scholarly journals Daptomycin Pharmacokinetics in Adult Oncology Patients with Neutropenic Fever

2008 ◽  
Vol 53 (2) ◽  
pp. 428-434 ◽  
Author(s):  
Joseph S. Bubalo ◽  
Myrna Y. Munar ◽  
Ganesh Cherala ◽  
Brandon Hayes-Lattin ◽  
Richard Maziarz

ABSTRACT Daptomycin is the first antibacterial agent of the cyclic lipopeptides with in vitro bactericidal activity against gram-positive organisms, including vancomycin-resistant enterococci, methicillin-resistant staphylococci, and glycopeptide-resistant Staphylococcus aureus. The pharmacokinetics of daptomycin were determined in 29 adult oncology patients with neutropenic fever. Serial blood samples were drawn at 0, 0.5, 1, 2, 4, 8, 12, and 24 h after the initial intravenous infusion of 6 mg/kg of body weight daptomycin. Daptomycin total and free plasma concentrations were determined by high-pressure liquid chromatography. Concentration-time data were analyzed by noncompartmental methods. The results (presented as means ± standard deviations and ranges, unless indicated otherwise) were as follows: the maximum concentration of drug in plasma (C max) was 49.04 ± 12.42 μg/ml (range, 21.54 to 75.20 μg/ml), the 24-h plasma concentration was 6.48 ± 5.31 μg/ml (range, 1.48 to 29.26 μg/ml), the area under the concentration-time curve (AUC) from time zero to infinity was 521.37 ± 523.53 μg·h/ml (range, 164.64 to 3155.11 μg·h/ml), the volume of distribution at steady state was 0.18 ± 0.05 liters/kg (range, 0.13 to 0.36 liters/kg), the clearance was 15.04 ± 6.09 ml/h/kg (range, 1.90 to 34.76 ml/h/kg), the half-life was 11.34 ± 14.15 h (range, 5.17 to 83.92 h), the mean residence time was 15.67 ± 20.66 h (range, 7.00 to 121.73 h), and the median time to C max was 0.6 h (range, 0.5 to 2.5 h). The fraction unbound in the plasma was 0.06 ± 0.02. All patients achieved C max/MIC and AUC from time zero to 24 h (AUC0-24)/MIC ratios for a bacteriostatic effect against Streptococcus pneumoniae. Twenty-seven patients (93%) achieved a C max/MIC ratio for a bacteriostatic effect against S. aureus, and 28 patients (97%) achieved an AUC0-24/MIC ratio for a bacteriostatic effect against S. aureus. Free plasma daptomycin concentrations were above the MIC for 50 to 100% of the dosing interval in 100% of patients for S. pneumoniae and 90% of patients for S. aureus. The median time to defervescence was 3 days from the start of daptomycin therapy. In summary, a 6-mg/kg intravenous infusion of daptomycin every 24 h was effective and well tolerated in neutropenic cancer patients.

2004 ◽  
Vol 22 (12) ◽  
pp. 2445-2451 ◽  
Author(s):  
Joel M. Reid ◽  
Wenchun Qu ◽  
Stephanie L. Safgren ◽  
Matthew M. Ames ◽  
Mark D. Krailo ◽  
...  

Purpose To determine the maximum tolerated dose, toxicity, and pharmacokinetics of gemcitabine in children with refractory solid tumors. Patients and Methods Gemcitabine was given as a 30-minute infusion for 2 or 3 consecutive weeks every 4 weeks, to 42 patients aged 1 to 21 years. Doses of 1,000, 1,200 and 1,500 mg/m2 were administered for 3 weeks. Subsequently, gemcitabine was given for only 2 consecutive weeks at 1,500, 1,800, and 2,100 mg/m2. Plasma concentrations of gemcitabine and its metabolite, 2′2′-difluorodeoxyuridine, were measured in 28 patients. Results Forty patients who received 132 courses of gemcitabine were assessable for toxicity. The maximum tolerated dose of gemcitabine given weekly for 3 weeks was 1,200 mg/m2. Dose-limiting toxicity was not seen in one-third of children treated at any doses given for 2 weeks. The major toxicity was myelosuppression in three of five patients at 1,500 mg/m2 for 3 weeks, and one of seven patients at 1,800 mg/m2 for 2 weeks. Other serious adverse events were somnolence, fever and hypotension, and rash in three patients. Gemcitabine plasma concentration–time data were fit to a one- (n = 5) or two-compartment (n = 23) open model. Mean gemcitabine clearance and half-life values were 2,140 mL/min/m2 and 13.7 minutes, respectively. One patient with pancreatic cancer had a partial response. Seven patients had stable disease for 2 to 17 months. Conclusion Gemcitabine given by 30-minute infusion for 2 or 3 consecutive weeks every 4 weeks was tolerated well by children at doses of 2,100 mg/m2 and 1,200 mg/m2, respectively.


