Determining Plasma Tacrolimus Concentrations Using High-Performance LC-MS/MS in Renal Transplant Recipients.

BACKGROUND: Whole-blood therapeutic drug monitoring of tacrolimus is conducted to maintain tacrolimus concentrations within a safe and effective range. Changes in hematocrit cause variability in blood concentrations of tacrolimus because it is highly bound to erythrocytes. Measuring plasma concentrations may eliminate this variability; however, current methods have limitations owing to the use of cross-reactive immunoassays, plasma separation at nonbiological temperatures, and lack of clinical validation. This study aimed to develop and validate a clinically applicable method to measure plasma tacrolimus concentrations in renal transplant recipients and to examine the concentration differences between genotypic CYP3A5 expressors and nonexpressors. METHODS: Plasma tacrolimus concentrations were measured in 9 stable renal transplant recipients who were genotypic CYP3A5 expressors or nonexpressors. Tacrolimus was extracted from plasma using solid-phase extraction, and liquid chromatography-tandem mass spectrometry was used for detection and quantitation. RESULTS: This assay was sensitive, selective, and linear between 100 and 5000 ng/L, with intraassay and interassay imprecision and inaccuracy <10% and <5% respectively. The extraction recovery of tacrolimus and ascomycin was 74%. Matrix ion suppression effects were 31.5% and 35% with overall recovery of 50.6% and 48.3% for tacrolimus and ascomycin, respectively. Whole-blood concentrations accounted for approximately 46% of the variation in plasma concentrations in CYP3A5 expressors and nonexpressors. No difference in dose-adjusted whole-blood and plasma concentrations was observed between CYP3A5 expressors and nonexpressors. CONCLUSIONS: This assay is clinically applicable with excellent performance and demonstrated that tacrolimus plasma concentrations highly correlated with whole-blood concentrations.

Analytical and Non-Analytical Variation May Lead to Inappropriate Antimicrobial Dosing in Neonates: An In Silico Study.

BACKGROUND: Therapeutic drug monitoring (TDM) of aminoglycosides and vancomycin is used to prevent oto- and nephrotoxicity in neonates. Analytical and nonanalytical factors potentially influence dosing recommendations. This study aimed to determine the impact of analytical variation (imprecision and bias) and nonanalytical factors (accuracy of drug administration time, use of non-trough concentrations, biological variation, and dosing errors) on neonatal antimicrobial dosing recommendations. METHODS: Published population pharmacokinetic models and the Australasian Neonatal Medicines Formulary were used to simulate antimicrobial concentration-time profiles in a virtual neonate population. Laboratory quality assurance data were used to quantify analytical variation in antimicrobial measurement methods used in clinical practice. Guideline-informed dosing recommendations based on drug concentrations were applied to compare the impact of analytical variation and nonanalytical factors on antimicrobial dosing. RESULTS: Analytical variation caused differences in subsequent guideline-informed dosing recommendations in 9.3-12.1% (amikacin), 16.2-19.0% (tobramycin), 12.2-45.8% (gentamicin), and 9.6-19.5% (vancomycin) of neonates. For vancomycin, inaccuracies in drug administration time (45.6%), use of non-trough concentrations (44.7%), within-subject biological variation (38.2%), and dosing errors (27.5%) were predicted to result in more dosing discrepancies than analytical variation (12.5%). Using current analytical performance specifications, tolerated dosing discrepancies would be up to 14.8% (aminoglycosides) and 23.7% (vancomycin). CONCLUSIONS: Although analytical variation can influence neonatal antimicrobial dosing recommendations, nonanalytical factors are more influential. These result in substantial variation in subsequent dosing of antimicrobials, risking inadvertent under- or overexposure. Harmonization of measurement methods and improved patient management systems may reduce the impact of analytical and nonanalytical factors on neonatal antimicrobial dosing.

Blood, dose recommendation reports and phone calls: Experiences of a therapeutic drug monitoring advisory service for vancomycin.

