCR: MELD score and ACLF. Dosing regimens are recommended to reach several PK/PD targets considering these clinical variables and any MIC within the susceptibility range.

Population pharmacokinetics and evaluation of the predictive performance of pharmacokinetic models in critically ill patients receiving continuous infusion meropenem: a comparison of eight pharmacokinetic models

Background

Several population pharmacokinetic (PopPK) models for meropenem dosing in ICU patients are available. It is not known to what extent these models can predict meropenem concentrations in an independent validation dataset when meropenem is infused continuously.

Patients and methods

A PopPK model was developed with concentration-time data collected from routine care of 21 ICU patients (38 samples) receiving continuous infusion meropenem. The predictability of this model and seven other published PopPK models was studied using an independent dataset that consisted of 47 ICU patients (161 samples) receiving continuous infusion meropenem. A statistical comparison of imprecision (mean square prediction error) and bias (mean prediction error) was conducted.

Results

A one-compartment model with linear elimination and creatinine clearance as a covariate of clearance best described our data. The mean ± SD parameter estimate for CL was 9.89 ± 3.71 L/h. The estimated volume of distribution was 48.1 L. The different PopPK models showed a bias in predicting serum concentrations from the validation dataset that ranged from -8.76 to 7.06 mg/L. Imprecision ranged from 9.90 to 42.1 mg/L.

Conclusions

Published PopPK models for meropenem vary considerably in their predictive performance when validated in an external dataset of ICU patients receiving continuous infusion meropenem. It is necessary to validate PopPK models in a target population before implementing them in a therapeutic drug monitoring program aimed at optimizing meropenem dosing.

Precision Dosing Priority Criteria: Drug, Disease, and Patient Population Variables

The administered dose of a drug modulates whether patients will experience optimal effectiveness, toxicity including death, or no effect at all. Dosing is particularly important for diseases and/or drugs where the drug can decrease severe morbidity or prolong life. Likewise, dosing is important where the drug can cause death or severe morbidity. Since we believe there are many examples where more precise dosing could benefit patients, it is worthwhile to consider how to prioritize drug-disease targets. One key consideration is the quality of information available from which more precise dosing recommendations can be constructed. When a new more precise dosing scheme is created and differs significantly from the approved label, it is important to consider the level of proof necessary to either change the label and/or change clinical practice. The cost and effort needed to provide this proof should also be considered in prioritizing drug-disease precision dosing targets. Although precision dosing is being promoted and has great promise, it is underutilized in many drugs and disease states. Therefore, we believe it is important to consider how more precise dosing is going to be delivered to high priority patients in a timely manner. If better dosing schemes do not change clinical practice resulting in better patient outcomes, then what is the use? This review paper discusses variables to consider when prioritizing precision dosing candidates while highlighting key examples of precision dosing that have been successfully used to improve patient care.

Exploring the Use of C-Reactive Protein to Estimate the Pharmacodynamics of Vancomycin

BACKGROUND

C-reactive protein (CRP) pharmacodynamic (PD) models have the potential to provide adjunctive methods for predicting the individual exposure response to antimicrobial therapy. We investigated CRP PD linked to a vancomycin pharmacokinetic (PK) model using routinely collected data from noncritical care adults in secondary care.

METHODS

Patients receiving intermittent intravenous vancomycin therapy in secondary care were identified. A 2-compartment vancomycin PK model was linked to a previously described PD model describing CRP response. PK and PD parameters were estimated using a Non-Parametric Adaptive Grid technique. Exposure-response relationships were explored with vancomycin area-under-the-concentration-time-curve (AUC) and EC50 (concentration of drug that causes a half maximal effect) using the index, AUC:EC50, fitted to CRP data using a sigmoidal Emax model.

RESULTS

Twenty-nine individuals were included. Median age was 62 (21-97) years. Fifteen (52%) patients were microbiology confirmed. PK and PD models were adequately fitted (r 0.83 and 0.82, respectively). There was a wide variation observed in individual Bayesian posterior EC50 estimates (6.95-48.55 mg/L), with mean (SD) AUC:EC50 of 31.46 (29.22). AUC:EC50 was fitted to terminal CRP with AUC:EC50 >19 associated with lower CRP value at 96-120 hours of therapy (100 mg/L versus 44 mg/L; P < 0.01).

CONCLUSIONS

The use of AUC:EC50 has the potential to provide in vivo organism and host response data as an adjunct for in vitro minimum inhibitory concentration data, which is currently used as the gold standard PD index for vancomycin therapy. This index can be estimated using routinely collected clinical data. Future work must investigate the role of AUC:EC50 in a prospective cohort and explore linkage with direct patient outcomes.