2009 ◽  
Vol 27 (15_suppl) ◽  
pp. 3048-3048 ◽  
Author(s):  
D. Kang ◽  
E. Wang ◽  
D. Wang ◽  
M. Amantea ◽  
P. Hsyu

3048 Background: Tremelimumab is a fully human monoclonal antibody targeted against CTLA4, a protein on T cells critical for regulating T-cell activities, which is under development for treatment of various cancers, including melanoma. Population PK analysis was conducted using concentration-time data from 450 pts, most with melanoma or solid tumors, enrolled in four phase I or II studies that evaluated PK, tolerability, and efficacy of single-agent tremelimumab. Methods: Tremelimumab was administered intravenously either as single dose or multiple doses every 4 or 12 weeks; doses varied between 0.01 and 15 mg/kg. PK was determined using nonlinear mixed-effect modeling implemented in NONMEM VI. Baseline characteristics, including body weight, ECOG score, age, sex, serum creatinine, AST, ALT, and bilirubin, and formulation effects were investigated as potential factors affecting PK. Tremelimumab plasma concentrations were determined using a sensitive, specific, validated ELISA assay. Results: A two-compartment linear model adequately described tremelimumab concentration-time data; an additive residual error model was employed on log-transformed data. Initial and terminal half-lives were 2.5 days and 22 days, respectively. Estimated parameter values were: 0.0109 L/hr for CL (clearance), 3.72 L for V1 (central volume of distribution), 0.0172 L/hr for Q (intercompartment clearance), and 3.31 L for V2 (peripheral volume of distribution). Females had 29.6% smaller V2 compared with males. Both CL and central V1 increased with weight. An ECOG score of ≥1 showed 20.2% increase in CL compared with a score of 0. New commercial formulation decreased CL by 18.5%. The model-predicted area under concentration-time curve value in females was 13.3% greater than males (p=0.5). None of the other covariates tested significantly affected PK. Furthermore, tremelimumab was tolerated in most pts at all doses tested. Conclusions: PK of tremelimumab were shown to be affected by weight, baseline ECOG score, and formulation. However, no effects other than weight were considered clinically significant enough to warrant treatment regimen change. Further investigation of PK-response relationships is warranted. [Table: see text]


2020 ◽  
Vol 21 (18) ◽  
pp. 1289-1297
Author(s):  
Adebanjo J Adegbola ◽  
Julius O Soyinka ◽  
Oluseye O Bolaji

Aim: We aimed to assess the effect of a functional polymorphism of CYP3A5 on lumefantrine pharmacokinetics. Patients & methods: Sixty-nine women diagnosed with malaria received standard doses of artemether–lumefantrine. Concentration–time data for lumefantrine and genotyping data were obtained for each participant. Pharmacokinetic-genotype associative relationships were assessed using linear regressions, Mann–Whitney U-test or Kruskal–Wallis statistics. Results: Average age and weight (standard deviation) of the patients were 33 (6.8) years and 59.5 (11.6) kg, respectively. CYP3A5*3 genotype associated with the log-transformed maximum concentration with the median (interquartile range) values of 8279 (6516–13,420) and 6331 (4093–8631) ng/ml (p = 0.032) among the carriers and noncarriers of CYP3A5*3, respectively. Besides, the NR1I3 c.152-1089T>C genotypes had an associative trend with the lumefantrine area under the curve (AUC0–96h) and clearance. Conclusion: CYP3A5*3 genetic variant is associated with a high maximum plasma concentration of lumefantrine. This warrants further investigations on the association between CYP3A5*3 gene variants, lumefantrine pharmacokinetics and electrophysiological effect.


