AIMSOne barrier contributing to the lack of pharmacokinetic (PK) data in paediatric populations is the need for serial sampling. Analysis of clinically obtained specimens and data may overcome this barrier. To add evidence for the feasibility of this approach, we sought to determine PK parameters for fentanyl in children after cardiac surgery using specimens and data generated in the course of clinical care, without collecting additional blood samples. METHODSWe measured fentanyl concentrations in plasma from leftover clinically-obtained specimens in 130 paediatric cardiac surgery patients and successfully generated a PK dataset using drug dosing data extracted from electronic medical records. Using a population PK approach, we estimated PK parameters for this population, assessed model goodness-of-fit and internal model validation, and performed subset data analyses. Through simulation studies, we compared predicted fentanyl concentrations using model-driven weight-adjusted per kg vs. fixed per kg fentanyl dosing. RESULTSFentanyl clearance for a 6.4 kg child, the median weight in our cohort, is 5.7 l h -1 (2.2-9.2 l h -1 ), similar to values found in prior formal PK studies. Model assessment and subset analyses indicated the model adequately fit the data. Of the covariates studied, only weight significantly impacted fentanyl kinetics, but substantial inter-individual variability remained. In simulation studies, model-driven weight-adjusted per kg fentanyl dosing led to more consistent therapeutic fentanyl concentrations than fixed per kg dosing. CONCLUSIONSWe show here that population PK modelling using sparse remnant samples and electronic medical records data provides a powerful tool for assessment of drug kinetics and generation of individualized dosing regimens.

Cardiovascular drugs are the most commonly prescribed medications. Some prior assays successfully detect cardiovascular drugs among multiple classes using a single sample. Here, we develop an assay to detect a broad range of cardiovascular drug classes to include commonly used cardiovascular drugs and evaluate the assay’s analytical and statistical properties in a clinical setting. We describe a protocol for drug detection that encompasses 34 commonly prescribed cardiovascular drugs or drug metabolites with a single LC-MS/MS method using 100µl of serum or plasma. Drug classes monitored by this assay include: anticoagulants, angiotensin converting enzyme inhibitors (ACEI), angiotensin II receptor blockers (ARB), beta blockers, calcium channel blockers, diuretics, statins, and vasodilators, as well as digoxin, fenofibrate, and niacin. Analytical accuracy and precision for each drug was evaluated by repeating the assay on spiked samples at low, medium, and high concentrations. In 294 clinical samples obtained from hospitalized patients for whom medication administration was recorded, we evaluated the assay’s statistical sensitivity, specificity, and accuracy. For the 34 drugs or drug metabolites, the assay was statistically sensitive (>0.90) for all drugs except captopril (0.25), isosorbide (0.81), and niacin (0.89). The assay was statistically specific for all drugs, with a minimum specificity of 0.94 (aspirin). To our knowledge, this method is the first method of simultaneous analysis of 34 cardiovascular drugs or drug metabolites from nine drug classes evaluated using clinical samples from hospitalized patients.

Aims: Our objectives were to perform a population pharmacokinetic analysis of dexmedetomidine in children using remnant specimens and electronic health records (EHRs) and explore the impact of patient's characteristics and pharmacogenetics on dexmedetomidine clearance. Methods: Dexmedetomidine dosing and patient data were gathered from EHRs and combined with opportunistically sampled remnant specimens. Population pharmacokinetic models were developed using nonlinear mixed-effects modelling. Stage 1 developed a model without genotype variables; Stage 2 added pharmacogenetic effects. Results: Our final study population included 354 post-cardiac surgery patients aged 0-22 years (median 16 mo). The data were best described with a 2-compartment model with allometric scaling for weight and Hill maturation function for age. Population parameter estimates and 95% confidence intervals were 27.3 L/h (24.0-31.1 L/ h) for total clearance, 161 L (139-187 L) for central compartment volume of distribution, 26.0 L/h (22.5-30.0 L/h) for intercompartmental clearance and 7903 L (5617-11 119 L) for peripheral compartment volume of distribution. The estimate for postmenstrual age when 50% of adult clearance is achieved was 42.0 weeks (41.5-42.5 weeks) and the Hill coefficient estimate was 7.04 (6.99-7.08). Genotype was not statistically or clinically significant. Conclusion:Our study demonstrates the use of real-world EHR data and remnant specimens to perform a population pharmacokinetic analysis and investigate covariate effects in a large paediatric population. Weight and age were important predictors of clearance. We did not find evidence for pharmacogenetic effects of UGT1A4 or UGT2B10 genotype or CYP2A6 risk score.

Quantitative matrix-assisted laser desorption/ionization time-of-flight (MALDI TOF) approaches have historically suffered from poor accuracy and precision mainly due to the nonuniform distribution of matrix and analyte across the target surface, matrix interferences, and ionization suppression. Tandem mass spectrometry (MS/MS) can be used to ensure chemical specificity as well as improve signal-to-noise ratios by eliminating interferences from chemical noise, alleviating some concerns about dynamic range. However, conventional MALDI TOF/TOF modalities typically only scan for a single MS/MS event per laser shot, and multiplex assays require sequential analyses. We describe here new methodology that allows for multiple TOF/TOF fragmentation events to be performed in a single laser shot. This technology allows the reference of analyte intensity to that of the internal standard in each laser shot, even when the analyte and internal standard are quite disparate in m/z, thereby improving quantification while maintaining chemical specificity and duty cycle. In the quantitative analysis of the drug enalapril in pooled human plasma with ramipril as an internal standard, a greater than 4-fold improvement in relative standard deviation (<10%) was observed as well as improved coefficients of determination (R2) and accuracy (>85% quality controls). Using this approach we have also performed simultaneous quantitative analysis of three drugs (promethazine, enalapril, and verapamil) using deuterated analogues of these drugs as internal standards.

Background: Ergothioneine (ERGO) is a unique antioxidant and a rare amino acid available in fungi and various bacteria but not in higher plants or animals. Substantial research data indicate that ERGO is a physiological antioxidant cytoprotectant. Different from other antioxidants that need to breach the blood–brain barrier to enter the brain parenchyma, a specialized transporter called OCTN1 has been identified for transporting ERGO to the brain. Purpose: To assess whether consumption of ERGO can prevent the progress of Alzheimer’s disease (AD) on young (4-month-old) 5XFAD mice. Methods and materials: Three cohorts of mice were tested in this study, including ERGO-treated 5XFAD, non-treated 5XFAD, and WT mice. After the therapy, the animals went through various behavioral experiments to assess cognition. Then, mice were scanned with PET imaging to evaluate the biomarkers associated with AD using [11C]PIB, [11C]ERGO, and [18F]FDG radioligands. At the end of imaging, the animals went through cardiac perfusion, and the brains were isolated for immunohistology. Results: Young (4-month-old) 5XFAD mice did not show a cognitive deficit, and thus, we observed modest improvement in the treated counterparts. In contrast, the response to therapy was clearly detected at the molecular level. Treating 5XFAD mice with ERGO resulted in reduced amyloid plaques, oxidative stress, and rescued glucose metabolism. Conclusions: Consumption of high amounts of ERGO benefits the brain. ERGO has the potential to prevent AD. This work also demonstrates the power of imaging technology to assess response during therapy.