We developed and applied pharmacokinetic-pharmacodynamic (PK-PD) models to characterize in vitro bacterial rate of killing as a function of ceftazidime concentrations over time. For PK-PD modeling, data obtained during continuous and intermittent infusion of ceftazidime in Pseudomonas aeruginosa killing experiments with an in vitro pharmacokinetic model were used. The basic PK-PD model was a maximum-effect model which described the number of viable bacteria (N) as a function of the growth rate (lambda) and killing rate (epsilon) according to the equation dN/dt = [lambda - epsilon x [Cgamma(EC50gamma + Cgamma)]] N, where gamma is the Hill factor, C is the concentration of antibiotic, and EC50 is the concentration of antibiotic at which 50% of the maximum effect is obtained. Next, four different models with increasing complexity were analyzed by using the EDSIM program (MediWare, Groningen, The Netherlands). These models incorporated either an adaptation rate factor and a maximum number of bacteria (Nmax) factor or combinations of the two parameters. In addition, a two-population model was evaluated. Model discrimination was by Akaike's information criterion. The experimental data were best described by the model which included an Nmax term and a rate term for adaptation for a period up to 36 h. The absolute values for maximal growth rate and killing rate in this model were different from those in the original experiment, but net growth rates were comparable. It is concluded that the derived models can describe bacterial growth and killing in the presence of antibiotic concentrations mimicking human pharmacokinetics. Application of these models will eventually provide us with parameters which can be used for further dosage optimization.

Objectives The %fT > MIC of ceftazidime has been shown to correlate with microbiological outcome of Gram-negative bacteria (GNB) in preclinical studies. However, clinical data are still lacking. We explored the relationship of ceftazidime exposure and outcome in patients with nosocomial pneumonia using data from a recent randomized, double-blind Phase 3 clinical trial. Patients and methods Pharmacokinetic (PK) and demographic data from three clinical trials were used to construct a population PK model using non-linear mixed-effects modelling. Individual concentration–time curves and PK/pharmacodynamic indices were determined for individual patients. The MICs used in the analyses were the highest MICs for any GNB cultured at baseline or end of therapy. Results A two-compartment model best fit the data, with creatinine clearance as covariate on clearance and age on the central compartment. Classification and regression tree analysis showed a breakpoint value of 44.9% (P < 0.0001) for GNB in 154 patients. The Emax model showed a good fit (R² = 0.93). The benefit of adequate treatment increased from an eradication rate of 0.4848 at %fT > MIC of 0% to 0.9971 at 100%. The EC₅₀ was 46.8% and the EC₉₀ was 95.5% for %fT > MIC. Exposure correlated significantly with both microbiological and clinical outcome at test-of-cure. Conclusions We conclude that exposures to ceftazidime predict microbiological as well as clinical outcome, and the %fT > MIC required to result in a likely favourable outcome is >45% of the dosing interval. This value is similar to that observed in animal models and underscores the principle that adequate dosing can be predicted and is beneficial to patient care.

Combination therapy could be of benefit for the treatment of invasive yeast infections. However, in vitro interaction studies are relatively scarce and the interpretation of the fractional inhibitory concentration (FIC) index can be contradictory due to various definitions used; not all information on the interaction study is used in the index, and different MIC end points exist for different classes of drugs. Fitting an interaction model to the whole response surface and estimation of an interaction coefficient alpha (ICα) would overcome these objections and has the additional advantage that confidence intervals of the interaction are obtained. The efficacy of flucytosine (5FC) in combination with amphotericin B (AB) and fluconazole (FCZ) was studied against 35 yeast isolates in triplicate ( Candida albicans [ n = 9], Candida glabrata [ n = 9], Candida krusei [ n = 9], and Cryptococcus neoformans [ n = 8]) using a broth microdilution checkerboard method and measuring growth after 48 h by a spectrophotometer. The FIC index and ICα were determined, the latter by estimation from the response surface approach described by Greco et al. (W. R. Greco, G. Bravo, and J. C. Parsons, Pharmacol. Rev. 47: 331-385, 1995) by using a computer program developed for that purpose. For the 5FC-FCZ combination, the interactions determined by the ICα generally were in concordance with the interactions determined by the FIC index, but large discrepancies were found between both methods for the 5FC-AB combination. These could mainly be explained by shortcomings in the FIC approach. The in vitro interaction of 5FC-AB demonstrated variable results depending on the tested Candida isolate. In general, the 5FC-FCZ combination was antagonistic against Candida species, but for some Candida isolates synergism was found. For C. neoformans the interaction for both combinations was highly dependent on the tested isolate and the method used. Response surface approach is an alternative method for determining the interaction between antifungal agents. By using this approach, some of the problems encountered with the FIC were overcome.