2007 ◽  
Vol 52 (3) ◽  
pp. 852-857 ◽  
Author(s):  
Charles A. Peloquin ◽  
David Jamil Hadad ◽  
Lucilia Pereira Dutra Molino ◽  
Moises Palaci ◽  
W. Henry Boom ◽  
...  

ABSTRACT The objective of this study was to determine the population pharmacokinetic parameters of levofloxacin, gatifloxacin, and moxifloxacin following multiple oral doses. Twenty-nine patients with tuberculosis at the University Hospital in Vitória, Brazil, participated. Subjects received multiple doses of one drug (levofloxacin, 1,000 mg daily, or gatifloxacin or moxifloxacin, 400 mg daily) as part of a 7-day study of early bactericidal activity. Serum samples were collected over 24 h after the fifth dose and assayed using validated high-performance liquid chromatography assays. Concentration-time data were analyzed using noncompartmental, compartmental, and population methods. The three drugs were well tolerated. Levofloxacin produced the highest maximum plasma concentrations (median, 15.55 μg/ml; gatifloxacin, 4.75 μg/ml; moxifloxacin, 6.13 μg/ml), largest volume of distribution (median, 81 liters; gatifloxacin, 79 liters; moxifloxacin, 63 liters), and longest elimination half-life (median, 7.4 h; gatifloxacin, 5.0 h; moxifloxacin, 6.5 h). A one-compartment model, with or without weight as a covariate, adequately described the data. Postmodeling simulations using median population parameter estimates closely approximated the median values from the original data. Area under the concentration-time curve/MIC ratios for free drug were high. All three quinolones showed favorable pharmacokinetic and pharmacodynamic indices, with the most favorable results in this population being seen with levofloxacin at the comparative doses used.


Blood ◽  
2021 ◽  
Vol 138 (Supplement 1) ◽  
pp. 4350-4350
Author(s):  
Lu Zhang ◽  
Bill Poland ◽  
Michelle Green ◽  
Shekman Wong ◽  
J. Greg Slatter

Abstract Background: Murine double minute 2 (MDM2) is the primary negative regulator of the tumor suppressor protein, p53. Navtemadlin (KRT-232), a potent and selective, orally available MDM2 inhibitor restores p53 activity to drive apoptosis of cancer cells in TP53 WT malignancies. Navtemadlin is currently being evaluated in a phase 3 trial of patients with relapsed or refractory myelofibrosis, as well as in numerous phase 1b/2 trials in various hematologic malignancies and solid tumors. Serum macrophage inhibitor cytokine-1 (MIC-1) is a pharmacodynamic (PD) marker of p53-mediated activity in patients treated with navtemadlin (Allard et al. HemaSphere. 2020). Using pharmacokinetic (PK) and PD data from a healthy subject food effect study (Wong et al. Blood. 2020), we developed a population PK (PPK) model that characterized enterohepatic recirculation (EHR) as a half-life extending element in the PK profiles of navtemadlin and its major acyl glucuronide metabolite M1. MIC-1 PD data were incorporated into the model to quantify plasma concentration-driven MIC-1 excursions and to simulate PK and PD across time and dose in healthy subjects. Methods: PPK and PK-PD models were developed using the first-order conditional estimation with interaction (FOCE-I) method in NONMEM 7.4, with model covariates selected using a stepwise forward addition and backward elimination method based on a 5% significance level. Model quality was checked by inspecting model parameters and confidence intervals, as well as standard residual-based and simulation-based diagnostics, and prediction-corrected visual predictive checks. Navtemadlin plasma concentration and MIC-1 serum concentration-time data from the food effect study (KRT-232-105) were modeled (N=30 subjects after a single 60 mg navtemadlin dose). Candidate PPK semi-mechanistic models that described EHR with multi-compartment structures (gut, central, and peripheral compartments for navtemadlin, and central and gallbladder [GB] compartments for M1), first-order elimination, and mealtime effects on GB emptying were tested. Post hoc parameter estimates from the final PPK model were used to generate individual predicted navtemadlin plasma concentrations for the PK-PD model. Based on exploratory plots, the pharmacological mechanism of action of navtemadlin, and a bile acid recycling model (Guiastrennec et al. CPT Pharmacometrics Syst Pharmacol. 2018), an indirect response equation was selected for the MIC-1 effect compartment (Figure 1a). Results: Navtemadlin and M1 plasma concentrations, including a second peak attributed to EHR at ~8-12 h, were well described by a model with central and peripheral compartments, constant basal M1 release rate into bile (KBR BASAL), and incremental mealtime GB emptying rate (KBR MEAL, Figure 1a). Figure 1b shows simulated navtemadlin and M1 amounts in various compartments over time. Median oral clearance of navtemadlin was estimated at 36.35 L/h. Estimated median apparent oral clearance of navtemadlin in healthy subjects was higher than PPK estimates for patients with advanced solid tumors (24.9 L/h [Ma et al. Blood. 2019]). The median central and peripheral volumes of navtemadlin were 159 L and 390 L, respectively. Navtemadlin exposure was higher in healthy female subjects relative to male subjects. Between-subject variability in clearance was 31%. Typical MIC-1 maximum stimulatory effect (S max) was estimated at 6.82, close to the median maximum ratio of MIC-1 to baseline MIC-1 (7.29) in the observed data. SC 50 was estimated at 85.22 ng/mL, with a Hill coefficient of 2.02, indicating a relatively steep increase in MIC-1 serum concentration with increasing navtemadlin concentration. For both PPK and PK-PD models, diagnostic plots confirmed an adequate fit. Subjects with lower baseline MIC-1 had a larger response and reached a maximum MIC-1 concentration later. Older subjects had the largest covariate impact, with a higher MIC-1 response. Conclusion: A two-compartment PPK model with basal and incremental mealtime GB emptying rates captured concentration-time data for navtemadlin and its metabolite M1. EHR was evident and navtemadlin reabsorption following hydrolysis of biliary M1 in the intestine contributed to navtemadlin half-life. An indirect stimulatory PK-PD model effectively described the relationship between navtemadlin and MIC-1 in healthy subjects. Figure 1 Figure 1. Disclosures Zhang: Certara, Inc.: Current Employment; Milad Pharmaceutical Consulting, LLC.: Ended employment in the past 24 months. Wong: Kartos Therapeutics: Current Employment; AbbVie Biotherapeutics: Current equity holder in publicly-traded company. Slatter: Telios Pharma: Current holder of stock options in a privately-held company; Kartos Therapeutics: Current Employment, Current holder of stock options in a privately-held company; AstraZeneca: Current equity holder in publicly-traded company; Amgen: Divested equity in a private or publicly-traded company in the past 24 months. OffLabel Disclosure: Yes, navtemadlin (KRT-232) is an investigational small molecule MDM2 inhibitor.