Dose-prediction software is recommended to enable area under the curve over 24 h (AUC24 )-guided dosing of the antibiotic vancomycin. However, uncertainty remains about how best to implement software in the clinic. We describe the activity, over 18 months, of a consultative therapeutic drug monitoring Advisory Service (the Service) for vancomycin that used dose-prediction software alongside clinical expertise, identifying factors that influence attainment of therapeutic targets. Of the 408 vancomycin dose reports provided for 182 courses of therapy, most (57%) recommended a dose change. The majority (82.8%, 193/233) of recommended dose adjustments were accepted by treating teams. A dose report was not published for 125 courses of therapy, with reasons including patient in intensive care unit or service error. An estimated 26.6 h of staff time was allocated to Service activities each month. Publication of a dose report facilitated attainment of therapeutic targets (P = .002). Software integration could improve Service outcomes, avoiding errors and reducing staff workload.

Effect of Therapeutic Plasma Exchange on Itraconazole Pharmacokinetics: A Case Study.

ABSTRACT: The authors present the case of a 34-year-old male patient who underwent therapeutic plasma exchange (TPE) for amyopathic dermatomyositis. Immunosuppression resulted in Aspergillus lentulus pulmonary infection , requiring treatment with super bioavailable-itraconazole. Therapeutic itraconazole concentrations were attained after 2 weeks of treatment after dose adjustments. Interestingly, a substantial reduction in plasma itraconazole concentration was observed during TPE, which was attributed to an insufficient delay between the dosing of itraconazole and TPE initiation. Furthermore, there was an increase in plasma concentration post-TPE, which presumably reflects the redistribution of itraconazole from peripheral compartments back into plasma. This was confirmed by sampling of the TPE plasmapheresate, which revealed that changes in plasma concentration overestimated itraconazole clearance. These findings highlight that the pharmacokinetics of itraconazole are altered during TPE, which should be considered when timing drug administration and obtaining plasma concentrations.

Application of User-Centered Codesign Principles to Address Barriers in Therapeutic Drug Monitoring.

BACKGROUND: Different software applications have been developed to support health care professionals in individualized drug dosing. However, their translation into clinical practice is limited, partly because of poor usability and integration into workflow, which can be attributed to the limited involvement of health care professionals in the development and implementation of drug dosing software. This study applied codesign principles to inform the design of a drug dosing software to address barriers in therapeutic drug monitoring using vancomycin as an example. METHODS: Three workshops (face-to-face and online) were conducted by design researchers with pharmacists and prescribers. User journey storyboards, user personas, and prototyping tools were used to explore existing barriers to practice and opportunities for innovation through drug dosing software design. A prototype of the software interface was developed for further evaluation. RESULTS: Health care professionals (11 hospital pharmacists and 6 prescribers) with ≥2 years of clinical experience were recruited. Confidence and software usability emerged as the main themes. Participants identified a lack of confidence in vancomycin dosing and pharmacokinetic understanding and difficulty in accessing practice guidelines as key barriers that could be addressed through software implementation. Accessibility to information (eg, guidelines and pharmacokinetic resources) and information presentation (eg, graphical) within the dosing software were dependent on the needs and experience of the user. A software prototype with a speedometer-dial visual to convey optimal doses was well received by participants. CONCLUSIONS: The perspectives of health care professionals highlight the need for drug dosing software to be user centered and adaptable to the needs and workflow of end users. Continuous engagement with stakeholders on tool usability, training, and education is needed to promote the implementation in practice.

Safety, Tolerability, Pharmacokinetics, and Pharmacodynamics of Coadministered Ruxolitinib and Artemether-Lumefantrine in Healthy Adults.

