Maximum likelihood estimation of renal transporter ontogeny profiles for pediatric PBPK modeling.

Optimal treatment of infants with many renally cleared drugs must account for maturational differences in renal transporter (RT) activity. Pediatric physiologically-based pharmacokinetic (PBPK) models may incorporate RT activity, but this requires ontogeny profiles for RT activity in children, especially neonates, to predict drug disposition. Therefore, RT expression measurements from human kidney postmortem cortical tissue samples were normalized to represent a fraction of mature RT activity. Using these data, maximum likelihood estimated the distributions of RT activity across the pediatric age spectrum, including preterm and term neonates. PBPK models of four RT substrates (acyclovir, ciprofloxacin, furosemide, and meropenem) were evaluated with and without ontogeny profiles using average fold error (AFE), absolute average fold error (AAFE), and proportion of observations within the 5-95% prediction interval. Novel maximum likelihood profiles estimated ontogeny distributions for the following RT: OAT1, OAT3, OCT2, P-gp, URAT1, BCRP, MATE1, MRP2, MRP4, and MATE-2 K. Profiles for OAT3, P-gp, and MATE1 improved infant furosemide and neonate meropenem PBPK model AFE from 0.08 to 0.70 and 0.53 to 1.34 and model AAFE from 12.08 to 1.44 and 2.09 to 1.36, respectively, and improved the percent of data within the 5-95% prediction interval from 48% to 98% for neonatal ciprofloxacin simulations, respectively. Even after accounting for other critical population-specific maturational differences, novel RT ontogeny profiles substantially improved neonatal PBPK model performance, providing validated estimates of maturational differences in RT activity for optimal dosing in children.

Medication patterns and dosing guidance in pediatric patients supported with intermittent hemodialysis or continuous kidney replacement therapy.

BACKGROUND: Hemodialysis is a life-saving technology used during periods of acute or chronic kidney failure to remove toxins, and maintain fluid, electrolyte and metabolic balance. While this technology plays an important role for pediatric patients with kidney dysfunction, it can alter the pharmacokinetic behavior of medications placing patients at risk for suboptimal dosing and drug toxicity. The ability to directly translate pharmacokinetic alterations into dosing recommendations has thus far been limited and dosing guidance specific to pediatric hemodialysis patients is rare. Despite differences in dialysis prescription and patient populations, intermittent (iHD) and continuous kidney replacement therapy (CKRT) patients are often pooled together. In order to develop evidence-based dosing guidelines, it is important to first prioritize drugs for study in each modality. METHODS: Here we aim to identify priority drugs in two hemodialysis modalities, through: 1) Identification of hospitalized, pediatric patients who received CKRT or intermittent hemodialysis (iHD) using a machine learning-based predictive model based on medications; 2) Identification of medication administration patterns in these patient cohorts; and 3) Identification of the most commonly prescribed drugs that lack published dosing guidance. RESULTS: Notable differences were found in the pattern of medications and drug dosing guidance between iHD and CKRT patients. Antibiotics, diuretics and sedatives were more common in CKRT patients. Out of the 50 most commonly administered medications in the two modalities, only 34% and 28% had dosing guidance present for iHD and CKRT, respectively. CONCLUSIONS: Our results add to the understanding of the differences between iHD and CKRT patient populations by identifying commonly used medications that lack dosing guidance for each hemodialysis modality, helping to pinpoint priority medications for further study. Overall, this study provides an overview of the current limitations in medication use in this at-risk population, and provides a framework for future studies by identifying commonly used medications in pediatric CKRT and iHD patients. A higher resolution version of the Graphical abstract is available as Supplementary information.

Anakinra Removal by Continuous Renal Replacement Therapy: An Ex Vivo Analysis.