Pharmacokinetic/ pharmacodynamic evaluation of anti-infective agents

Pharmacokinetic/pharmacodynamic modeling has become an extremely important tool in evaluating and optimizing anti-infective therapy. By systematically linking the pharmacokinetic and pharmacodynamic properties of the anti-infective agent, it is possible to make educated decisions about the correct drug to be used, correct dosing regimen and to estimate the probability of success with the selected dose regimen. This article gives an overview of the current pharmacokinetic/pharmacodynamic approaches for anti-infective agents and discusses their use in optimizing drug therapy.

Dose optimisation of antibiotics in children: application of pharmacokinetics/pharmacodynamics in paediatrics

The judicious use of antibiotics to combat infections in children relies upon appropriate selection of an agent, dose and duration to maximise efficacy and to minimise toxicity. Critical to dose optimisation is an understanding of the pharmacokinetics and pharmacodynamics of available drugs. Optimal dosing strategies may take advantage of pharmacokinetic/pharmacodynamic (PK/PD) principles so that antibiotic dosing can be individualised to assure effective bacterial killing in patients who have altered pharmacokinetics or who have infections with less susceptible or resistant organisms. This review will outline the fundamentals of antimicrobial pharmacokinetics/pharmacodynamics through discussion of antibacterial agents most often used in children. We aim to highlight the importance of dose optimisation in paediatrics and describe non-conventional dosing strategies that can take advantage of PK/PD principles at the bedside.

Do antibiotic residues in soils play a role in amplification and transmission of antibiotic resistant bacteria in cattle populations?

When we consider factors that contribute to the emergence, amplification, and persistence of antibiotic resistant bacteria, the conventional assumption is that antibiotic use is the primary driver in these processes and that selection occurs primarily in the patient or animal. Evidence suggests that this may not always be the case. Experimental trials show that parenteral administration of a third-generation cephalosporin (ceftiofur) in cattle has limited or short-term effects on the prevalence of ceftiofur-resistant bacteria in the gastrointestinal tract. While this response may be sufficient to explain a pattern of widespread resistance to cephalosporins, approximately two-thirds of ceftiofur metabolites are excreted in the urine raising the possibility that environmental selection plays an important additive role in the amplification and maintenance of antibiotic resistant E. coli on farms. Consequently, we present a rationale for an environmental selection hypothesis whereby excreted antibiotic residues such as ceftiofur are a significant contributor to the proliferation of antibiotic resistant bacteria in food animal systems. We also present a mathematical model of our hypothesized system as a guide for designing experiments to test this hypothesis. If supported for antibiotics such as ceftiofur, then there may be new approaches to combat the proliferation of antibiotic resistance beyond the prudent use mantra.

Pharmacokinetic-pharmacodynamic-model-guided doripenem dosing in critically ill patients

The growing number of infections caused by multidrug-resistant pathogens has prompted a more rational use of available antibiotics given the paucity of new, effective agents. Monte Carlo simulations were utilized to determine the appropriateness of several doripenem dosing regimens based on the probability of attaining the critical drug exposure metric of time that drug concentrations remain above the drug MIC (T>MIC) for 35% (and lower thresholds) of the dosing interval in >80 to 90% of the population (T>MIC 35% target). This exposure level generally correlates with in vivo efficacy for carbapenems. In patients with creatinine clearance of >50 ml/min, a 500-mg dose of doripenem infused over 1 h every 8 h is expected to be effective against bacilli with doripenem MICs of < or =1 microg/ml based on a T>MIC 35% target and MICs of < or =2 microg/ml based on lower targets. A longer, 4-hour infusion time improved target attainment in most cases, such that the T>MIC was adequate for pathogens with doripenem MICs as high as 4 microg/ml. Efficacy is expected for infections caused by pathogens with doripenem MICs of < or =2 microg/ml in patients with moderate renal impairment (creatinine clearance, 30 to 50 ml/min) who receive doripenem at 250 mg infused over 1 h every 8 h and in patients with severe impairment (creatinine clearance between 10 and 29 ml/min) who receive doripenem at 250 mg, infused over 1 h or 4 h, every 12 h. Results of pharmacokinetics/pharmacodynamics (PK/PD) modeling can guide dose optimization, thereby potentially increasing the clinical efficacy of doripenem against serious Gram-negative bacterial infections.