Despite repeated malaria infection, individuals living in areas where malaria is endemic remain vulnerable to reinfection. The Janus kinase (JAK1/2) inhibitor ruxolitinib could potentially disrupt the parasite-induced dysfunctional immune response when administered with antimalarial therapy. This randomized, single-blind, placebo-controlled, single-center phase 1 trial investigated the safety, tolerability, and pharmacokinetic and pharmacodynamic profile of ruxolitinib and the approved antimalarial artemether-lumefantrine in combination. Ruxolitinib pharmacodynamics were assessed by inhibition of phosphorylation of signal transducer and activator of transcription 3 (pSTAT3). Eight healthy male and female participants ages 18 to 55 years were randomized to either ruxolitinib (20 mg) (n = 6) or placebo (n = 2) administered 2 h after artemether-lumefantrine (80/480 mg) twice daily for 3 days. Mild adverse events occurred in six participants (four ruxolitinib; two placebo). The combination of artemether-lumefantrine and ruxolitinib was well tolerated, with adverse events and pharmacokinetics consistent with the known profiles of both drugs. The incidence of adverse events and artemether, dihydroartemisinin (the major active metabolite of artemether), and lumefantrine exposure were not affected by ruxolitinib coadministration. Ruxolitinib coadministration resulted in a 3-fold-greater pSTAT3 inhibition compared to placebo (geometric mean ratio = 3.01 [90% confidence interval = 2.14 to 4.24]), with a direct and predictable relationship between ruxolitinib plasma concentrations and %pSTAT3 inhibition. This study supports the investigation of the combination of artemether-lumefantrine and ruxolitinib in healthy volunteers infected with Plasmodium falciparum malaria. (This study has been registered at ClinicalTrials.gov under registration no. NCT04456634.).

Optimal Practice for Vancomycin Therapeutic Drug Monitoring: Position Statement From the Anti-infectives Committee of the International Association of Therapeutic Drug Monitoring and Clinical Toxicology.

ABSTRACT: Individualization of vancomycin dosing based on therapeutic drug monitoring (TDM) data is known to improve patient outcomes compared with fixed or empirical dosing strategies. There is increasing evidence to support area-under-the-curve (AUC24)-guided TDM to inform vancomycin dosing decisions for patients receiving therapy for more than 48 hours. It is acknowledged that there may be institutional barriers to the implementation of AUC24-guided dosing, and additional effort is required to enable the transition from trough-based to AUC24-based strategies. Adequate documentation of sampling, correct storage and transport, accurate laboratory analysis, and pertinent data reporting are required to ensure appropriate interpretation of TDM data to guide vancomycin dosing recommendations. Ultimately, TDM data in the clinical context of the patient and their response to treatment should guide vancomycin therapy. Endorsed by the International Association of Therapeutic Drug Monitoring and Clinical Toxicology, the IATDMCT Anti-Infectives Committee, provides recommendations with respect to best clinical practice for vancomycin TDM.

Model-Optimized Fluconazole Dose Selection for Critically Ill Patients Improves Early Pharmacodynamic Target Attainment without the Need for Therapeutic Drug Monitoring.

Fluconazole has been associated with higher mortality compared with the echinocandins in patients treated for invasive candida infections. Underexposure from current fluconazole dosing regimens may contribute to these worse outcomes, so alternative dosing strategies require study. The objective of this study was to evaluate fluconazole drug exposure in critically ill patients comparing a novel model-optimized dose selection method with established approaches over a standard 14-day (336-h) treatment course. Target attainment was evaluated in a representative population of 1,000 critically ill adult patients for (i) guideline dosing (800-mg loading and 400-mg maintenance dosing adjusted to renal function), (ii) guideline dosing followed by therapeutic drug monitoring (TDM)-guided dose adjustment, and (iii) model-optimized dose selection based on patient factors (without TDM). Assuming a MIC of 2 mg/liter, free fluconazole 24-h area under the curve (fAUC24) targets of ≥200 mg · h/liter and <800 mg · h/liter were used for assessment of target attainment. Guideline dosing resulted in underexposure in 21% of patients at 48 h and in 23% of patients at 336 h. The TDM-guided strategy did not influence 0- to 48-h target attainment due to inherent procedural delays but resulted in 37% of patients being underexposed at 336 h. Model-optimized dosing resulted in ≥98% of patients meeting efficacy targets throughout the treatment course, while resulting in less overexposure compared with guideline dosing (7% versus 14%) at 336 h. Model-optimized dose selection enables fluconazole dose individualization in critical illness from the outset of therapy and should enable reevaluation of the comparative effectiveness of this drug in patients with severe fungal infections.