OBJECTIVES: Patients with sepsis are at significant risk for multiple organ dysfunction, including the lungs and kidneys. To manage the morbidity associated with kidney impairment, continuous renal replacement therapy (CRRT) may be required. The extent of anakinra pharmacokinetics in CRRT remains unknown. The objectives of this study were to investigate the anakinra-circuit interaction and quantify the rate of removal from plasma. DESIGN: The anakinra-circuit interaction was evaluated using a closed-loop ex vivo CRRT circuit. CRRT was performed in three phases based on the method of solute removal: 1) hemofiltration, 2) hemodialysis, and 3) hemodiafiltration. Standard control samples of anakinra were included to assess drug degradation. SETTING: University research laboratory. PATIENTS: None. INTERVENTIONS: Anakinra was administered to the CRRT circuit and serial prefilter blood samples were collected along with time-matched control and hemofiltrate samples. Each circuit was run in triplicate to assess inter-run variability. Concentrations of anakinra in each reference fluid were measured by enzyme-linked immunosorbent assay. Transmembrane filter clearance was estimated by the product of the sieving coefficient/dialysate saturation constant and circuit flow rates. MEASUREMENTS AND MAIN RESULTS: Removal of anakinra from plasma occurred within minutes for each CRRT modality. Average drug remaining (%) in plasma following anakinra administration was lowest with hemodiafiltration (34.9%). The average sieving coefficient was 0.34, 0.37, and 0.41 for hemodiafiltration, hemofiltration, and hemodialysis, respectively. Transmembrane clearance was fairly consistent across each modality with the highest during hemodialysis (5.53 mL/min), followed by hemodiafiltration (4.99 mL/min), and hemofiltration (3.94 mL/min). Percent drug remaining within the control samples (93.1%) remained consistent across each experiment, indicating negligible degradation within the blood. CONCLUSIONS: The results of this analysis are the first to demonstrate that large molecule therapeutic proteins such as anakinra, are removed from plasma with modern CRRT technology. Current dosing recommendations for patients with severe renal impairment may result in subtherapeutic anakinra concentrations in those receiving CRRT.

Direct and continuous dosing of propofol can saturate Ex vivo ECMO circuit to improve propofol recovery.

BACKGROUND: Extracorporeal membrane oxygenation (ECMO) is a cardiopulmonary bypass device that provides life-saving complete respiratory and cardiac support in patients with cardiorespiratory failure. The majority of drugs prescribed to patients on ECMO lack a dosing strategy optimized for ECMO patients. Several studies demonstrated that dosing is different in this population because the ECMO circuit components can adsorb drugs and affect drug exposure substantially. Saturation of ECMO circuit components by drug disposition has been posited but has not been proven. In this study, we have attempted to determine if propofol adsorption is saturable in ex vivo ECMO circuits. METHODS: We injected ex vivo ECMO circuits with propofol, a drug that is highly adsorbed to the ECMO circuit components. Propofol was injected as a bolus dose (50 µg/mL) and a continuous infusion dose (6 mg/h) to investigate the saturation of the ECMO circuit. RESULTS: After the bolus dose, only 27% of propofol was recovered after 30 minutes which is as expected. However, >80% propofol was recovered after the infusion dose which persisted even when the infusion dose was discontinued. CONCLUSION: Our results suggest that if ECMO circuits are dosed directly with propofol, drug adsorption can be eliminated as a cause for altered drug exposure. Field of Research: Artificial Lung/ECMO.

Meropenem extraction by ex vivo extracorporeal life support circuits.

BACKGROUND: Meropenem is a broad-spectrum carbapenem-type antibiotic commonly used to treat critically ill patients infected with extended-spectrum ß-lactamase (ESBL)-producing Enterobacteriaceae. As many of these patients require extracorporeal membrane oxygenation (ECMO) and/or continuous renal replacement therapy (CRRT), it is important to understand how these extracorporeal life support circuits impact meropenem pharmacokinetics. Based on the physicochemical properties of meropenem, it is expected that ECMO circuits will minimally extract meropenem, while CRRT circuits will rapidly clear meropenem. The present study seeks to determine the extraction of meropenem from ex vivo ECMO and CRRT circuits and elucidate the contribution of different ECMO circuit components to extraction. METHODS: Standard doses of meropenem were administered to three different configurations (n = 3 per configuration) of blood-primed ex vivo ECMO circuits and serial sampling was conducted over 24 h. Similarly, standard doses of meropenem were administered to CRRT circuits (n = 4) and serial sampling was conducted over 4 h. Meropenem was administered to separate tubes primed with circuit blood to serve as controls to account for drug degradation. Meropenem concentrations were quantified, and percent recovery was calculated for each sample. RESULTS: Meropenem was cleared at a similar rate in ECMO circuits of different configurations (n = 3) and controls (n = 6), with mean (standard deviation) recovery at 24 h of 15.6% (12.9) in Complete circuits, 37.9% (8.3) in Oxygenator circuits, 47.1% (8.2) in Pump circuits, and 20.6% (20.6) in controls. In CRRT circuits (n = 4) meropenem was cleared rapidly compared with controls (n = 6) with a mean recovery at 2 h of 2.36% (1.44) in circuits and 93.0% (7.1) in controls. CONCLUSION: Meropenem is rapidly cleared by hemodiafiltration during CRRT. There is minimal adsorption of meropenem to ECMO circuit components; however, meropenem undergoes significant degradation and/or plasma metabolism at physiological conditions. These ex vivo findings will advise pharmacists and physicians on the appropriate dosing of meropenem.