2020 ◽  
Vol 7 (Supplement_1) ◽  
pp. S673-S673
Author(s):  
Jeffrey Pearson ◽  
Yazed S Alsowaida ◽  
B S Pharm ◽  
David W Kubiak ◽  
Mary P Kovacevic ◽  
...  

Abstract Background Current guidelines endorse area under the concentration-time curve (AUC)-based monitoring over trough-only monitoring for systemic vancomycin. Vancomycin AUC can be estimated using either Bayesian modeling software or first-order pharmacokinetic (PK) calculations. The objective of this pilot study was to evaluate and compare the efficiency and feasibility of these two approaches for calculating the estimated vancomycin AUC. Methods A single-center crossover study was conducted in four medical/surgical units at Brigham and Women’s Hospital over a 3-month time period. All adult patients who received vancomycin were included. Patients were excluded if they were receiving vancomycin for surgical prophylaxis, were on hemodialysis, if vancomycin was being dosed by level, or if vancomycin levels were never drawn. The primary endpoint was the amount of time study team members spent calculating the estimated AUC and determining regimen adjustments with Bayesian modeling compared to first-order PK calculations. Secondary endpoints included the number of vancomycin levels drawn and the percent of those drawn that were usable for AUC calculations. Results One hundred twenty-four patients received vancomycin during the study, of whom 47 met inclusion criteria. The most likely reasons for exclusion were receiving vancomycin for surgical prophylaxis (n=40) or never having vancomycin levels drawn (n=32). The median time taken to assess levels in the Bayesian arm was 9.3 minutes [interquartile range (IQR) 7.8-12.4] versus 6.8 minutes (IQR 4.8-8.0) in the 2-level PK arm (p=0.004). However, if Bayesian software is integrated into the electronic health record (EHR), the median time to assess levels was 3.8 minutes (IQR 2.3-6.8, p=0.019). In the Bayesian arm, 30 of 34 vancomycin levels (88.2%) were usable for AUC calculations, compared to 28 of 58 (48.3%) in the 2-level PK arm. Conclusion With EHR integration, the use of Bayesian software to calculate the AUC was more efficient than first-order PK calculations. Additionally, vancomycin levels were more likely to be usable in the Bayesian arm, thereby avoiding delays in estimating the vancomycin AUC. Disclosures All Authors: No reported disclosures


Author(s):  
Abby P. Douglas ◽  
Lisa Hall ◽  
Rodney S. James ◽  
Leon J. Worth ◽  
Monica A. Slavin ◽  
...  