Barriers and opportunities for the clinical implementation of therapeutic drug monitoring in oncology.

There are few fields of medicine in which the individualisation of medicines is more important than in the area of oncology. Under-dosing can have significant ramifications due to the potential for therapeutic failure and cancer progression; by contrast, over-dosing may lead to severe treatment-limiting side effects, such as agranulocytosis and neutropenia. Both circumstances lead to poor patient prognosis and contribute to the high mortality rates still seen in oncology. The concept of dose individualisation tailors dosing for each individual patient to ensure optimal drug exposure and best clinical outcomes. While the value of this strategy is well recognised, it has seen little translation to clinical application. However, it is important to recognise that the clinical setting of oncology is unlike that for which therapeutic drug monitoring (TDM) is currently the cornerstone of therapy (e.g. antimicrobials). Whilst there is much to learn from these established TDM settings, the challenges presented in the treatment of cancer must be considered to ensure the implementation of TDM in clinical practice. Recent advancements in a range of scientific disciplines have the capacity to address the current system limitations and significantly enhance the use of anticancer medicines to improve patient health. This review examines opportunities presented by these innovative scientific methodologies, specifically sampling strategies, bioanalytics and dosing decision support, to enable optimal practice and facilitate the clinical implementation of TDM in oncology.

The effect of high-dose, short-term caffeine intake on the renal clearance of calcium, sodium and creatinine in healthy adults.

The consumption of caffeine has been linked to osteoporosis, believed to be due to enhanced bone resorption as a result of increased calcium excretion in the urine. However, the amount of calcium in the urine may not necessarily reflect the true effect of caffeine on calcium clearance. This study therefore examined the impact of high-dose, short-term caffeine intake on renal clearance of calcium, sodium and creatinine in healthy adults. In a double-blind clinical study, participants chewed caffeine (n = 12) or placebo (n = 12) gum for 5 minutes at 2-hour intervals over a 6-hour treatment period (800 mg total caffeine). Caffeine increased renal calcium clearance by 77%. Furthermore, the effect was positively correlated with sodium clearance and urine volume, suggesting that caffeine may act through inhibition of sodium reabsorption in the proximal convoluted tubule. This study confirmed that caffeine does increase renal calcium clearance and fosters further investigation into safe consumption of caffeine.

Accuracy of documented administration times for intravenous antimicrobial drugs and impact on dosing decisions.

AIMS: Accurate documentation of medication administration time is imperative for many therapeutic decisions, including dosing of intravenous antimicrobials. The objectives were to determine (1) the discrepancy between actual and documented administration times for antimicrobial infusions and (2) whether day of the week, time of day, nurse-to-patient ratio and drug impacted accuracy of documented administration times. METHODS: Patient and dosing data were collected (June-August 2019) for 55 in-patients receiving antimicrobial infusions. "Documented" and "actual" administration times (n = 660) extracted from electronic medication management systems and smart infusion pumps, respectively, were compared. Influence of the day (weekday/weekend), time of day (day/evening/night), nurse-to-patient ratio (high 1:1/low 1:5) and drug were examined. Monte Carlo simulation was used to predict the impact on dose adjustments for vancomycin using the observed administration time discrepancies compared to the actual administration time. RESULTS: The median discrepancy between actual and documented administration times was 16 min (range, 2-293 min), with discrepancies greater than 60 minutes in 7.7% of administrations. Overall, discrepancies (median [range]) were similar on weekends (17 [2-293] min) and weekdays (16 [2-188] min), and for high (16 [2-157] min) and low nurse-to-patient ratio wards (16 [2-293] min). Discrepancies were smallest for night administrations (P < .05), and antimicrobials with shorter half-lives (P < .0001). The observed discrepancies in vancomycin administration time resulted in a different dose recommendation in 58% of cases (30% higher, 28% lower). CONCLUSIONS: Overall, there were discrepancies between actual and documented antimicrobial infusion administration times. For vancomycin, these discrepancies in administration time were predicted to result in inappropriate dose recommendations.