Streamlining the Detection of Human Thyroid Receptor Ligand Interactions with XL1-Blue Cell-Free Protein Synthesis and Beta-Galactosidase Fusion Protein Biosensors.

Thyroid receptor signaling controls major physiological processes and disrupted signaling can cause severe disorders that negatively impact human life. Consequently, methods to detect thyroid receptor ligands are of great toxicologic and pharmacologic importance. Previously, we reported thyroid receptor ligand detection with cell-free protein synthesis of a chimeric fusion protein composed of the human thyroid receptor beta (hTRß) receptor activator and a ß-lactamase reporter. Here, we report a 60% reduction in sensing cost by reengineering the chimeric fusion protein biosensor to include a reporter system composed of either the full-length beta galactosidase (ß-gal), the alpha fragment of ß-gal (ß-gal-α), or a split alpha fragment of the ß-gal (split ß-gal-α). These biosensor constructs are deployed using E. coli XL1-Blue cell extract to (1) avoid the ß-gal background activity abundant in BL21 cell extract and (2) facilitate ß-gal complementation reporter activity to detect human thyroid receptor ligands. These results constitute a promising platform for high throughput screening and potentially the portable detection of human thyroid receptor ligands.

Interaction of ceftazidime and clindamycin with extracorporeal life support.

BACKGROUND: Ceftazidime and clindamycin are commonly prescribed to critically ill patients who require extracorporeal life support such as ECMO and CRRT. The effect of ECMO and CRRT on the disposition of ceftazidime and clindamycin is currently unknown. METHODS: Ceftazidime and clindamycin extraction were studied with ex vivo ECMO and CRRT circuits primed with human blood. The percent recovery of these drugs over time was calculated to determine the degree of interaction between these drugs and circuit components. RESULTS: Neither ceftazidime nor clindamycin exhibited measurable interactions with the ECMO circuit. In contrast, CRRT cleared 100% of ceftazidime from the experimental circuit within the first 2 h. Clearance of clindamycin from the CRRT circuit was slower, with about 20% removed after 6 h. CONCLUSION: Clindamycin and ceftazidime dosing adjustments are likely required in patients who are supported with CRRT, and future studies to quantify these adjustments should consider the pathophysiology of the patient in combination with the clearance due to CRRT. Dosing adjustments to account for adsorption to ECMO circuit components are likely unnecessary and should focus instead on the pathophysiology of the patient and changes in volume of distribution. These results will help improve the safety and efficacy of ceftazidime and clindamycin in patients requiring ECMO and CRRT.

Utility of triazole antifungal therapeutic drug monitoring: Insights from the Society of Infectious Diseases Pharmacists: Endorsed by the Mycoses Study Group Education and Research Consortium.

Triazole antifungals (i.e., fluconazole, itraconazole, voriconazole, posaconazole, and isavuconazole) are commonly used in clinical practice to prevent or treat invasive fungal infections. Most triazole antifungals require therapeutic drug monitoring (TDM) due to highly variable pharmacokinetics, known drug interactions, and established relationships between exposure and response. On behalf of the Society of Infectious Diseases Pharmacists (SIDP), this insight describes the pharmacokinetic principles and pharmacodynamic targets of commonly used triazole antifungals and provides the rationale for utility of TDM within each agent.

