A population pharmacokinetic model of trimethoprim in patients with pneumocystis pneumonia, made with parametric and nonparametric methods

External Evaluation of Two Pediatric Population Pharmacokinetics Models of Oral Trimethoprim and Sulfamethoxazole

The antibiotic combination trimethoprim (TMP)-sulfamethoxazole (SMX) has a broad spectrum of activity and is used for the treatment of numerous infections, but pediatric pharmacokinetic (PK) data are limited. We previously published population PK (popPK) models of oral TMP-SMX in pediatric patients based on sparse opportunistically collected data (POPS study) (J. Autmizguine, C. Melloni, C. P. Hornik, S. Dallefeld, et al., Antimicrob Agents Chemother 62:e01813-17, 2017, https://doi.org/10.1128/AAC.01813-17). We performed a separate PK study of oral TMP-SMX in infants and children with more-traditional PK sample collection and independently developed new popPK models of TMP-SMX using this external data set. The POPS data set and the external data set were each used to evaluate both popPK models. The external TMP model had a model and error structure identical to those of the POPS TMP model, with typical values for PK parameters within 20%. The external SMX model did not identify the covariates in the POPS SMX model as significant. The external popPK models predicted higher exposures to TMP (median overprediction of 0.13 mg/liter for the POPS data set and 0.061 mg/liter for the external data set) and SMX (median overprediction of 1.7 mg/liter and 0.90 mg/liter) than the POPS TMP (median underprediction of 0.016 mg/liter and 0.39 mg/liter) and SMX (median underprediction of 1.2 mg/liter and 14 mg/liter) models. Nonetheless, both models supported TMP-SMX dose increases in infants and young children for resistant pathogens with a MIC of 1 mg/liter, although the required dose increase based on the external model was lower. (The POPS and external studies have been registered at ClinicalTrials.gov under registration no. NCT01431326 and NCT02475876, respectively.).

Pharmacokinetics of ticarcillin-clavulanate in premature infants

Ticarcillin-clavulanate covers a broad spectrum of pathogens that are common in premature infants. In infants <30 weeks gestational age, pharmacokinetic data to guide ticarcillin-clavulanate dosing are lacking. We enrolled 15 premature infants <30 weeks gestational age, determined pharmacokinetic parameters, and performed dosing simulations to determine optimal dosing for ticarcillin-clavulanate. The infants had a median (range) postnatal age (PNA) of 18 days (6-44 days) and gestational age of 25 weeks (23-28 weeks). Clearance was lower in infants with a PNA <14 days (0.050 L/kg/h [range 0.043-0.075]) compared with a PNA ≥14-45 days (0.078 L/kg/h [0.047-0.100]), consistent with maturation of renal function. Dosing simulations determined that ticarcillin 75 mg/kg q12h (PNA <14 days) or q8h (PNA ≥ 14-45 days) achieved the target exposure for organisms with a minimum inhibitory concentration ≤16 μ/mL in >90% of simulated infants. For highly resistant organisms (minimum inhibitory concentration 32 μg/mL), increased dosing frequency or extended infusion are necessary.

Population Pharmacokinetics of Intramuscular and Intravenous Ketamine in Children

Ketamine is an N-methyl D-aspartate receptor antagonist used off-label to facilitate dissociative anesthesia in children undergoing invasive procedures. Available for both intravenous and intramuscular administration, ketamine is commonly used when vascular access is limited. Pharmacokinetic (PK) data in children are sparse, and the bioavailability of intramuscular ketamine in children is unknown. We performed 2 prospective PK studies of ketamine in children receiving either intramuscular or intravenous ketamine and combined the data to develop a pediatric population PK model using nonlinear mixed-effects methods. We applied our model by performing dosing simulations targeting plasma concentrations previously associated with analgesia (>100 ng/mL) and anesthesia awakening (750 ng/mL). A total of 113 children (50 intramuscular and 63 intravenous ketamine) with a median age of 3.3 years (range 0.02 to 17.6 years), and median weight of 14 kg (2.4 to 176.1) contributed 275 plasma samples (149 after intramuscular, 126 after intravenous ketamine). A 2-compartment model with first-order absorption following intramuscular administration and first-order elimination described the data best. Allometrically scaled weight was included in the base model for central and peripheral volume of distribution (exponent 1) and for clearance and intercompartmental clearance (exponent 0.75). Model-estimated bioavailability of intramuscular ketamine was 41%. Dosing simulations suggest that doses of 2 mg/kg intravenously and 8 mg/kg or 6 mg/kg intramuscularly, depending on age, provide adequate sedation (plasma ketamine concentrations >750 ng/mL) for procedures lasting up to 20 minutes.