Functional relationship between bacterial cell density and the efficacy of antibiotics

OBJECTIVES

To determine the functional relationship between the density of bacteria and the pharmacodynamics of antibiotics, and the potential consequences of this inoculum effect on the microbiological course of antibiotic treatment of Staphylococcus aureus infections.

METHODS

In vitro time-kill, MIC estimation and antibiotic bioassay experiments were performed with S. aureus ATCC 25923 to ascertain the functional relationship between rates of kill and the MICs of six classes of antibiotics and the density of bacteria exposed. The potential consequences of the observed inoculum effects on the microbiological course of antibiotic treatment are explored with a mathematical model.

RESULTS

Modest or substantial inoculum effects on efficacy were observed for all six antibiotics studied, such as density-dependent declines in the rate and extent of antibiotic-mediated killing and increases in MIC. Although these measures of antibiotic efficacy declined with inoculum, this density effect did not increase monotonically. At higher densities, the rate of kill of ciprofloxacin and oxacillin declined with the antibiotic concentration. For daptomycin and vancomycin, much of this inoculum effect is due to density-dependent reductions in the effective concentration of the antibiotic. For the other four antibiotics, this density effect is primarily associated with a decrease in per-cell antibiotic concentration. With parameters in the range estimated, our mathematical model predicts that the course of antibiotic treatment can be affected by cell density; treatment protocols based on conventional (density-independent) MICs can fail to clear higher density infections.

CONCLUSIONS

The MICs used for pharmacokinetic/pharmacodynamic indices should be functions of the anticipated densities of the infecting population.

Continuous infusion of beta-lactams

PURPOSE OF REVIEW

Continuous infusion of beta-lactam antibiotics is becoming increasingly popular. The background and current clinical evidence are discussed. Tools to apply continuous infusion are analyzed.

RECENT FINDINGS

One randomized controlled trial in an ICU setting and two nonrandomized controlled trials have shown continuous infusion to be more beneficial than intermittent infusion. One randomized controlled trial in chronic obstructive pulmonary disorder patients, however, showed no difference between the two treatments. The stability of most beta-lactams for use during continuous infusion has been documented.

SUMMARY

Killing of bacteria by beta-lactam antibiotics is maximal at around four times the minimum inhibitory concentration in vitro. To ensure an optimal effect when treating severe infections, free unbound concentrations at or above four times the minimum inhibitory concentration should be maintained. Although continuous infusion has been demonstrated to be superior in animal studies, randomized clinical trials have failed to confirm this in humans, primarily because of suboptimal design. A better designed randomized clinical trial, set up as a pilot study, recently demonstrated a favorable outcome with continuous infusion. A major issue during continuous infusion is the stability of the antibiotic, which may limit its application. The calculation of the infusion rate necessary to obtain the desired free drug concentration is relatively straightforward.

Pharmacodynamics of non-replicating viruses, bacteriocins and lysins

The pharmacodynamics of antibiotics and many other chemotherapeutic agents is often governed by a 'multi-hit' kinetics, which requires the binding of several molecules of the therapeutic agent for the killing of their targets. In contrast, the pharmacodynamics of novel alternative therapeutic agents, such as phages and bacteriocins against bacterial infections or viruses engineered to target tumour cells, is governed by a 'single-hit' kinetics according to which the agent will kill once it is bound to its target. In addition to requiring only a single molecule for killing, these agents bind irreversibly to their targets. Here, we explore the pharmacodynamics of such 'irreversible, single-hit inhibitors' using mathematical models. We focus on agents that do not replicate, i.e. in the case of phage therapy, we deal only with non-lytic phages and in the case of cancer treatment, we restrict our analysis to replication of incompetent viruses. We study the impact of adsorption on dead cells, heterogeneity in adsorption rates and spatial compartmentalization.

A limited sampling strategy to estimate individual pharmacokinetic parameters of methotrexate in children with acute lymphoblastic leukemia

PURPOSE

The objectives of this study were to characterize the population pharmacokinetics of MTX in patients with acute lymphoblastic leukemia (ALL) with ages ranging from 2 to 16 years and to propose a limited sampling strategy to estimate individual pharmacokinetic parameters.

METHODS

Seventy-nine children were enrolled in this study; they received 1-4 courses of chemotherapy. MTX was administered at a dose of 5 g/m2. MTX population parameters were estimated from 61 patients (231 courses; age range: 2-16 years). The data were analyzed by nonlinear mixed-effect modeling with use of a two-compartment structural model. The interoccasion variability was taken into account in the model. Eighteen additional patients (70 courses) were used to evaluate the predictive performances of the Bayesian approach and to devise a limited sampling strategy.