Mapping the Evidence for Opioid-Mediated Changes in Malignancy and Chemotherapeutic Efficacy: Protocol for a Scoping Review.

BACKGROUND: Numerous reports contend opioids can augment or inhibit malignancy. At present, there is no consensus on the risk or benefit posed by opioids on malignancy or chemotherapeutic activity. Distinguishing the consequences of opioid use from pain and its management is challenging. Additionally, opioid concentration data is often lacking in clinical studies. A scoping review approach inclusive of preclinical and clinical data will improve our understanding of the risk-benefit relationship concerning commonly prescribed opioids and cancer and cancer treatment. OBJECTIVE: The aim of the study is to map diverse studies spanning from preclinical to clinical regarding opioids with malignancy and its treatment. METHODS: This scoping review will use the Arksey six stages framework to (1) identify the research question; (2) identify relevant studies; (3) select studies meeting criteria; (4) extract and chart data; (5) collate, summarize, and report results; and (6) conduct expert consultation. An initial pilot study was undertaken to (1) parameterize the extent and scale of existing data for an evidence review, (2) identify key factors to be extracted in systematic charting efforts, and (3) assess opioid concentration as a variable for its relevance to the central hypothesis. Six databases will be searched with no filters: MEDLINE, Embase, CINAHL Complete, Cochrane Library, Biological Sciences Collection, and International Pharmaceutical Abstracts. Trial registries will include ClinicalTrials.gov, Cochrane CENTRAL, International Standard Randomised Controlled Trial Number Registry, European Union Clinical Trials Register, and World Health Organization International Clinical Trials Registry. Eligibility criteria will include preclinical and clinical study data on opioids effects on tumor growth or survival, or alteration on the antineoplastic activity of chemotherapeutics. We will chart data on (1) opioid concentration from human subjects with cancer, yielding a "physiologic range" to better interpret available preclinical data; (2) patterns of opioid exposure with disease and treatment-related patient outcomes; and (3) the influence of opioids on cancer cell survival, as well as opioid-related changes to cancer cell susceptibility for chemotherapeutics. RESULTS: This scoping review will present results in narrative forms as well as with the use of tables and diagrams. Initiated in February 2021 at the University of Utah, this protocol is anticipated to generate a scoping review by August 2023. The results of the scoping review will be disseminated through scientific conference proceedings and presentations, stakeholder meetings, and by publication in a peer-reviewed journal. CONCLUSIONS: The findings of this scoping review will provide a comprehensive description of the consequences of prescription opioids on malignancy and its treatment. By incorporating preclinical and clinical data, this scoping review will invite novel comparisons across study types that could inform new basic, translational, and clinical studies regarding risks and benefits of opioid use among patients with cancer. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/38167.

Micellar Encapsulation of Propofol Reduces its Adsorption on Extracorporeal Membrane Oxygenator (ECMO) Circuit.

Extracorporeal membrane oxygenation (ECMO) is a life-saving cardiopulmonary bypass device used on critically ill patients with refractory heart and lung failure. Patients supported with ECMO receive numerous drugs to treat critical illnesses and the underlying diseases. Unfortunately, most drugs prescribed to patients on ECMO lack accurate dosing information. Dosing can be variable in this patient population because the ECMO circuit components can adsorb drugs and affect drug exposure substantially. Propofol is a widely used anesthetic in ECMO patients and is known to have high adsorption rates in ECMO circuits due to its high hydrophobicity. In an attempt to reduce adsorption, we encapsulated propofol with Poloxamer 407 (Polyethylene-Polypropylene Glycol). Size and polydispersity index (PDI) were characterized using dynamic light scattering. Encapsulation efficiency was analyzed using High performance liquid chromatography. Cytocompatibility of micelles was analyzed against human macrophages and the formulation was finally injected in an ex-vivo ECMO circuit to determine the adsorption of propofol. Size and PDI of micellar propofol were 25.5 ± 0.8 nm and 0.08 ± 0.01, respectively. Encapsulation efficiency of the drug was 96.1 ± 1.3%. Micellar propofol demonstrated colloidal stability at physiological temperature for a period of 7 days, and was cytocompatible with human macrophages. Micellar propofol demonstrated a significant reduction in adsorption of propofol in the ECMO circuit at earlier time points compared to free propofol (Diprivan®). We observed 97 ± 2% recovery of the propofol from the micellar formulation after an infusion. These results demonstrate the potential of micellar propofol to reduce drug adsorption to ECMO circuit.