Current fluconazole treatment regimens result in under-dosing of critically ill adults during early therapy.

PURPOSE: To evaluate current fluconazole treatment regimens in critically ill adults over the typical treatment course. METHODS: Data from critically ill adults treated with fluconazole (n=30) were used to develop a population pharmacokinetic model. Probability of target attainment (PTA) (fAUC24/MIC >100) was determined from simulations for four previously proposed treatment regimens: (i) 400 mg once daily, (ii) an 800 mg loading dose followed by 400 mg once daily, (iii) 400 mg twice daily, and (iv) a 12 mg/kg loading dose followed by 6 mg/kg once daily. The effect of body weight (40, 70, 120 kg) and renal function (continuous renal replacement therapy (CRRT); 20, 60, 120, 180 mL/min creatinine clearance) on PTA was assessed. RESULTS: Early (0-48 h) fluconazole target attainment for infections with a minimum inhibitory concentration (MIC) of 2 mg/L was highly variable. PTA was highest with an 800 mg loading dose for underweight (40 kg) patients and with a 12 mg/kg loading dose for the remainder. End-of-treatment PTA was highest with the 400 mg twice daily maintenance dosing for patients who were under- or normal weight and 6 mg/kg maintenance dosing for overweight (120 kg) patients. None of the fluconazole regimens reliably attained early targets for MICs of ≥4 mg/L. CONCLUSION: Current fluconazole dosing regimens do not achieve adequate early target attainment in critically ill adults, particularly in those who are overweight, have higher creatinine clearance, or are undergoing CRRT. Current fluconazole dosing strategies are generally inadequate to treat organisms with an MIC of ≥4 mg/L.

A retrospective study to determine the cefepime-induced neurotoxicity threshold in hospitalized patients.

OBJECTIVES: Cefepime-induced neurotoxicity (CIN) has been demonstrated to be associated with cefepime plasma concentrations; however, the toxicity threshold remains unclear. The primary objective of this study was to identify the cefepime plasma trough concentration at which neurotoxicity occurs. Secondary objectives were to determine the incidence of CIN at a large tertiary institution and to identify patient factors associated with the development of CIN. METHODS: A retrospective review of all adult patients administered cefepime between October 2017 and May 2018 in a tertiary hospital was conducted to determine total incidence of CIN. A receiver operating characteristic (ROC) curve was constructed to review the sensitivity and specificity of using various cefepime trough plasma concentrations to predict the development of neurotoxicity. Cefepime plasma concentrations were measured using ultra-HPLC. A regression was conducted to identify patient factors associated with CIN. RESULTS: In total, 206 patients were administered 259 courses of cefepime, with an overall CIN incidence of 6% (16/259 courses). A total of 64 courses had a cefepime trough concentration measured (24.7%). A cefepime trough concentration of 36 mg/L provided the best differentiation between patients who experienced neurotoxicity and those who did not. No other patient covariates were identified to be significantly associated with neurotoxicity occurring. CONCLUSIONS: A cefepime trough plasma concentration ≥36 mg/L appears to be the most sensitive and specific cut-off to predict CIN occurring. No patient factors were associated with the development of CIN when accounting for cefepime trough plasma concentrations.

Assessing the accuracy of two Bayesian forecasting programs in estimating vancomycin drug exposure.