Methotrexate (MTX), an antifolate, is administered at high doses to treat malignancies in children and adults. However, there is considerable interpatient variability in clearance of high‐dose (HD) MTX. Patients with delayed clearance are at an increased risk for severe nephrotoxicity and life‐threatening systemic MTX exposure. Glucarpidase is a rescue agent for severe MTX toxicity that reduces plasma MTX levels via hydrolysis of MTX into inactive metabolites, but is only indicated when MTX concentrations are > 2 SDs above the mean excretion curve specific for the given dose together with a significant creatinine increase (> 50%). Appropriate administration of glucarpidase is challenging due to the ambiguity in the labeled indication. A recent consensus guideline was published with an algorithm to provide clarity in when to administer glucarpidase, yet clinical interpretation of laboratory results that do not directly correspond to the algorithm prove to be a limitation of its use. The goal of our study was to develop a clinical decision support tool to optimize the administration of glucarpidase for patients receiving HD MTX. Here, we describe the development of a novel 3‐compartment MTX population pharmacokinetic (PK) model using 31,672 MTX plasma concentrations from 772 pediatric patients receiving HD MTX for the treatment of acute lymphoblastic leukemia and its integration into the online clinical decision support tool, MTXPK.org. This web‐based tool has the functionality to utilize individualized demographics, serum creatinine, and real‐time drug concentrations to predict the elimination profile and facilitate model‐informed administration of glucarpidase.

BAL9141, a new antimicrobial agent belonging to the class of parenteral pyrrolidinone-3-ylidenemethyl cephalosporins, is active against most gram-positive microorganisms, including methicillin-resistant variants (methicillin-resistant Staphylococcus aureus [MRSA] and methicillin-resistant Staphylococcus epidermidis [MRSE]), as well as against penicillin-resistant pneumococci (PRP) and many gram-negative microorganisms. BAL9141 is administered as the prodrug BAL5788, which is rapidly converted to BAL9141 by plasma esterases. Pharmacokinetic (PK) data obtained in a previous multiple ascending dose study were used to fit a population PK model to using the NPEM2 program, yielding PK parameter estimates and its covariance matrix for BAL9141. These estimates and matrix were used to perform Monte Carlo simulations (MCSs) and obtain unbiased target attainment rates (TARs) for various time periods during which the concentration remains above the MIC ( T _>MIC ). Assuming a T _>MIC of 40%, TARs of 100% were reached with a dose of 500 mg/liter every 12 h for pathogens with MICs of 2 mg/liter and with a dose of 750 mg/liter every 12 h for pathogens with MICs of 4 mg/liter. Because MICs are ≤2 mg/liter for most strains of MRSA, MRSE, and PRP (with some strains showing an MIC of 4 mg/liter), a dosing regimen of 750 mg every 12 h is proposed for clinical studies. The corresponding provisional breakpoint is S (susceptible) ≤ 4 mg/liter.

Growth-kill dynamics were characterized in vitro, and the parameter estimates were used to simulate bacterial growth and kill in vivo using both mouse and human pharmacokinetics. The parameter estimates obtained in vitro predicted a time above the MIC of between 35 and 38% for a static effect in mice after 24 h of treatment.