RESULTS

The following population parameters were obtained: total clearance (CL) = 8.8 l/h (inter-individual variability: 43%), initial volume of distribution (V1) = 17.3 l (48%), k12 = 0.0225 h(-1) (41%), and k21 = 0.0629 h(-1) (24%). The inter-individual variability in the initial volume of distribution was partially explained by the fact that this parameter was weight-dependent. Intercourse variability was limited, with a mean variation of 13.2%. The protocol involving two sampling times, 24 and 48 h after the beginning of infusion, allows precise and accurate determination of individual pharmacokinetic parameters and consequently, it was possible to predict the time at which the MTX concentration reached the predicted threshold (0.2 microM) below which the administration of folinic acid could be stopped.

CONCLUSION

The results of this study combine the relationships between the pharmacokinetic parameters of MTX and patient covariates that may be useful for dose adjustment, with a convenient sampling procedure that may aid in optimizing pediatric patient care.

Limited predictability of amikacin clearance in extreme premature neonates at birth

AIM

Identify and quantify factors describing variability of amikacin clearance in preterm neonates at birth.

METHODS

Population pharmacokinetics of amikacin were estimated in a cohort of 205 extreme preterm neonates [post conception age (PCA) 27.8, SD 1.8, range 24-30 weeks; weight 1.07, SD 0.34, range 0.45-1.98 kg, postnatal age < 72 h]. Covariate analysis included weight, PCA, Apgar score, prophylactic administration of a nonsteroidal anti-inflammatory drug (NSAID) to the neonate, maternal indomethacin and betamethasone administration, and chorioamnionitis.

RESULTS

A one-compartment linear disposition model with zero order input (0.3 h i.v. infusion) and first-order elimination was used. The population parameter estimate for volume of distribution (V) was 40.2 l per 70 kg. Clearance (CL) increased from 0.486 l h(-1) per 70 kg at 24 weeks PCA to 0.940 l h(-1) per 70 kg by 30 weeks PCA. The population parameter variability (PPV) for CL and V was 0.336 and 0.451. The use of a NSAID (either aspirin or ibuprofen) in the first day of life reduced amikacin clearance by 22%. Overall 65% of the variability of CL was predictable. Weight explained 48%, PCA 15% and NSAIDs 2%.

CONCLUSIONS

Size and post-conception age are the major contributors to clearance variability in extreme premature neonates (<31 weeks PCA). The large (35% of total) unexplained variability in clearance reinforces the need for target concentration intervention to reduce variability in exposure to a safe and effective range.

Competition between plasmid-bearing and plasmid-free organisms in the host: population dynamics and antibiotic resistance

OBJECTIVE

To clarify the effects of antibiotic exposure on bacterial antibiotic resistance.

MATERIALS AND METHODS

A competitive population dynamics model for plasmid-bearing organisms and plasmid-free organisms in the host was established. The Poincaré-Bendixson theorem was used for analysis.

RESULTS

All possible results of the competition dependent on biologically meaningful parameters were obtained, which can be classified into eight categories. With the outcomes of the plasmid model, we discussed the sterilizing effect if an antibiotic was added to the host.

CONCLUSION

When antibiotic-resistant bacteria existed in a host, a higher dosage of antibiotics was needed with an increased risk of survival of plasmid-bearing organisms and greater danger of resistance to antibiotics.

Population pharmacokinetic analysis of vancomycin in patients with hematological malignancies

This study determines vancomycin (VAN) population pharmacokinetics (PK) in adult patients with hematological malignancies. VAN serum concentration data (n = 1,004) from therapeutic drug monitoring were collected retrospectively from 215 patients. A one-compartment PK model was selected. VAN pharmacokinetics population parameters were generated using the NONMEM program. A graphic approach and stepwise generalized additive modeling were used to elucidate the preliminary relationships between PK parameters and clinical covariates analyzed. Covariate selection revealed that total body weight (TBW) affected V, whereas renal function, estimated by creatinine clearance, and a diagnosis of acute myeloblastic leukemia (AML) influenced VAN clearance. We propose one general and two AML-specific models. The former was defined by CL (liters/h) = 1.08 x CL(CR(Cockcroft and Gault)) (liters/h); CV(CL) = 28.16% and V (liters) = 0.98 x TBW; CV(V) =37.15%. AML models confirmed this structure but with a higher clearance coefficient (1.17). The a priori performance of the models was evaluated in another 59 patients, and clinical suitability was confirmed. The models were fairly accurate, with more than 33% of the measured concentrations being within +/-20% of the predicted value. This therapeutic precision is twofold higher than that of a non-customized population model (16.1%). The corresponding standardized prediction errors included zero and a standard deviation close to unity. The models could be used to estimate appropriate VAN dosage guidelines, which are not clearly defined for this high-risk population. Their simple structure should allow easy implementation in clinical software and application in dosage individualization using the Bayesian approach.

