Purpose
Individualising drug dosing using model-informed precision dosing (MIPD) of beta-lactam antibiotics and ciprofloxacin has been proposed as an alternative to standard dosing to optimise ...antibiotic efficacy in critically ill patients. However, randomised clinical trials (RCT) on clinical outcomes have been lacking.
Methods
This multicentre RCT, including patients admitted to the intensive care unit (ICU) who were treated with antibiotics, was conducted in eight hospitals in the Netherlands. Patients were randomised to MIPD with dose and interval adjustments based on monitoring serum drug levels (therapeutic drug monitoring) combined with pharmacometric modelling of beta-lactam antibiotics and ciprofloxacin. The primary outcome was ICU length of stay (LOS). Secondary outcomes were ICU mortality, hospital mortality, 28-day mortality, 6-month mortality, delta sequential organ failure assessment (SOFA) score, adverse events and target attainment.
Results
In total, 388 (MIPD
n =
189; standard dosing
n =
199) patients were analysed (median age 64 IQR 55–71). We found no significant differences in ICU LOS between MIPD compared to standard dosing (10 MIPD vs 8 standard dosing; IRR = 1.16; 95% CI 0.96–1.41;
p =
0.13). There was no significant difference in target attainment before intervention at day 1 (T1) (55.6% MIPD vs 60.9% standard dosing;
p =
0.24) or at day 3 (T3) (59.5% vs 60.4%;
p =
0.84). There were no significant differences in other secondary outcomes.
Conclusions
We could not show a beneficial effect of MIPD of beta-lactam antibiotics and ciprofloxacin on ICU LOS in critically ill patients. Our data highlight the need to identify other approaches to dose optimisation.
Introduction: Tacrolimus (Tac) is the cornerstone of immunosuppressive therapy after solid organ transplantation and will probably remain so. Excluding belatacept, no new immunosuppressive drugs were ...registered for the prevention of acute rejection during the last decade. For several immunosuppressive drugs, clinical development halted because they weren't sufficiently effective or more toxic.
Areas covered: Current methods of monitoring Tac treatment, focusing on traditional therapeutic drug monitoring (TDM), controversies surrounding TDM, novel matrices, pharmacogenetic and pharmacodynamic monitoring are discussed.
Expert opinion: Due to a narrow therapeutic index and large interpatient pharmacokinetic variability, TDM has been implemented for individualization of Tac dose to maintain drug efficacy and minimize the consequences of overexposure. The relationship between predose concentrations and the occurrence of rejection or toxicity is controversial. Acute cellular rejection also occurs when the Tac concentration is within the target range, suggesting that Tac whole blood concentrations don't necessarily correlate with pharmacological effect. Intracellular Tac, the unbound fraction of Tac or pharmacodynamic monitoring could be better biomarkers/tools for adequate Tac exposure - research into this has been promising. Traditional TDM, perhaps following pre-emptive genotyping for Tac-metabolizing enzymes, must suffice for a few years before these strategies can be implemented in clinical practice.
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Because of increasing antimicrobial resistance and the shortage of new antibiotics, there is a growing need to optimize the use of old and new antibiotics. Modelling of the ...pharmacokinetic/pharmacodynamic (PK/PD) characteristics of antibiotics can support the optimization of dosing regimens. Antimicrobial efficacy is determined by susceptibility of the drug to the microorganism and exposure to the drug, which relies on the PK and the dose. Population PK models describe relationships between patients characteristics and drug exposure. This article highlights three clinical applications of these models applied to antibiotics: 1) dosing evaluation of old antibiotics, 2) setting clinical breakpoints and 3) dosing individualization using therapeutic drug monitoring (TDM). For each clinical application, challenges regarding interpretation are discussed. An important challenge is to improve the understanding of the interpretation of modelling results for good implementation of the dosing recommendations, clinical breakpoints and TDM advices. Therefore, also background information on PK/PD principles and approaches to analyse PK/PD data are provided.
