Population plasma and urine pharmacokinetics and the probability of target attainment of fosfomycin in healthy male volunteers

Purpose: A population pharmacokinetic model of fosfomycin was developed in healthy volunteers after intravenous administration, and different dosing regimens were evaluated in terms of the probability of target attainment for Escherichia coli using both plasma and urinary pharmacokinetic/pharmacodynamic targets. Methods: Eight healthy men received fosfomycin as both intermittent 8 g q8h and continuous infusion 1 g/h with a loading dose of 8 g in a crossover study design. Dense sampling was conducted during both regimens. Population pharmacokinetic modelling was performed using NONMEM. Monte Carlo simulations were conducted to evaluate the Probability of Target Attainment (PTA) of different dosing regimens using bactericidal (AUC24h/MIC of 83 and 75%T&gt;MIC) and bacteriostatic (AUC24h/MIC of 25) plasma targets and bacteriostatic (AUC24h/MIC of 3994) urine target. Results: A total of 176 plasma and 86 urine samples were available for PK analysis. A two-compartment model with a urine compartment best described the data. Glomerular filtration rate (GFR) showed a significant correlation with renal clearance and was implemented in the final model. Simulation results show that the dose of 4 g q8h reached 100% of PTA using bactericidal and bacteriostatic targets for MIC up to 16 mg/L. Conclusion: For the clinical breakpoint of 32 mg/L, the standard dosing regimen (4 g q8h) might not be sufficient to reach the bactericidal target. Higher dosing of 8 g q8h as an intermittent infusion or 0.75 g/h as a continuous infusion might be required. Continuous infusion resulted in better attainment of the %T&gt;MIC target than intermittent infusion.</p

Population pharmacokinetics of dexamethasone in critically ill COVID-19 patients:Does inflammation play a role?

Purpose: The aim of this study is to design a population pharmacokinetic study to gain a deeper understanding of the pharmacokinetics of dexamethasone in critically ill COVID-19 patients in order to identify relevant covariates that can be used to personalize dosing regimens. Methods: Blood samples from critically ill patients receiving fixed-dose intravenous dexamethasone (6 mg/day) for the treatment of COVID-19 were sampled in a retrospective pilot study. The data were analyzed using Nonlinear Mixed Effects Modeling (NONMEM) software for population pharmacokinetic analysis and clinically relevant covariates were selected and evaluated. Results: A total of 51 dexamethasone samples from 18 patients were analyzed and a two-compartment model fit the data best. The mean population estimates were 2.85 L/h (inter-individual-variability 62.9%) for clearance, 15.4 L for the central volume of distribution, 12.3 L for the peripheral volume of distribution and 2.1 L/h for the inter-compartmental distribution clearance. The covariate analysis showed a significant negative correlation between dexamethasone clearance and CRP. Conclusions: Dexamethasone PK parameters in ICU COVID patients were substantially different from those from non-ICU non-COVID patients, and inflammation may play an important role in dexamethasone exposure. This finding suggests that fixed-dose dexamethasone over several days may not be appropriate for ICU COVID patients.</p

Pharmacokinetics of Haloperidol in Critically Ill Patients:Is There an Association with Inflammation?

Haloperidol is considered the first-line treatment for delirium in critically ill patients. However, clinical evidence of efficacy is lacking and no pharmacokinetic studies have been performed in intensive care unit (ICU) patients. The aim of this study was to establish a pharmacokinetic model to describe the PK in this population to improve insight into dosing. One hundred and thirty-nine samples from 22 patients were collected in a single-center study in adults with ICU delirium who were treated with low-dose intravenous haloperidol (3–6 mg per day). We conducted a population pharmacokinetic analysis using Nonlinear Mixed Effects Modelling (NONMEM). A one-compartment model best described the data. The mean population estimates were 51.7 L/h (IIV 42.1%) for clearance and 1490 L for the volume of distribution. The calculated half-life was around 22 h (12.3–29.73 h) for an average patient. A negative correlation between C-Reactive Protein (CRP) and haloperidol clearance was observed, where clearance decreased significantly with increasing CRP up to a CRP concentration of 100 mg/L. This is the first step towards haloperidol precision dosing in ICU patients and our results indicate a possible role of inflammation

Individualized dosing algorithms for tacrolimus in kidney transplant recipients:current status and unmet needs