Population Pharmacokinetics of Trimethoprim-Sulfamethoxazole in Infants and Children

Trimethoprim (TMP)-sulfamethoxazole (SMX) is used to treat various types of infections, including community-acquired methicillin-resistant Staphylococcus aureus (CA-MRSA) and Pneumocystis jirovecii infections in children. Pharmacokinetic (PK) data for infants and children are limited, and the optimal dosing is not known. We performed a multicenter, prospective PK study of TMP-SMX in infants and children. Separate population PK models were developed for TMP and SMX administered by the enteral route using nonlinear mixed-effects modeling. Optimal dosing was determined on the basis of the matching adult TMP exposure and attainment of the surrogate pharmacodynamic (PD) target for efficacy, a free TMP concentration above the MIC over 50% of the dosing interval. Data for a total of 153 subjects (240 samples for PK analysis) with a median postnatal age of 8 years (range, 0.1 to 20 years) contributed to the analysis for both drugs. A one-compartment model with first-order absorption and elimination characterized the TMP and SMX PK data well. Weight was included in the base model for clearance (CL/F) and volume of distribution (V/F). Both TMP and SMX CL/F increased with age. In addition, TMP and SMX CL/F were inversely related to the serum creatinine and albumin concentrations, respectively. The exposure achieved in children after oral administration of TMP-SMX at 8/40 mg/kg of body weight/day divided into administration every 12 h matched the exposure achieved in adults after administration of TMP-SMX at 320/1,600 mg/day divided into administration every 12 h and achieved the PD target for bacteria with an MIC of 0.5 mg/liter in >90% of infants and children. The exposure achieved in children after oral administration of TMP-SMX at 12/60 and 15/75 mg/kg/day divided into administration every 12 h matched the exposure achieved in adults after administration of TMP-SMX at 640/3,200 mg/day divided into administration every 12 h in subjects 6 to <21 years and 0 to <6 years of age, respectively, and was optimal for bacteria with an MIC of up to 1 mg/liter.

Population pharmacokinetic modelling of repaglinide in healthy volunteers by using Non-Parametric Adaptive Grid Algorithm

OBJECTIVE

To estimate population pharmacokinetic parameters of repaglinide in 121 healthy Malaysian volunteers.

METHODS

Each subject received 4 mg of oral repaglinide. Six blood samples were taken per individual (0, 30, 60, 120, 180 and 240 min) for repaglinide's serum concentration determination by using high-performance liquid chromatography. The parametric Iterative Two-Stage Bayesian Population Model (it2b) program followed by the Non-Parametric Adaptive Grid (npag) program was used to determine a population pharmacokinetic modelling of repaglinide.

RESULTS

Using the npag program, the mean elimination rate constant (k(el)) of repaglinide was 0.58 +/- 0.27 h and the volume of distribution (V(d)) was 23.09 +/- 9.19 L/h.

CONCLUSION

In this first report, specifically on the population pharmacokinetic modelling of repaglinide, the data generated should help us to better understand appropriate dosage-regimens for the drug.

Impact of CYP2D6 genetic polymorphism on tramadol pharmacokinetics and pharmacodynamics

BACKGROUND AND OBJECTIVE

Tramadol is metabolized by the highly polymorphic enzyme cytochrome P450 (CYP)2D6. Patients with different CYP2D6 genotypes may respond differently to tramadol in terms of pain relief and adverse events. In this study, we compare the pharmacokinetics and effects of tramadol in Malaysian patients with different genotypes to establish the pharmacokinetic-pharmacodynamic relationship of tramadol.

STUDY DESIGN AND SETTING

All patients received an intravenous dose of tramadol 100mg as their first postoperative analgesic. Blood was sampled at 0 minutes and subsequently at 15 and 30 minutes, 1, 2, 4, 8, 16, 20, and 24 hours for serum tramadol and analyzed by high-performance liquid chromatography (HPLC). Patients were genotyped for CYP2D6*1, *3, *4, *5, *9, *10, and *17 alleles and duplication of the gene by means of an allele-specific PCR. Pain was measured using the Visual Analog Scales, and adverse effects were recorded.