Personalized medicine is currently hampered by the lack of flexible drug formulations. Especially for pediatric patients, manual compounding of personalized drug formulations by pharmacists is ...required. Three‐Dimensional (3D) printing of medicines, which enables small‐scale manufacturing at the point‐of‐care, can fulfill this unmet clinical need. This study investigates the feasibility of developing a 3D‐printed tablet formulation at the point‐of‐care which complies to quality requirements for clinical practice, including bioequivalence. Development, manufacturing, and quality control of the 3D‐printed tablets was performed at the manufacturing facility and laboratory of the department of Clinical Pharmacy and Toxicology at Leiden University Medical Center. Sildenafil was used as a model drug for the tablet formulation. Along with the 3D‐printed tablets a randomized, an open‐label, 2‐period, crossover, single‐dose clinical trial to assess bioequivalence was performed in healthy adults. Bioequivalence was established if areas under the plasma concentration curve from administration to the time of the last quantifiable concentration (AUC0‐t) and maximum plasma concentration (Cmax) ratios were within the limits of 80.00–125.00%. The manufacturing process provided reproducible 3D‐printed tablets that adhered to quality control requirements and were consequently used in the clinical trial. The clinical trial was conducted in 12 healthy volunteers. The 90% confidence intervals (CIs) of both AUC0‐t and Cmax ratios were within bioequivalence limits (AUC0‐t 90% CI: 87.28–104.14; Cmax 90% CI: 80.23–109.58). For the first time, we demonstrate the development of a 3D‐printed tablet formulation at the point‐of‐care that is bioequivalent to its marketed originator. The 3D printing of personalized formulations is a disruptive technology for compounding, bridging the gap toward personalized medicine.
Background
Multiple clinical, demographic, and genetic factors affect the pharmacokinetics of tacrolimus in children, yet in daily practice, a uniform body-weight based starting dose is used. It can ...take weeks to reach the target tacrolimus pre-dose concentration.
Objectives
The objectives of this study were to determine the pharmacokinetics of tacrolimus immediately after kidney transplantation and to find relevant parameters for dose individualization using a population pharmacokinetic analysis.
Methods
A total of 722 blood samples were collected from 46 children treated with tacrolimus over the first 6 weeks after renal transplantation. Non-linear mixed-effects modeling (NONMEM
®
) was used to develop a population pharmacokinetic model and perform a covariate analysis. Simulations were performed to determine the optimal starting dose and to develop dosing guidelines.
Results
The data were accurately described by a two-compartment model with allometric scaling for bodyweight. Mean tacrolimus apparent clearance was 50.5 L/h, with an inter-patient variability of 25%. Higher bodyweight, lower estimated glomerular filtration rate, and higher hematocrit levels resulted in lower total tacrolimus clearance. Cytochrome P450 3A5 expressers and recipients who received a kidney from a deceased donor had a significantly higher tacrolimus clearance. The model was successfully externally validated. In total, these covariates explained 41% of the variability in clearance. From the significant covariates, the cytochrome P450 3A5 genotype, bodyweight, and donor type were useful to adjust the starting dose to reach the target pre-dose concentration. Dosing guidelines range from 0.27 to 1.33 mg/kg/day.
Conclusion
During the first 6 weeks after transplantation, the tacrolimus weight-normalized starting dose should be higher in pediatric kidney transplant recipients with a lower bodyweight, those who express the cytochrome P450 3A5 genotype, and those who receive a kidney from a deceased donor.
To describe the population pharmacokinetics of oral amoxicillin and to compare the PTA of current dosing regimens.
Two groups, each with 14 healthy male volunteers, received oral ...amoxicillin/clavulanic acid tablets on two separate days 1 week apart. One group received 875/125 mg twice daily and 500/125 mg three times daily and the other group 500/125 mg twice daily and 250/125 mg three times daily. A total of 1428 amoxicillin blood samples were collected before and after administration. We analysed the concentration-time profiles using a non-compartmental pharmacokinetic method (PKSolver) and a population pharmacokinetic method (NONMEM). The PTA was computed using Monte Carlo simulations for several dosing regimens.