Drug exposure during pregnancy: Current understanding and approaches to measure maternal-fetal drug exposure.

Prescription drug use is prevalent during pregnancy, yet there is limited knowledge about maternal-fetal safety and efficacy of this drug use because pregnant individuals have historically been excluded from clinical trials. Underrepresentation has resulted in a lack of data available to estimate or predict fetal drug exposure. Approaches to study fetal drug pharmacology are limited and must be evaluated for feasibility and accuracy. Anatomic and physiological changes throughout pregnancy fluctuate based on gestational age and can affect drug pharmacokinetics (PK) for both mother and fetus. Drug concentrations have been studied throughout different stages of gestation and at or following delivery in tissue and fluid biospecimens. Sampling amniotic fluid, umbilical cord blood, placental tissue, meconium, umbilical cord tissue, and neonatal hair present surrogate options to quantify and characterize fetal drug exposure. These sampling methods can be applied to all therapeutics including small molecule drugs, large molecule drugs, conjugated nanoparticles, and chemical exposures. Alternative approaches to determine PK have been explored, including physiologically based PK modeling, in vitro methods, and traditional animal models. These alternative approaches along with convenience sampling of tissue or fluid biospecimens can address challenges in studying maternal-fetal pharmacology. In this narrative review, we 1) present an overview of the current understanding of maternal-fetal drug exposure; 2) discuss biospecimen-guided sampling design and methods for measuring fetal drug concentrations throughout gestation; and 3) propose methods for advancing pharmacology research in the maternal-fetal population.

Medication based machine learning to identify subpopulations of pediatric hemodialysis patients in an electronic health record database.

Electronic health records (EHRs) have given rise to large and complex databases of medical information that have the potential to become powerful tools for clinical research. However, differences in coding systems and the detail and accuracy of the information within EHRs can vary across institutions. This makes it challenging to identify subpopulations of patients and limits the widespread use of multi-institutional databases. In this study, we leveraged machine learning to identify patterns in medication usage among hospitalized pediatric patients receiving renal replacement therapy and created a predictive model that successfully differentiated between intermittent (iHD) and continuous renal replacement therapy (CRRT) hemodialysis patients. We trained six machine learning algorithms (logistical regression, Naïve Bayes, k-nearest neighbor, support vector machine, random forest, and gradient boosted trees) using patient records from a multi-center database (n = 533) and prescribed medication ingredients (n = 228) as features to discriminate between the two hemodialysis types. Predictive skill was assessed using a 5-fold cross-validation, and the algorithms showed a range of performance from 0.7 balanced accuracy (logistical regression) to 0.86 (random forest). The two best performing models were further tested using an independent single-center dataset and achieved 84-87% balanced accuracy. This model overcomes issues inherent within large databases and will allow us to utilize and combine historical records, significantly increasing population size and diversity within both iHD and CRRT populations for future clinical studies. Our work demonstrates the utility of using medications alone to accurately differentiate subpopulations of patients in large datasets, allowing codes to be transferred between different coding systems. This framework has the potential to be used to distinguish other subpopulations of patients where discriminatory ICD codes are not available, permitting more detailed insights and new lines of research.

Use of Electronic Health Records to Identify Exposure-Response Relationships in Critically Ill Children: An Example of Midazolam and Delirium.