BACKGROUND: Current guidelines for intravenous vancomycin identify drug exposure (as indicated by the AUC) as the best pharmacokinetic (PK) indicator of therapeutic outcome. OBJECTIVES: To assess the accuracy of two Bayesian forecasting programs in estimating vancomycin AUC0-∞ in adults with limited blood concentration sampling. METHODS: The application of seven vancomycin population PK models in two Bayesian forecasting programs was examined in non-obese adults (n = 22) with stable renal function. Patients were intensively sampled following a single (1000 mg or 15 mg/kg) dose. For each patient, AUC was calculated by fitting all vancomycin concentrations to a two-compartment model (defined as AUCTRUE). AUCTRUE was then compared with the Bayesian-estimated AUC0-∞ values using a single vancomycin concentration sampled at various times post-infusion. RESULTS: Optimal sampling times varied across different models. AUCTRUE was generally overestimated at earlier sampling times and underestimated at sampling times after 4 h post-infusion. The models by Goti et al. (Ther Drug Monit 2018. 40: 212-21) and Thomson et al. (J Antimicrob Chemother 2009. 63: 1050-7) had precise and unbiased sampling times (defined as mean imprecision <25% and <38 mg·h/L, with 95% CI for mean bias containing zero) between 1.5 and 6 h and between 0.75 and 2 h post-infusion, respectively. Precise but biased sampling times for Thomson et al. were between 4 and 6 h post-infusion. CONCLUSIONS: When using a single vancomycin concentration for Bayesian estimation of vancomycin drug exposure (AUC), the predictive performance was generally most accurate with sample collection between 1.5 and 6 h after infusion, though optimal sampling times varied across different population PK models.

Population pharmacokinetics of ribavirin in lung transplant recipients and examination of current and alternative dosing regimens.

BACKGROUND: Ribavirin is used in the treatment of respiratory paramyxovirus infection in lung transplant recipients; however, its pharmacokinetic profile in the transplant population is unknown despite the potential for alterations due to underlying pathology. Furthermore, the ability of current regimens to meet exposure targets has not been established. OBJECTIVES: This study examined the pharmacokinetics of ribavirin in a lung transplant population for which current and alternative dosing regimens were assessed. METHODS: Population pharmacokinetic modelling was conducted in NONMEM using concentration-time data from 24 lung transplant recipients and 6 healthy volunteers. Monte Carlo simulation was used to assess the ability of dosing regimens to achieve pre-specified target concentrations. RESULTS AND CONCLUSIONS: A three-compartment model with first-order elimination most adequately described ribavirin concentration-time data, with CLCR and patient type (i.e. lung transplant) identified as significant covariates in the model. Simulations indicate that current regimens achieve efficacious concentrations within 24 h of treatment initiation that increase to supra-therapeutic levels over the treatment period. A regimen of 8 mg/kg q6h orally for 48 h followed by 8 mg/kg q24h orally for the remainder of the treatment period was predicted to result in >90% of patients exhibiting concentrations within the defined target range throughout the entire treatment course. Additional work to formally establish target therapeutic concentrations is required; however, this study provides a valuable first step in determining optimal ribavirin treatment regimens for paramyxovirus infections in the lung transplant population.

Population pharmacokinetics of lenalidomide in patients with B-cell malignancies.