RESULTS

About half of the patients had the wild-type allele (CYP2D6*1), with the 'Asian'CYP2D6*10 allele accounting for most of the rest (40%). None of the genotypes predicted poor metabolism. Twenty-seven percent of the patients were intermediate metabolizers (IM) and 2.9% were ultra-rapid (UM) metabolizers; the remaining 70% were extensive metabolizers (EM). The mean total clearance (CL) predicted by the model was lower (19 L/h) and the half-life longer (5.9 hours) than those reported in Western populations. This may due to the high frequency of the CYP2D6*10 allele amongst Malaysian patients. The UM and EM groups had 2.6- and 1.3-times faster CL, respectively, than the IM. CL was 16, 18, 23, and 42 L/h while mean half-lives were 7.1, 6.8, 5.6, and 3.8 hours among the IM, EM1, EM2, and UM groups, respectively. However, the analgesic effects of tramadol were not measured adequately among the postoperative patients to establish its full therapeutic effects. There were significant differences in the adverse-effect profiles amongst the various genotype groups, with the IM group experiencing more adverse effects than the EM, and the EM having more adverse effects than the UM.

CONCLUSION

CYP2D6 activity may play an important role in determining the pharmacokinetics of tramadol and in predicting its adverse effects. If these results can be confirmed in a larger population, genotyping may be an important tool in determining the dose of tramadol.

Influence of Underlying Disease on Busulfan Disposition in Pediatric Bone Marrow Transplant Recipients: A Nonparametric Population Pharmacokinetic Study

Busulfan is an alkylating agent used in a conditioning regimen prior to bone marrow transplantation. Busulfan has a narrow therapeutic index, giving rise to major liver toxicity (veno-occlusive disease), and a wide interpatient and intrapatient pharmacokinetic variability. This report presents the results of a population pharmacokinetic analysis leading to models based on underlying diseases requiring bone marrow transplantation. One hundred children received oral busulfan-based conditioning regimens between March 1998 and February 2006. Busulfan pharmacokinetic parameter estimates (Ka, first order absorption rate constant; Vs, volume of distribution related to the body weight; and Cl/F, apparent clearance) were estimated by using the nonparametric adaptative grid (NPAG) algorithm in patients divided into four groups according to initial diagnosis: metabolic diseases, hemoglobinopathies, hematological malignancies, and immune deficiencies. Ka and Vs did no differ significantly in the four subgroups. Cl/F and areas under the plasma concentration curve were significantly different in the four groups. Cl/F was significantly higher in the hemoglobinopathies group (P = 0.002), with a mean value of 7.78 L . h, whereas the immune deficiencies group was characterized by the lowest Cl/F (3.59 L . h). Interindividual variability was shown by high interindividual parameter percent coefficients of variation (CV%) but, nevertheless, with less diversity in the population parameter distributions for Vs in the three subgroups-metabolic diseases, hemoglobinopathies, and malignant diseases-and in Cl/F for patients with hemoglobinopathies. The fit was good for busulfan concentration predictions based on Bayesian individual posterior values, with little bias and good precision. In comparison with the overall population, the only model of subgroup presenting a greater precision was patients with hemoglobinopathies (P = 0.002). Use of these more specific models of a given disease may well result in more accurate individualization of busulfan dose regimens, especially in very sparse blood sampling situations.

Population pharmacokinetic modelling of tramadol with application of the NPEM algorithms

BACKGROUND AND OBJECTIVE

Although the kinetic behaviour of tramadol has been described, the present study is the first to our knowledge, to report specifically on the population pharmacokinetic modelling of tramadol hydrochloride.

METHODS

The parametric Iterative Two-stage Bayesian Population Model (IT2B) program followed by the Non-parametric Expectation Maximization Population Model (NPEM2) program was used to determine population pharmacokinetic parameter values of tramadol in 138 postoperative orthopaedic Malaysian patients. All patients had received a 100 mg intravenous dose of tramadol, infused over 2-3 min, as their first postoperative analgesic. Blood was sampled at 0 min and subsequently at 15, 30 min, 1, 2, 4, 8, 16, 20 and 24 h for serum tramadol high-performance liquid chromatography analysis.

RESULTS AND DISCUSSION

The one-compartmental model pharmacokinetic parameters--volume of distribution (Vd), elimination rate constant (kel) and the total clearance rates (ClT)--found were: mean Vd = 167.6 +/- 63.84 L; median Vd = 161.48 L; mean kel = 0.1241 +/- 0.056 h(-1); median kel = 0.1138 h(-1); ClT = 19.57 +/- 9.51 L/h; median ClT =18.12 L/h. The interindividual coefficient of variation of ClT (48.56%) was higher than that of Vd (38.09%), indicating the presence of other possible influencing factors on tramadol's ClT such as CYP2D6 polymorphism, gender and age. Overall, NPEM2 suggested more diversity in the population than did IT2B.