Micafungin Population PK Analysis in Healthy and Septic Pigs: Can the Septic Porcine Model Predict the Micafungin PK in Septic Patients?

OBJECTIVES: To describe micafungin pharmacokinetic (PK) alterations of sepsis induced in piglets and to determine whether the porcine septic model is able to predict the PK of micafungin in septic patients at the plasma and peritoneal sites. METHODS: From healthy (n = 8) and septic piglet group (n = 16), total micafungin concentrations were subject to a population PK analysis using Monolix®. Data from 16 septic humans patients from others studies was used to compare micafungin PK between septic piglets and septic patients. RESULTS: Sepsis induced in piglets slightly alters the total clearance and the volume of distribution, while inter-compartment clearance is increased (from 3.88 to 5.74 L/h) as well as the penetration into peritoneal cavity (from 61 to 90%). In septic human patients, PK parameters are similar except for the Vd, which is corrected by an allometric factor based on the body weight of each species. Micafungin penetration into peritoneal cavity of humans is lower than in septic piglets (40 versus 90%). CONCLUSIONS: The sepsis induced in the porcine model alters the PK of micafungin comparable to that in humans. In addition, micafungin PK is similar between these two species at the plasma level taking into account the allometric relationship of the body weight of these species on the central volume of distribution. The porcine septic plasma model would be able to predict the micafungin PK in the septic patients. However, further studies on peritoneal penetration are necessary to characterize this inter-species difference.

A Loading Micafungin Dose in Critically Ill Patients Undergoing Continuous Venovenous Hemofiltration or Continuous Venovenous Hemodiafiltration: A Population Pharmacokinetic Analysis.

BACKGROUND: In this study, the authors aimed to compare the pharmacokinetics (PK) of micafungin in critically ill patients receiving continuous venovenous hemofiltration (CVVH, 30 mL·kg-1·h-1) with those of patients receiving equidoses of hemodiafiltration (CVVHDF, 15 mL·kg-1·h-1 + 15 mL·kg-1·h-1) and determine the optimal dosing regimen using the developed model. METHODS: Patients with septic shock undergoing continuous renal replacement therapy and receiving a conventional dose of 100 mg micafungin once daily were eligible for inclusion. Total micafungin plasma concentrations from 8 CVVH sessions and 8 CVVHDF sessions were subjected to a population PK analysis using Pmetrics. Validation of the model performance was reinforced by external validation. Monte Carlo simulations were performed considering the total ratio of free drug area under the curve (AUC) over 24 hours to the minimum inhibitory concentration (MIC) (AUC0-24/MIC) in plasma. RESULTS: The median total body weight (min-max) was 94.8 (66-138) kg. Micafungin concentrations were best described by a 2-compartmental PK model. No covariates, including continuous renal replacement therapy modality (CVVH or CVVHDF), were retained in the final model. The mean parameter estimates (SD) were 0.96 (0.32) L/h for clearance and 14.8 (5.3) L for the central compartment volume. External validation confirmed the performance of the developed PK model. Dosing simulations did not support the use of standard 100 mg daily dosing, except for Candida albicans on the second day of therapy. A loading dose of 150 mg followed by 100 mg daily reached the probability of target attainment for all C. albicans and C. glabrata, but not for C. krusei and C. parapsilosis. CONCLUSIONS: No difference was observed in micafungin PK between equidoses of CVVH and CVVHDF. A loading dose of 150 mg is required to achieve the PK/PD target for less susceptible Candida species from the first day of therapy.

Therapeutic Bayesian monitoring of sunitinib in two patients with impaired absorption or elimination.

WHAT IS KNOWN AND OBJECTIVE: Sunitinib pharmacokinetics can be influenced by the physio-pathological conditions of individual patients. Therapeutic drug monitoring (TDM) helps to optimize efficacy and reduce the risk of adverse effects. We report on the use of Bayesian analysis to optimize sunitinib blood levels. CASE SUMMARY: We describe two patients with risk of sunitinib pharmacokinetic variability due to gastrectomy and ongoing haemodialysis, respectively. TDM and Bayesian estimation allowed maintaining their sunitinib pharmacokinetic profiles within the usual limits. WHAT IS NEW AND CONCLUSION: Our analysis showed that Bayesian analysis can be successfully applied for real-time TDM to optimize sunitinib blood levels in patients with major comorbidities.

Caspofungin Population Pharmacokinetic Analysis in Plasma and Peritoneal Fluid in Septic Patients with Intra-Abdominal Infections: A Prospective Cohort Study.