Adverse drug events are common in critically ill children and often result from systemic or target organ drug exposure. Methods of drug dosing and titration that consider pharmacokinetic alterations may improve our ability to optimally dose critically ill patients and reduce the risk for drug-related adverse events. To demonstrate this possibility, we explored the exposure-response relationship between midazolam and delirium in critically ill children. We retrospectively examined electronic health records (EHRs) of critically ill children <18 years of age hospitalized in the pediatric intensive care unit at Duke University; these children were administered midazolam during mechanical ventilation and had ≥1 Cornell Assessment of Pediatric Delirium (CAPD) score. We used individual-level data extracted from the EHR and a previously published population pharmacokinetic (PK) model developed in critically ill children to simulate plasma concentrations at the time of CAPD scores in 1,000 representative datasets. We used multilevel repeated measures models, with clustering at patient and simulation levels, to evaluate the associations between measures of drug exposure (e.g., concentration and area under concentration time curve) and delirium scores. We included 61 children, median age 1.5 years (range = 0.1-16.3), with 181 CAPD assessments. We identified similarities between simulated Empirical Bayesian parameter estimates from the EHR cohort and those from the PK model population. We identified a stronger association between drug concentration at the time of score and CAPD scores (coefficient 1.78; 95% confidence interval: 1.66-1.90) compared with cumulative dose per kilogram and CAPD scores (coefficient -0.01; 95% confidence interval: -0.01 to -0.01). EHR and PK models can be leveraged to investigate exposure-response relationships in critically ill children.

Use of physiologically-based pharmacokinetic modeling to inform dosing of the opioid analgesics fentanyl and methadone in children with obesity.

Obesity is an increasingly alarming public health threat, with nearly 20% of children classified as obese in the United States today. Children with obesity are commonly prescribed the opioids fentanyl and methadone, and accurate dosing is critical to reducing the risk of serious adverse events associated with overexposure. However, pharmacokinetic studies in children with obesity are challenging to conduct, so there is limited information to guide fentanyl and methadone dosing in these children. To address this clinical knowledge gap, physiologically-based pharmacokinetic models of fentanyl and methadone were developed in adults and scaled to children with and without obesity to explore the interplay of obesity, age, and pharmacogenomics. These models included key obesity-induced changes in physiology and pharmacogenomic effects. Model predictions captured observed concentrations in children with obesity well, with an overall average fold error of 0.72 and 1.08 for fentanyl and methadone, respectively. Model simulations support a reduced fentanyl dose (1 vs. 2 µg/kg/h) starting at an earlier age (6 years) in virtual children with obesity, highlighting the importance of considering both age and obesity status when selecting an infusion rate most likely to achieve steady-state concentrations within the target range. Methadone dosing simulations highlight the importance of considering genotype in addition to obesity status when possible, as cytochrome P450 (CYP)2B6*6/*6 virtual children with obesity required half the dose to match the exposure of wildtype children without obesity. This physiologically-based pharmacokinetic modeling approach can be applied to explore dosing of other critical drugs in children with obesity.

Cefepime Extraction by Extracorporeal Life Support Circuits.

Extracorporeal life support (ECLS) devices are lifesaving for critically ill patients with multi-organ dysfunction. Despite this, patients supported with ECLS are at high risk for ECLS-related complications, including nosocomial infections, and mortality rates are high in this patient population. The high mortality rates are suspected to be, in part, a result of significantly altered drug disposition by the ECLS circuit, resulting in suboptimal antimicrobial dosing. Cefepime is commonly used in critically ill patients with serious infections. Cefepime dosing is not routinely guided by therapeutic drug monitoring and treatment success is dependent upon the percentage of time of the dosing interval that the drug concentration remains above the minimum inhibitory concentration of the organism. This ex vivo study measured the extraction of cefepime by continuous renal replacement therapy (CRRT) and extracorporeal membrane oxygenation (ECMO) circuits. Cefepime was studied in four closed-loop CRRT circuit configurations and a single closed-loop ECMO circuit configuration. Circuits were primed with a physiologic human blood-plasma mixture and the drug was dosed to achieve therapeutic concentrations. Serial blood samples were collected over time and concentrations were quantified using validated assays. In ex vivo CRRT experiments, cefepime was rapidly cleared by dialysis, hemofiltration, and hemodiafiltration, with greater than 96% cefepime eliminated from the circuit by 2 hours. In the ECMO circuits, the mean recovery of cefepime was similar in both circuit and standard control. Mean (standard deviation) recovery of cefepime in the ECMO circuits (n = 6) was 39.2% (8.0) at 24 hours. Mean recovery in the standard control (n = 3) at 24 hours was 52.2% (1.5). Cefepime is rapidly cleared by dialysis, hemofiltration, and hemodiafiltration in the CRRT circuit but minimally adsorbed by either the CRRT or ECMO circuits. Dosing adjustments are needed for patients supported with CRRT.