Introduction: Tacrolimus is a potent immunosuppressive drug with many side effects including nephrotoxicity and post-transplant diabetes mellitus. To limit its toxicity, therapeutic drug monitoring (TDM) is performed. However, tacrolimus’ pharmacokinetics are highly variable within and between individuals, which complicates their clinical management. Despite TDM, many kidney transplant recipients will experience under- or overexposure to tacrolimus. Therefore, dosing algorithms have been developed to limit the time a patient is exposed to off-target concentrations. Areas Covered: Tacrolimus starting dose algorithms and models for follow-up doses developed and/or tested since 2015, encompassing both adult and pediatric populations. Literature was searched in different databases, i.e. Embase, PubMed, Web of Science, Cochrane Register, and Google Scholar, from inception to February 2023 Expert Opinion: Many algorithms have been developed, but few have been prospectively evaluated. These performed better than bodyweight-based starting doses, regarding the time a patient is exposed to off-target tacrolimus concentrations. No benefit in reduced tacrolimus toxicity has yet been observed. Most algorithms were developed from small datasets, contained only a few tacrolimus concentrations per person, and were not externally validated. Moreover, other matrices should be considered which might better correlate with tacrolimus toxicity than the whole-blood concentration, e.g. unbound plasma or intra-lymphocytic tacrolimus concentrations.</p

Population Pharmacokinetic Modelling of Intravenous Immunoglobulin Treatment in Patients with Guillain–Barré Syndrome

BACKGROUND AND OBJECTIVE: Intravenous immunoglobulin (IVIg) at a standard dosage is the treatment of choice for Guillain–Barré syndrome. The pharmacokinetics, however, is highly variable between patients, and a rapid clearance of IVIg is associated with poor recovery. We aimed to develop a model to predict the pharmacokinetics of a standard 5-day IVIg course (0.4 g/kg/day) in patients with Guillain–Barré syndrome. METHODS: Non-linear mixed-effects modelling software (NONMEM(®)) was used to construct a pharmacokinetic model based on a model-building cohort of 177 patients with Guillain–Barré syndrome, with a total of 589 sequential serum samples tested for total immunoglobulin G (IgG) levels, and evaluated on an independent validation cohort that consisted of 177 patients with Guillain–Barré syndrome with 689 sequential serum samples. RESULTS: The final two-compartment model accurately described the daily increment in serum IgG levels during a standard IVIg course; the initial rapid fall and then a gradual decline to steady-state levels thereafter. The covariates that increased IgG clearance were a more severe disease (as indicated by the Guillain–Barré syndrome disability score) and concomitant methylprednisolone treatment. When the current dosing regimen was simulated, the percentage of patients who reached a target ∆IgG > 7.3 g/L at 2 weeks decreased from 74% in mildly affected patients to only 33% in the most severely affected and mechanically ventilated patients (Guillain–Barré syndrome disability score of 5). CONCLUSIONS: This is the first population-pharmacokinetic model for standard IVIg treatment in Guillain–Barré syndrome. The model provides a new tool to predict the pharmacokinetics of alternative regimens of IVIg in Guillain–Barré syndrome to design future trials and personalise treatment. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s40262-022-01136-z

Removing the physician from the equation:Patient-controlled, home-based therapeutic drug self-monitoring of tacrolimus

The dosing of tacrolimus, which forms the backbone of immunosuppressive therapy after kidney transplantation, is complex. This is due to its variable pharmacokinetics (both between and within individual patients), narrow therapeutic index, and the severe consequences of over- and underexposure, which may cause toxicity and rejection, respectively. Tacrolimus is, therefore, routinely dosed by means of therapeutic drug monitoring (TDM). TDM is performed for as long as the transplant functions and frequent and often lifelong sampling is therefore the rule. This puts a significant burden on patients and transplant professionals and is associated with high healthcare-associated costs. Furthermore, by its very nature, TDM is reactive and has no predictive power. Finally, the current practice of TDM does not foresee in an active role for patients themselves. Rather, the physician or pharmacist prescribes the next tacrolimus dose after obtaining the concentration measurement test results. In this article, we propose a strategy of patient-controlled, home-based, self-TDM of the immunosuppressant tacrolimus after transplantation. We argue that with the combined use of population tacrolimus pharmacokinetic models, home-based sampling by means of dried blood spotting and implementation of telemedicine, this may become a feasible approach in the near future