OBJECTIVES: The aim of this study was to report the pharmacokinetics (PK) of caspofungin in plasma and peritoneal fluid and to identify optimal dosing strategies in septic patients with intra-abdominal infections. METHODS: Eleven patients with secondary peritonitis with septic shock received the standard dosing regimen of caspofungin. Total caspofungin plasma and peritoneal concentrations were subject to a population PK analysis using Pmetrics®. Monte Carlo simulations were performed considering the ratio of 24-h total drug exposure above the minimum inhibitory concentration (AUC24/MIC) in plasma and comparing simulated concentrations versus MIC in peritoneal fluid. RESULTS: Fat-free mass (FFM) was retained in the final model of caspofungin, reporting a total clearance (standard deviation) of 0.78 (0.17) L/h and a central volume of distribution of 9.36 (2.61) L. The peritoneal fluid/plasma ratio of caspofungin was 33% on the first day of therapy (AUC24 73.92 (21.93) and 26.03 (9.88) mg*h/L for plasma and peritoneal data, respectively). Dosing simulations supported the use of standard dosing regimens for patients with an FFM < 50 kg for the most susceptible candida species (C. albicans and C. glabrata). For higher FFM, a loading dose of 70 or 100 mg, with a maintenance dose of 70 mg, reached AUC24/MIC ratios for these species. CONCLUSIONS: There is moderate penetration of caspofungin into the peritoneal cavity (33%). For empirical treatment, a dose escalation of 100 mg loading dose on the first day is suggested for higher FFM to ensure adequate concentrations into the abdominal cavity for the most susceptible candida species.

PXR Modulates the Prostate Cancer Cell Response to Afatinib by Regulating the Expression of the Monocarboxylate Transporter SLC16A1.

Resistance to castration is a crucial issue in the treatment of metastatic prostate cancer. Kinase inhibitors (KIs) have been tested as potential alternatives, but none of them are approved yet. KIs are subject of extensive metabolism at both the hepatic and the tumor level. Here, we studied the role of PXR (Pregnane X Receptor), a master regulator of metabolism, in the resistance to KIs in a prostate cancer setting. We confirmed that PXR is expressed in prostate tumors and is more frequently detected in advanced forms of the disease. We showed that stable expression of PXR in 22Rv1 prostate cancer cells conferred a resistance to dasatinib and a higher sensitivity to erlotinib, dabrafenib, and afatinib. Higher sensitivity to afatinib was due to a ~ 2-fold increase in its intracellular accumulation and involved the SLC16A1 transporter as its pharmacological inhibition by BAY-8002 suppressed sensitization of 22Rv1 cells to afatinib and was accompanied with reduced intracellular concentration of the drug. We found that PXR could bind to the SLC16A1 promoter and induced its transcription in the presence of PXR agonists. Together, our results suggest that PXR could be a biomarker of response to kinase inhibitors in castration-resistant prostate cancers.

Association of NR1I2, CYP3A5 and ABCB1 genetic polymorphisms with variability of temsirolimus pharmacokinetics and toxicity in patients with metastatic bladder cancer.

PURPOSE: Temsirolimus is a mammalian target of rapamycin (mTOR) inhibitor that exhibits antitumor activity in renal cell carcinoma and mantle cell lymphoma. The metabolism of temsirolimus and its active metabolite sirolimus mainly depends on cytochrome P450 3A4/5 (CYP3A4/A5) and the ABCB1 transporter. Differently from sirolimus, no pharmacogenetic study on temsirolimus has been conducted. Therefore, the aim of this pilot study was to identify genetic determinants of the inter-individual variability in temsirolimus pharmacokinetics and toxicity. METHODS: Pharmacokinetic profiles were obtained for 16 patients with bladder cancer after intravenous infusion of 25 mg temsirolimus. Non-compartmental analysis was performed to calculate the pharmacokinetic parameters of temsirolimus and sirolimus, its main metabolite. The presence of single nucleotide polymorphisms (SNPs) in CYP3A5, ABCB1 and in their transcriptional regulator NR1I2 (PXR) was assessed by genotyping. Non-parametric statistical tests were used to assess associations between candidate SNPs and temsirolimus pharmacokinetics and toxicity. RESULTS: The ratio between sirolimus AUC and temsirolimus AUC was 1.6-fold higher in patients who experienced serious toxic events (p = 0.034). The frequency of adverse events was significantly higher in patients homozygous for the NR1I2-rs6785049 A allele (OR = 0.065, p = 0.04) or NR1I2-rs3814055 C allele (OR = 0.032, p = 0.006). These NR1I2 SNPs were also predictive of temsirolimus half-life and global exposure to temsirolimus and sirolimus. Finally, the effect of the ABCB1-rs1128503, ABCB1-rs2032582 and CYP3A5*3 SNPs on sirolimus pharmacokinetics was confirmed. CONCLUSIONS: Our findings suggest that SNPs of NR1I2 and its target genes CYP3A5 and ABCB1 are genetic determinants of temsirolimus pharmacokinetics and toxicity in patients with bladder cancer.