Remdesivir and GS-441524 Extraction by Ex Vivo Extracorporeal Life Support Circuits.

Patients with severe, COVID-related multi-organ failure often require extracorporeal life support (ECLS) such as extracorporeal membrane oxygenation (ECMO) or continuous renal replacement therapy (CRRT). An ECLS can alter drug exposure via multiple mechanisms. Remdesivir (RDV) and its active metabolite GS-441524 are likely to interact with ECLS circuits, resulting in lower than expected exposures. We evaluated circuit-drug interactions in closed loop, ex vivo ECMO and CRRT circuits. We found that mean (standard deviation) recovery of RDV at 6 hours after dosing was low in both the ECMO (33.3% [2.0]) and CRRT (3.5% [0.4]) circuits. This drug loss appears to be due primarily to drug adsorption by the circuit materials and potentially due to metabolism in the blood. GS-441524 recovery at 6 hours was high in the ECMO circuit 75.8% (16.5); however, was not detectable at 6 hours in the CRRT circuit. Loss in the CRRT circuit appears to be due primarily to efficient hemodiafiltration. The extent of loss for both molecules, especially in CRRT, suggests that in patients supported with ECMO and CRRT, RDV dosing adjustments are needed.

Amiodarone Extraction by the Extracorporeal Membrane Oxygenation Circuit.

Amiodarone is an anti-arrhythmic agent that is frequently used to treat tachycardias in critically ill adults and children. Because of physicochemical properties of amiodarone, extracorporeal membrane oxygenation (ECMO) circuits are expected to extract amiodarone from circulation, increasing the risk of therapeutic failure. The present study seeks to determine amiodarone extraction by the ECMO circuit. Amiodarone was administered to three ex vivo circuit configurations (n = 3 per configuration) to determine the effect of each circuit component on drug extraction. The circuits were primed with human blood; standard amiodarone doses were administered; and serial samples were collected over 24 hours. Additional circuits were primed with crystalloid fluid to analyze the effect of blood on extraction and to investigate circuit saturation by drug. The crystalloid circuits were dosed multiple times over 72 hours, including a massive dose at 48 hours. For both setups, the flow was set to 1 L/min. Drug was added to separate tubes containing the prime solution to serve as controls. Drug concentrations were quantified with a validated assay, and drug recovery was calculated for each sample. Mean recovery for the circuits and controls were compared to correct for drug degradation over time. Amiodarone was heavily extracted by all ECMO circuit configurations. Eight hours after dosing, mean recovery in the blood prime circuits was 13.5-22.1%. In the crystalloid prime circuits, drug recovery decreased even more rapidly, with a mean recovery of 22.0% at 30 minutes. Similarly, drug recovery decreased more quickly in the crystalloid prime controls than in the blood prime controls. Saturation was not achieved in the crystalloid prime circuits, as final amiodarone concentrations were at the lower limit of quantification. The results suggest that amiodarone is rapidly extracted by the ECMO circuit and that saturation is not achieved by standard doses. In vivo circuit extraction may cause decreased drug exposure.

Optimal Dosing of Meropenem in a Small Cohort of Critically Ill Children Receiving Continuous Renal Replacement Therapy.