AUC0-24 and Cmax increased non-linearly with dose. The final model included the following components: Savic's transit compartment model, Michaelis-Menten absorption, two distribution compartments and first-order elimination. The mean central volume of distribution was 27.7 L and mean clearance was 21.3 L/h. We included variability for the central volume of distribution (34.4%), clearance (25.8%), transit compartment model parameters and Michaelis-Menten absorption parameters. For 40% fT>MIC and >97.5% PTA, the breakpoints were 0.125 mg/L (500 mg twice daily), 0.25 mg/L (250 mg three times daily and 875 mg twice daily), 0.5 mg/L (500 mg three times daily) and 1 mg/L (750, 875 or 1000 mg three times daily and 500 mg four times daily).
The amoxicillin absorption rate appears to be saturable. The PTAs of high-dose as well as twice-daily regimens are less favourable than regimens with lower doses and higher frequency.
Purpose
We developed a pharmacokinetic model of intravenous sildenafil in newborns with congenital diaphragmatic hernia (CDH) to achieve a target plasma concentration of over 50 μg/l.
Methods
...Twenty-three CDH newborns with pulmonary hypertension (64 blood samples) received intravenous sildenafil. Patients received a loading dose of 0.35 mg/kg (IQR 0.16 mg/kg) for 3 h, followed by a continuous infusion of 1.5 mg/kg/day (IQR 0.1 mg/kg/day). For model development, non-linear mixed modeling was used. Inter-individual variability (IIV) and inter-occasion variability were tested. Demographic and laboratory parameters were evaluated as covariates. Normalized prediction distribution errors (NPDE) and visual predictive check (VPC) were used for model validation.
Results
A two-compartment disposition model of sildenafil and a one-compartment disposition model of desmethyl sildenafil (DMS) was observed with IIV in sildenafil and DMS clearance and volume of distribution of sildenafil. NPDE and VPC revealed adequate predictability. Only postnatal age increased sildenafil clearance. This was partly compensated by a higher DMS concentration, which also has a therapeutic effect. In this small group of patients, sildenafil was tolerated well.
Conclusions
This model for sildenafil in CDH patients shows that concentration-targeted sildenafil dosing of 0.4 mg/kg in 3 h, followed by 1.6 mg/kg/day continuous infusion achieves appropriate sildenafil plasma levels.
Aims
Tacrolimus is a critical dose drug and to avoid under‐ and overexposure, therapeutic drug monitoring is standard practice. However, rejection and drug‐related toxicity occur despite whole‐blood ...tacrolimus pre‐dose concentrations (Tacblood) being on target. Monitoring tacrolimus concentrations at the target site (within peripheral blood mononuclear cells; Taccells) may better correlate with drug‐efficacy. The aim of this study was to (1) investigate the relationship between Tacblood and Taccells, (2) identify factors affecting the tacrolimus distribution in cells and whole‐blood, and (3) study the relationship between Taccells and clinical outcomes after kidney transplantation.
Methods
A total of 175 renal transplant recipients were prospectively followed. Tacblood and Taccells were determined at Months 3, 6 and 12 post‐transplantation. Patients were genotyped for ABCB1 1199G>A and 3435C>T, CYP3A4 15389C>T, and CYP3A5 6986G>A. Data on rejection and tacrolimus‐related nephrotoxicity and post‐transplant diabetes mellitus were collected.
Results
Correlations between Tacblood and Taccells were moderate to poor (Spearman's r = 0.31; r = 0.41; r = 0.61 at Months 3, 6 and 12, respectively). The Taccells/Tacblood ratio was stable over time in most patients (median intra‐patient variability 39.0%; range 3.5%–173.2%). Age, albumin and haematocrit correlated with the Taccells/Tacblood ratio. CYP3A5 and CYP3A4 genotype combined affected both dose‐corrected Tacblood and Taccells. ABCB1 was not significantly related to tacrolimus distribution. Neither Tacblood nor Taccells correlated with clinical outcomes.