Abstract Objectives: To compare antimicrobial prescribing practices in Australian hematology and oncology patients to noncancer acute inpatients and to identify targets for stewardship interventions. Design: Retrospective comparative analysis of a national prospectively collected database. Methods: Using data from the 2014–2018 annual Australian point-prevalence surveys of antimicrobial prescribing in hospitalized patients (ie, Hospital National Antimicrobial Prescribing Survey called Hospital NAPS), the most frequently used antimicrobials, their appropriateness, and guideline concordance were compared among hematology/bone marrow transplant (hemBMT), oncology, and noncancer inpatients in the setting of treatment of neutropenic fever and antibacterial and antifungal prophylaxis. Results: In 454 facilities, 94,226 antibiotic prescriptions for 62,607 adult inpatients (2,230 hemBMT, 1,824 oncology, and 58,553 noncancer) were analyzed. Appropriateness was high for neutropenic fever management across groups (83.4%–90.4%); however, hemBMT patients had high rates of carbapenem use (111 of 746 prescriptions, 14.9%), and 20.2% of these prescriptions were deemed inappropriate. Logistic regression demonstrated that hemBMT patients were more likely to receive appropriate antifungal prophylaxis compared to oncology and noncancer patients (adjusted OR, 5.3; P < .001 for hemBMT compared to noncancer patients). Oncology had a low rate of antifungal prophylaxis guideline compliance (67.2%), and incorrect dosage and frequency were key factors. Compared to oncology patients, hemBMT patients were more likely to receive appropriate nonsurgical antibacterial prophylaxis (aOR, 8.4; 95% CI, 5.3–13.3; P < .001). HemBMT patients were also more likely to receive appropriate nonsurgical antibacterial prophylaxis compared to noncancer patients (OR, 3.1; 95% CI, 1.9–5.0; P < .001). However, in the Australian context, the hemBMT group had higher than expected use of fluoroquinolone prophylaxis (66 of 831 prescriptions, 8%). Conclusions: This study demonstrates why separate analysis of hemBMT and oncology populations is necessary to identify specific opportunities for quality improvement in each patient group.


2020 ◽  
Vol 37 (12) ◽  
Author(s):  
Hannah Britz ◽  
Nina Hanke ◽  
Mitchell E. Taub ◽  
Ting Wang ◽  
Bhagwat Prasad ◽  
...  

Abstract Purpose To provide whole-body physiologically based pharmacokinetic (PBPK) models of the potent clinical organic anion transporter (OAT) inhibitor probenecid and the clinical OAT victim drug furosemide for their application in transporter-based drug-drug interaction (DDI) modeling. Methods PBPK models of probenecid and furosemide were developed in PK-Sim®. Drug-dependent parameters and plasma concentration-time profiles following intravenous and oral probenecid and furosemide administration were gathered from literature and used for model development. For model evaluation, plasma concentration-time profiles, areas under the plasma concentration–time curve (AUC) and peak plasma concentrations (Cmax) were predicted and compared to observed data. In addition, the models were applied to predict the outcome of clinical DDI studies. Results The developed models accurately describe the reported plasma concentrations of 27 clinical probenecid studies and of 42 studies using furosemide. Furthermore, application of these models to predict the probenecid-furosemide and probenecid-rifampicin DDIs demonstrates their good performance, with 6/7 of the predicted DDI AUC ratios and 4/5 of the predicted DDI Cmax ratios within 1.25-fold of the observed values, and all predicted DDI AUC and Cmax ratios within 2.0-fold. Conclusions Whole-body PBPK models of probenecid and furosemide were built and evaluated, providing useful tools to support the investigation of transporter mediated DDIs.


Sign in / Sign up

Export Citation Format

Share Document