AIMS: Lenalidomide is an immunomodulatory imide drug used broadly in the treatment of multiple myeloma and lymphoma. It continues to be evaluated in chronic lymphocytic leukaemia (CLL) at lower doses due to dose-related toxicities including tumour flare and tumour lysis syndrome. This study aimed to develop a population pharmacokinetic model for lenalidomide in multiple cancers, including CLL, to identify any disease-related differences in disposition. METHODS: Lenalidomide concentrations from 4 clinical trials were collated (1999 samples, 125 subjects), covering 4 cancers (multiple myeloma, CLL, acute myeloid leukaemia and acute lymphoblastic leukaemia) and a large dose range (2.5-75 mg). A population pharmacokinetic model was developed with NONMEM and patient demographics were tested as covariates. RESULTS: The data were best fitted by a 1-compartment kinetic model with absorption described by 7 transit compartments. Clearance and volume of distribution were allometrically scaled for fat-free mass. The population parameter estimates for apparent clearance, apparent volume of distribution and transit rate constant were 12 L/h (10.8-13.6), 68.8 L (61.8-76.3), and 13.5 h-1 (11.9-36.8) respectively. Patients with impaired renal function (creatinine clearance <30 mL/min) exhibited a 22% reduction in lenalidomide clearance compared to patients with creatinine clearance of 90 mL/min. Cancer type had no discernible effect on lenalidomide disposition. CONCLUSIONS: This is the first report of a lenalidomide population pharmacokinetic model to evaluate lenalidomide pharmacokinetics in patients with CLL and compare its pharmacokinetics with other B-cell malignancies. As no differences in pharmacokinetics were found between the observed cancer-types, the unique toxicities observed in CLL may be due to disease-specific pharmacodynamics.

Comparison of the Area Under the Curve for Vancomycin Estimated Using Compartmental and Noncompartmental Methods in Adult Patients With Normal Renal Function.

BACKGROUND: Vancomycin pharmacokinetics are best described using a 2-compartment model. However, 1-compartment population models are commonly used as the basis for dose prediction software. Therefore, the validity of using a 1-compartment model to guide vancomycin drug dosing was examined. METHODS: Published plasma concentration-time data from adult subjects (n = 30) with stable renal function administered a single intravenous infusion of vancomycin were extracted from previous studies. The vancomycin area under the curve (AUC0-∞) was calculated for each subject using noncompartmental methods (AUCNCA) and by fitting 1- (AUC1CMT), 2- (AUC2CMT), and 3- (AUC3CMT) compartment infusion models. The optimal model fit was determined using the Akaike information criterion and visual inspection of the residual plots. The individual compartmental AUC0-∞ values from the 1- and 2-compartment models were compared with AUCNCA values using one-way repeated measures analysis of variance. RESULTS: The mean (±SD) AUC estimates were similar for the different methods: AUCNCA 180 ± 86 mg·h/L, AUC1CMT 167 ± 79 mg·h/L, and AUC2CMT 183 ± 88 mg·h/L. Despite the overlapping AUC values, AUC2CMT and AUCNCA were significantly greater than AUC1CMT (P < 0.05). The 3-compartment model was excluded from the analysis because of the failure to converge in some instances. CONCLUSIONS: Dose prediction software using a 1-compartment model as the basis for Bayesian forecasting underestimates drug exposure (estimated as the AUC) by less than 10%. This is unlikely to be clinically significant with respect to dose adjustment. Therefore, a 1-compartment model may be sufficient to guide vancomycin dosing in adult patients with stable renal function.

Population pharmacokinetics of orally administered mefloquine in healthy volunteers and patients with uncomplicated Plasmodium falciparum malaria.

BACKGROUND: The determination of dosing regimens for the treatment of malaria is largely empirical and thus a better understanding of the pharmacokinetic/pharmacodynamic properties of antimalarial agents is required to assess the adequacy of current treatment regimens and identify sources of suboptimal dosing that could select for drug-resistant parasites. Mefloquine is a widely used antimalarial, commonly given in combination with artesunate. PATIENTS AND METHODS: Mefloquine pharmacokinetics was assessed in 24 healthy adults and 43 patients with Plasmodium falciparum malaria administered mefloquine in combination with artesunate. Population pharmacokinetic modelling was conducted using NONMEM. RESULTS: A two-compartment model with a single transit compartment and first-order elimination from the central compartment most adequately described mefloquine concentration-time data. The model incorporated population parameter variability for clearance (CL/F), central volume of distribution (VC/F) and absorption rate constant (KA) and identified, in addition to body weight, malaria infection as a covariate for VC/F (but not CL/F). Monte Carlo simulations predict that falciparum malaria infection is associated with a shorter elimination half-life (407 versus 566 h) and T>MIC (766 versus 893 h). CONCLUSIONS: This is the first known population pharmacokinetic study to show falciparum malaria to influence mefloquine disposition. Protein binding, anaemia and other factors may contribute to differences between healthy individuals and patients. As VC/F is related to the earlier portion of the concentration-time profiles, which occurs during acute malaria, and CL/F is more related to the terminal phase during convalescence after treatment, this may explain why malaria was found to be a covariate for VC/F but not CL/F.

