Background Limited pharmacokinetic (PK) data of metronidazole in premature infants has led to various dosing recommendations. Surrogate efficacy targets for metronidazole are ill-defined and therefore aimed to exceed minimum inhibitory concentration of organisms responsible for intra-abdominal infections. Methods We evaluated the PK of metronidazole using plasma and dried blood spot (DBS) samples from infants ≤32 weeks gestational age in an open-label, PK, multicenter (N=3) study using population PK modeling (NONMEM). Monte Carlo simulations (N=1000 virtual subjects) were used to evaluate the surrogate efficacy target. Metabolic ratios of parent and metabolite were calculated. Results Twenty-four premature infants (111 plasma and 51 DBS samples) were enrolled: median (range) gestational age at birth 25 (23–31) weeks, postnatal age 27 (1–82) days, postmenstrual age (PMA) 31 (24–39) weeks, and weight 740 (431–1466) g. Population clearance (CL, L/h/kg) was 0.038 × (PMA/30)2.45 and volume of distribution (L/kg) of 0.93. PK parameter estimates and precision were similar between plasma and DBS samples. Metabolic ratios correlated with CL. Conclusion Simulations suggested the majority of infants in the neonatal intensive care unit (>80%) would meet the surrogate efficacy target using PMA-based dosing.

Infants are therapeutic orphans. Many drugs used in infants are used “off-label”, increasing the risk of drug toxicity and suboptimal efficacy in this vulnerable population. This knowledge gap in clinical pharmacology is partly attributed to challenges associated with conducting clinical trials in infants. Consequently, there is a need for novel and efficient study designs more suited to this population. Available literature describing the use of minimal-risk approaches to characterize the pharmacokinetics (PK) of drugs in infants was critically reviewed. Population PK approach with sparse sampling was found to be well established. Other, more recent alternatives, like dried blood spots sampling, opportunistic design, and the use of non-blood matrices are promising strategies with an increasing number of applications in infants. Physiologically based pharmacokinetic modeling provides valuable insight in drug disposition but still needs more prospective validation. Increasing experience with these methods provides understanding of their strengths and limitations and will help improve the design of future PK studies in infants.

Despite metronidazole's widespread clinical use since the 1960s, the specific enzymes involved in its biotransformation have not been previously identified. Hence, in vitro studies were conducted to identify and characterize the cytochrome P450 enzymes involved in the formation of the major metabolite, 2-hydroxymetronidazole. Formation of 2-hydroxymetronidazole in human liver microsomes was consistent with biphasic, Michaelis-Menten kinetics. Although several cDNA-expressed P450 enzymes catalyzed 2-hydroxymetronidazole formation at a supratherapeutic concentration of metronidazole (2000 mM), at a "therapeutic concentration" of 100 mM only CYPs 2A6, 3A4, 3A5, and 3A7 catalyzed metronidazole 2-hydroxylation at rates substantially greater than control vector, and CYP2A6 catalyzed 2-hydroxymetronidazole formation at rates 6-fold higher than the next most active enzyme. Kinetic studies with these recombinant enzymes revealed that CYP2A6 has a K m = 289 mM which is comparable to the K m for the high-affinity (low-K m ) enzyme in human liver microsomes, whereas the K m values for the CYP3A enzymes corresponded with the low-affinity (high-K m ) component. The sample-to-sample variation in 2-hydroxymetronidazole formation correlated significantly with CYP2A6 activity (r ‡ 0.970, P < 0.001) at substrate concentrations of 100 and 300 mM. Selective chemical inhibitors of CYP2A6 inhibited metronidazole 2-hydroxylation in a concentration-dependent manner and inhibitory antibodies against CYP2A6 virtually eliminated metronidazole 2-hydroxylation (>99%). Chemical and antibody inhibitors of other P450 enzymes had little or no effect on metronidazole 2-hydroxylation. These results suggest that CYP2A6 is the primary catalyst responsible for the 2-hydroxylation of metronidazole, a reaction that may function as a marker of CYP2A6 activity both in vitro and in vivo.