Severe sepsis is an important cause of mortality and morbidity in critically ill children. Meropenem is a broad-spectrum antibiotic commonly used to treat sepsis. Current meropenem dosage recommendations for children on continuous renal replacement therapy are extrapolated from pharmacokinetic (PK) studies done in adults. Our study aims to determine the optimal dosing in critically ill septic children receiving continuous renal replacement therapy. A prospective single-center PK study was performed in 9 children in the intensive care unit on continuous renal replacement therapy. Meropenem concentrations were measured from blood and effluent fluid samples. A population PK model was developed using nonlinear mixed-effects modeling software (NONMEM, AstraZeneca UK Ltd, Cheshire, UK). Monte Carlo simulations were performed. The PK/pharmacodynamic target aimed for plasma concentrations above minimum inhibitory concentration of 4 mg/L for 100% of dosing interval (100%ƒT>MIC ). A 2-compartment model best characterized meropenem PK. Mean (range) clearance and elimination half-life was 0.091 L/h/kg (0.04-0.157) and 3.9 hours (2.1-7.5), respectively. Dosing of 40 mg/kg/dose every 12 hours over 30 minutes achieved PK/PD target in only 32% while 20 mg/kg every 8 hours over 4 hours or 40 mg/kg every 8 hours over 2 hours achieved 100% ƒT>MIC target for at least 90% of simulated patients.

Dexmedetomidine Use in Infants Undergoing Cooling Due to Neonatal Encephalopathy (DICE Trial): A Randomized Controlled Trial: Background, Aims and Study Protocol.

Background: Neonatal hypoxia-ischemia encephalopathy (HIE) is the leading cause of neonatal death and poor neurodevelopmental outcomes worldwide. Therapeutic hypothermia (TH), while beneficial, still leaves many HIE treated infants with lifelong disabilities. Furthermore, infants undergoing TH often require treatment for pain and agitation which may lead to further brain injury. For instance, morphine use in animal models has been shown to induce neuronal apoptosis. Dexmedetomidine is a potent α2-adrenergic receptor agonist that may be a better alternative to morphine for newborns with HIE treated with TH. Dexmedetomidine provides sedation, analgesia, and prevents shivering but does not suppress ventilation. Importantly, there is increasing evidence that dexmedetomidine has neuroprotective properties. Even though there are limited data on pharmacokinetics (PK), safety and efficacy of dexmedetomidine in infants with HIE, it has been increasingly administered in many centers. Objectives: To review the current approach to treatment of pain, sedation and shivering in infants with HIE undergoing TH, and to describe a new phase II safety and pharmacokinetics randomized controlled trial that proposes the use of dexmedetomidine vs. morphine in this population. Methods: This article presents an overview of the current management of pain and sedation in critically ill infants diagnosed with HIE and undergoing TH for 72 h. The article describes the design and methodology of a randomized, controlled, unmasked multicenter trial of dexmedetomidine vs. morphine administration enrolling 50 (25 per arm) neonates ≥36 weeks of gestation with moderate or severe HIE undergoing TH and that require pain/sedation treatment. Results and Conclusions: Dexmedetomidine may be a better alternative to morphine for the treatment of pain and sedation in newborns with HIE treated with TH. There is increasing evidence that dexmedetomidine has neuroprotective properties in several preclinical studies of injury models including ischemia-reperfusion, inflammation, and traumatic brain injury as well as adult clinical trials of brain trauma. The Dexmedetomidine Use in Infants undergoing Cooling due to Neonatal Encephalopathy (DICE) trial will evaluate whether administration of dexmedetomidine vs. morphine is safe, establish dexmedetomidine optimal dosing by collecting opportunistic PK data, and obtain preliminary neurodevelopmental data to inform a large Phase III efficacy trial with long term neurodevelopment impairment as the primary outcome.

Predicting Resolvin D1 Pharmacokinetics in Humans with Physiologically-Based Pharmacokinetic Modeling.

Sjögren's syndrome (SS) is an autoimmune disease with no effective treatment options. Resolvin D1 (RvD1) belongs to a class of lipid-based specialized pro-resolving mediators that showed efficacy in preclinical models of SS. We developed a physiologically-based pharmacokinetic (PBPK) model of RvD1 in mice and optimized the model using plasma and salivary gland pharmacokinetic (PK) studies performed in NOD/ShiLtJ mice with SS-like features. The predictive performance of the PBPK model was also evaluated with two external datasets from the literature reporting RvD1 PKs. The PBPK model adequately captured the observed concentrations of RvD1 administered at different doses and in different species. The PKs of RvD1 in virtual humans were predicted using the verified PBPK model at various doses (0.01-10 mg/kg). The first-in-human predictions of RvD1 will be useful for the clinical trial design and translation of RvD1 as an effective treatment strategy for SS.