Population pharmacokinetics of mycophenolic acid in kidney transplant pediatric and adolescent patients

Current data on mycophenolate mofetil (MMF) suggest that there is a pharmacokinetic/pharmacodynamic relationship between the mycophenolic acid (MPA) area under the curve (AUC) during treatment and both the risk of acute rejection and the occurrence of side effects. The aim of this study was to characterize the population pharmacokinetics of MPA in kidney transplant patients between the ages of 2 and 21 years and to propose a limited sampling strategy to estimate individual MPA AUCs. Forty-one patients received long-term oral MMF continuous therapy as part of a triple immunosuppressive regimen, which also included cyclosporine or tacrolimus (n=3) and corticosteroids. Therapy was initiated at a dose of 600 mg/m twice daily. The population parameters were calculated from an initial group of 32 patients. The data were analyzed by nonlinear mixed-effect modeling using a 2-compartment structural model with first-order absorption and a lag time. The interindividual variability in the initial volume of distribution was partially explained by the fact that this parameter was weight-dependent. Fifteen concentration-time profiles from 13 patients were used to evaluate the predictive performance of the Bayesian approach and to devise a limited sampling strategy. The protocol, involving two sampling times, 1 and 4 hours after oral administration, allows the precise and accurate determination of MPA AUCs (bias -0.9 microg.h/mL; precision 6.02 microg.h/mL). The results of this study combine the relationships between the pharmacokinetic parameters of MPA and patient covariates, which may be useful for dose adjustment, with a convenient sampling procedure that may aid in optimizing pediatric patient care.

Pharmacodynamic functions: a multiparameter approach to the design of antibiotic treatment regimens

There is a complex quantitative relationship between the concentrations of antibiotics and the growth and death rates of bacteria. Despite this complexity, in most cases only a single pharmacodynamic parameter, the MIC of the drug, is employed for the rational development of antibiotic treatment regimens. In this report, we use a mathematical model based on a Hill function-which we call the pharmacodynamic function and which is related to previously published E(max) models-to describe the relationship between the bacterial net growth rates and the concentrations of antibiotics of five different classes: ampicillin, ciprofloxacin, tetracycline, streptomycin, and rifampin. Using Escherichia coli O18:K1:H7, we illustrate how precise estimates of the four parameters of the pharmacodynamic function can be obtained from in vitro time-kill data. We show that, in addition to their respective MICs, these antibiotics differ in the values of the other pharmacodynamic parameters. Using a computer simulation of antibiotic treatment in vivo, we demonstrate that, as a consequence of differences in pharmacodynamic parameters, such as the steepness of the Hill function and the minimum bacterial net growth rate attained at high antibiotic concentrations, there can be profound differences in the microbiological efficacy of antibiotics with identical MICs. We discuss the clinical implications and limitations of these results.

Population pharmacokinetics of ciprofloxacin in pediatric and adolescent patients with acute infections

The aim of the present study was to characterize the population pharmacokinetics of ciprofloxacin in patients with and without cystic fibrosis ranging in age from 1 day to 24 years and to propose a limited sampling strategy to estimate individual pharmacokinetic parameters. Patients were divided into four groups according to the treatment schedule. They received ciprofloxacin by intravenous infusion (30 min) or by the oral route. The number of samples collected from each patient ranged from 1 to 12. The population parameters were computed for an initial group of 37 patients. The data were analyzed by nonlinear mixed-effect modeling by use of a two-compartment structural model. The interindividual variability in clearance (CL) was partially explained by a dependence on age and the patient's clinical status. In addition, a significant relationship was found between weight and the initial volume of distribution. Eighteen additional patients were used for model validation and evaluation of limited sampling strategies. When ciprofloxacin was administered intravenously, sampling at a single point (12 h after the start of infusion) allowed the precise and accurate estimation of CL and the elimination half-life, as well as the ciprofloxacin concentration at the end of the infusion. It should be noted that to take into account the presence of a lag time after oral administration, a schedule based on two sampling times of 1 and 12 h is needed. The results of this study combine relationships between ciprofloxacin pharmacokinetic parameters and patient covariates that may be useful for dose adjustment and a convenient sampling procedure that can be used for further studies.