Conclusions
The correlation between Tacblood and Taccells is poor. Age, albumin and haematocrit correlate with the Taccells/Tacblood ratio, whereas genetic variation in ABCB1, CYP3A4 and CYP3A5 do not. Neither Tacblood nor Taccells correlated with clinical outcomes.
Antipsychotic drugs are an important part of the treatment of irritability and aggression in children with an autism spectrum disorder (ASD). However, significant weight gain and metabolic ...disturbances are clinically relevant side effects of antipsychotic use in children. In the SPACe study, we showed positive correlations between both risperidone and aripiprazole plasma trough concentrations and weight gain over a 6-month period. The trial SPACe 2: STAR is designed as a follow-up study, in which we aim to research whether therapeutic drug monitoring in clinical practice can prevent severe weight gain, while retaining clinical effectiveness.
SPACe 2: STAR is an international, multicentre, randomised controlled trial (RCT). One hundred forty children aged 6 to 18 who are about to start risperidone or aripiprazole treatment for ASD related behavioural problems will be randomised into one of two groups: a therapeutic drug monitoring (TDM) group, and a care as usual (CAU) group. Participants will be assessed at baseline and 4, 10, 24, and 52 weeks follow-up. In the TDM group, physicians will receive dosing advice based on plasma levels of risperidone and aripiprazole and its metabolites at 4 and 10 weeks. Plasma levels will be measured in dried blood spots (DBS). The primary outcome will be BMI z-score at 24 weeks after start of antipsychotic treatment. Among the secondary outcomes are effectiveness, metabolic laboratory measurements, levels of prolactin, leptin and ghrelin, extrapyramidal side effects, and quality of life.
This will be the first RCT evaluating the effect of TDM of antipsychotic drugs in children and adolescents. Thus, findings from SPACe 2: STAR will be of great value in optimising treatment in this vulnerable population.
ClinicalTrials.gov Identifier: NCT05146245. EudraCT number: 2020-005450-18. Sponsor protocol name: SPACe2STAR. Registered 8 June 2021. Protocol Version 6, Protocol date: 18 august 2022.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Bodyweight‐based tacrolimus dosing followed by therapeutic drug monitoring is standard clinical care after renal transplantation. However, after transplantation, a meager 38% of patients are on ...target at first steady‐state and it can take up to 3 weeks to reach the target tacrolimus predose concentration (C0). Tacrolimus underexposure and overexposure is associated with an increased risk of rejection and drug‐related toxicity, respectively. To minimize subtherapeutic and supratherapeutic tacrolimus exposure in the immediate post‐transplant phase, a previously developed dosing algorithm to predict an individual’s tacrolimus starting dose was tested prospectively. In this single‐arm, prospective, therapeutic intervention trial, 60 de novo kidney transplant recipients received a tacrolimus starting dose based on a dosing algorithm instead of a standard, bodyweight‐based dose. The algorithm included cytochrome P450 (CYP)3A4 and CYP3A5 genotype, body surface area, and age as covariates. The target tacrolimus C0, measured for the first time at day 3, was 7.5–12.5 ng/mL. Between February 23, 2019, and July 7, 2020, 60 patients were included. One patient was excluded because of a protocol violation. On day 3 post‐transplantation, 34 of 59 patients (58%, 90% CI 47–68%) had a tacrolimus C0 within the therapeutic range. Markedly subtherapeutic (< 5.0 ng/mL) and supratherapeutic (> 20 ng/mL) tacrolimus concentrations were observed in 7% and 3% of the patients, respectively. Biopsy‐proven acute rejection occurred in three patients (5%). In conclusion, algorithm‐based tacrolimus dosing leads to the achievement of the tacrolimus target C0 in as many as 58% of the patients on day 3 after kidney transplantation.
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