No abstract

Background Population pharmacokinetic (popPK) models derived from small PK studies in neonates are often underpowered to detect clinically important characteristics that drive dosing. External validation of such models is crucial. In this study, the predictive performance of a gentamicin popPK model in neonates receiving hypothermia was evaluated. Methods A previously published gentamicin popPK model was developed in neonates with hypoxic ischemic encephalopathy undergoing hypothermia using a retrospective single-institution (UCSF) dataset. The predictive performance of this model was evaluated in an external retrospective dataset from UCSF (Validation A) and another from Duke University (Validation B). Both institutions used the same hypothermia protocol and collected similar clinical and PK data. Gentamicin dosing and samples were collected per routine care. Predictive performance was evaluated by quantifying the accuracy and precision of model predictions and using simulation-based diagnostics to detect bias in predictions. Results 41 neonates (18 Validation A, 23 Validation B) with median (range) gestational age of 40wks (33–42) and birth weight of 3.3kg (1.9–4.6) and 76 samples (55% troughs, 33% and 28% drawn at 24 and 36h post dose, respectively) were analyzed. The model adequately predicted gentamicin concentrations from the same institution (Validation A; median average fold error [AFE]=1.1 and numerical prediction distribution error [NPDE] p-value>0.05) but under-predicted concentrations from the outside institution (Validation B; median AFE=0.6 and NPDE p-value<0.05). Conclusion The model demonstrated adequate predictive performance for an external dataset in the same institution but not from an outside institution. Larger sample sizes, use of data from multiple institutions, and external evaluation in development of popPK models in neonates may improve generalizability of dosing recommendations arising from single-institution studies.

Background Acyclovir is used to treat herpes infections in preterm and term infants; however, the influence of maturation on drug disposition and dosing requirements is poorly characterized in this population. Methods We administered intravenous acyclovir to preterm and term infants <31 days postnatal age and collected plasma samples. We performed a population pharmacokinetic analysis. The primary pharmacodynamic target was acyclovir concentration ≥3 mg/L for ≥50% of the dosing interval. The final model was simulated using infant data from a clinical database. Results The analysis included 28 infants (median 30 weeks gestation). Acyclovir pharmacokinetics was described by a 1-compartment model: clearance (L/h/kg) = 0.305 × (postmenstrual age [PMA]/31.3 weeks)3.02. This equation predicts a 4.5-fold increase in clearance from 25 to 41 weeks PMA. With proposed dosing, the pharmacodynamic target was achieved in 91% of infants: 20 mg/kg every 12 hours in infants <30 weeks PMA; 20 mg/kg every 8 hours in infants 30 to <36 weeks PMA; 20 mg/kg every 6 hours in infants 36–41 weeks PMA. Conclusions Acyclovir clearance increased with infant maturation. A dosing strategy based on PMA accounted for developmental changes in acyclovir disposition to achieve the surrogate pharmacodynamic target in the majority of infants.

Introduction Childhood obesity is common and results in substantial morbidity. The most commonly prescribed drugs in obese children are antibiotics. However, physiologic changes associated with childhood obesity can alter antibiotic pharmacokinetics and optimal body size measures to guide dosing in his population are ill defined. This combination can result in therapeutic failures or drug-related toxicities. This review summarizes pharmacokinetic information for antibiotics in obese children and implications for dosing. Methods We conducted a comprehensive literature search of PubMed, EMBASE, and International Pharmaceutical Abstracts to identify pharmacokinetic studies of antimicrobial agents in obese children. We included the following search terms: obesity, pharmacokinetics, pharmacodynamics, drug toxicity, dosing, anti-infective agents, antiviral agents, and antifungal agents. Results We identified four pharmacokinetic studies of antibiotics in obese children: one for cefazolin and tobramycin, one for gentamicin, and two for vancomycin. Only the cefazolin/tobramycin trial was prospective. The drugs studied differ in their tissue and body water distribution characteristics. Two of the studies (tobramycin and gentamicin) reported pharmacokinetic differences and required dosing modifications in obese children. Discussion The lack of pharmacokinetic studies in obese children is pronounced. The scarcity of pharmacokinetic data limits the ability to predict drug disposition using drug physicochemical properties and impedes a rational approach to selection of appropriate body size measures for dosing. Given this knowledge gap, additional trials in obese children are urgently needed and is a public health concern. Conclusion Pharmacokinetic studies of antimicrobials in obese children are desperately needed to guide dosing and avoid therapeutic failures or unwanted toxicities.

Azithromycin's extensive distribution to proinflammatory cells, including peripheral blood mononuclear cells (PBMCs) and polymorphonuclear cells (PMNs), may be important to its antimicrobial and anti-inflammatory properties. The need to simultaneously predict azithromycin concentrations in whole blood (“blood”), PBMCs, and PMNs motivated this investigation. A single-dose study in 20 healthy adults was conducted, and nonlinear mixed effects modeling was used to simultaneously describe azithromycin concentrations in blood, PBMCs, and PMNs (simultaneous PK model). Data were well described by a four-compartment mamillary model. Apparent central clearance and volume of distribution estimates were 67.3 l/hour and 336 l (interindividual variability of 114 and 122%, respectively). Bootstrapping and visual predictive checks showed adequate model performance. Azithromycin concentrations in blood, PBMCs, and PMNs from external studies of healthy adults and cystic fibrosis patients were within the 5th and 95th percentiles of model simulations. This novel empirical model can be used to predict azithromycin concentrations in blood, PBMCs, and PMNs with different dosing regimens.