Determination of a vancomycin nephrotoxicity threshold and assessment of target attainment in hematology patients.

An area-under-the-curve (AUC24)-based approach is recommended to guide vancomycin therapeutic drug monitoring (TDM), yet trough concentrations are still commonly used despite associated risks. A definitive toxicity target is lacking, which is important for hematology patients who have a higher risk of nephrotoxicity. The aims were to (1) assess the impact of trough-based TDM on acute kidney injury (AKI) incidence, (2) establish a vancomycin nephrotoxicity threshold, and (3) evaluate the proportion of hematology patients achieving vancomycin therapeutic targets. Retrospective data was collected from 100 adult patients with a hematological malignancy or aplastic anemia who received vancomycin between April 2020 and January 2021. AKI occurrence was determined based on serum creatinine concentrations, and individual pharmacokinetic parameters were estimated using a Bayesian approach. Receiver operating characteristic (ROC) curve analysis was performed to assess the ability of pharmacokinetic indices to predict AKI occurrence. The proportion of patients who achieved target vancomycin exposure was evaluated based on an AUC24/MIC ≥400 and the determined toxicity threshold. The incidence of AKI was 37%. ROC curve analysis indicated a maximum AUC24 of 644 mg.h/L over the treatment period was an important predictor of AKI. By Day 4 of treatment, 29% of treatment courses had supratherapeutic vancomycin exposure, with only 62% of courses achieving AUC24 targets. The identified toxicity threshold supports an AUC24 target range of 400-650 mg.h/L, assuming an MIC of 1 mg/L, to optimize vancomycin efficacy and minimize toxicity. This study highlights high rates of AKI in this population and emphasizes the importance of transitioning from trough-based TDM to an AUC-based approach to improve clinical outcomes.

The Influence of a Therapeutic Drug Monitoring Service on Vancomycin-Associated Nephrotoxicity.

Vancomycin's widespread use as the mainstay antibiotic against methicillin-resistant Staphylococcus aureus infections is complicated by its narrow therapeutic index. Therapeutic drug monitoring using area under the concentration-time curve (AUC)-guided dosing is recommended to optimize therapy and prevent vancomycin-associated nephrotoxicity (VAN). In 2018, a consultative therapeutic drug monitoring Advisory Service (the Service) was piloted at an Australian hospital to enable AUC-guided vancomycin dosing. This study sought to compare the incidence of VAN pre- and post-Service implementation. A 4-year retrospective observational study of intravenous vancomycin therapy (greater than 48 hours) in adults (aged 18 years or older), spanning 3 years before and 1-year after implementation of the Service was undertaken. Nephrotoxicity was defined as an increase in serum creatinine concentrations of 26.5 µmol/L or greater or 50% or more from baseline, on 2 or more consecutive days. Univariate analysis was performed to compare patients before and after implementation, and with and without VAN. Independent factors associated with VAN were identified using a multivariate model. In total, 971 courses of vancomycin therapy, administered to 781 patients, were included: 764 courses (603 patients) before implementation and 207 courses (163 patients) after implementation. The incidence of VAN decreased by 5% after Service implementation (15% before implementation vs 10% after implementation; P = .075). Independent factors associated with VAN were sepsis, heart failure, solid-organ transplant, concomitant piperacillin-tazobactam, and average vancomycin AUC during therapy. In conclusion, there was a nonsignificant trend toward a reduced incidence of VAN after the Service. Larger prospective studies are needed to confirm the efficacy of the Service.