Sampling Schedule Research Articles

Effect of Different Sampling Schedules on Results of Bioavailability and Bioequivalence Studies: Evaluation by Means of Monte Carlo Simulations.

Bioavailability and bioequivalence study is one of the most frequently performed investigations in clinical trials. Bioequivalence testing is based on the assumption that 2 drug products will be therapeutically equivalent when they are equivalent in the rate and extent to which the active drug ingredient or therapeutic moiety is absorbed and becomes available at the site of drug action. In recent years there has been a significant growth in published papers that use in silico studies based on mathematical simulations to analyze pharmacokinetic and pharmacodynamic properties of drugs, including bioavailability and bioequivalence aspects. The goal of this study is to evaluate the usefulness of in silico studies as a tool in the planning of bioequivalence, bioavailability and other pharmacokinetic assays, e.g., to determine an appropriate sampling schedule. Monte Carlo simulations were used to define adequate blood sampling schedules for a bioequivalence assay comparing 2 different formulations of cefadroxil oral suspensions. In silico bioequivalence studies comparing different formulation of cefadroxil oral suspensions using various sampling schedules were performed using models. An in vivo study was conducted to confirm in silico results. The results of in silico and in vivo bioequivalence studies demonstrated that schedules with fewer sampling times are as efficient as schedules with larger numbers of sampling times in the assessment of bioequivalence, but only if Tmax is included as a sampling time. It was also concluded that in silico studies are useful tools in the planning of bioequivalence, bioavailability and other pharmacokinetic in vivo assays.

In vivo and in vitro ageing results in accumulation of de novo copy number variations in bulls

We have identified de novo copy number variations (CNVs) generated in bulls as they age. Blood samples from eight bulls were collected and SNP arrayed in a prospective design over 30 months allowing us to differentiate de novo CNVs from constant CNVs that are present throughout the sampling period. Quite remarkably, the total number of CNVs doubled over the 30-month period, as we observed an almost equal number of de novo and constant CNVs (107 and 111, respectively, i.e. 49% and 51%). Twice as many de novo CNVs emerged during the second half of the sampling schedule as in the first part. It suggests a dynamic generation of de novo CNVs in the bovine genome that becomes more frequent as the age of the animal progresses. In a second experiment de novo CNVs were detected through in vitro ageing of bovine fibroblasts by sampling passage #5, #15 and #25. De novo CNVs also became more frequent, but the proportion of them was only ~25% of the total number of CNVs (21 out of 85). Temporal generation of de novo CNVs resulted in increasing genome coverage. Genes and quantitative trait loci overlapping de novo CNVs were further investigated for ageing related functions.

FPCA-based Method to Select Optimal Sampling Schedules That Capture Between-subject Variability in Longitudinal Studies

A critical component of longitudinal study design involves determining the sampling schedule. Criteria for optimal design often focus on accurate estimation of the mean profile, although capturing the between-subject variance of the longitudinal process is also important since variance patterns may be associated with covariates of interest or predict future outcomes. Existing design approaches have limited applicability when one wishes to optimize sampling schedules to capture between-individual variability. We propose an approach to derive optimal sampling schedules based on functional principal component analysis (FPCA), which separately characterizes the mean and the variability of longitudinal profiles and leads to a parsimonious representation of the temporal pattern of the variability. Simulation studies show that the new design approach performs equally well compared to an existing approach based on parametric mixed model (PMM) when a PMM is adequate for the data, and outperforms the PMM-based approach otherwise. We use the methods to design studies aiming to characterize daily salivary cortisol profiles and identify the optimal days within the menstrual cycle when urinary progesterone should be measured.

Experiment Design for Early Molecular Events in HIV Infection.

The recent introduction of integrase inhibitors to the HIV antiviral repertoire permits us to create in vitro experiments that reliably terminate HIV infection at the point of chromosomal integration. This allows us to isolate the dynamics of a single round of infection, without needing to account for the influence of multiple overlapping rounds of infection. By measuring the various nucleic acid concentrations in a population of infected target cells at multiple time points, we can infer the rates of these molecular events with great accuracy, which allows us to compare the rates between target cells with different functional phenotypes. This information will help in understanding the behavior of the various populations of reservoir cells such as active and quiescent T-cells which maintain HIV infection in treated patients. In this paper, we introduce a family of models of the early molecular events in HIV infection, with either linear dynamics or age-structured delays at each step. We introduce an experimental design metric based on the delta AIC (Akaike Information Criteria) between a model fit for simulated data from a matching model vs a mismatched model, which allows us to determine a candidate experiment design's ability to discriminate between models. Using parameters values drawn from experimentally-derived priors corrupted with appropriate measurement noise, we confirm that a proposed sampling schedule at different time points allows us to consistently discriminate between candidate models.

Age, Weight, and CYP2D6 Genotype Are Major Determinants of Primaquine Pharmacokinetics in African Children.

ABSTRACTLow-dose primaquine is recommended to prevent Plasmodium falciparum malaria transmission in areas threatened by artemisinin resistance and areas aiming for malaria elimination. Community treatment campaigns with artemisinin-based combination therapy in combination with the gametocytocidal primaquine dose target all age groups, but no studies thus far have assessed the pharmacokinetics of this gametocytocidal drug in African children. We recruited 40 children participating in a primaquine efficacy trial in Burkina Faso to study primaquine pharmacokinetics. These children received artemether-lumefantrine and either a 0.25- or a 0.40-mg/kg primaquine dose. Seven blood samples were collected from each participant for primaquine and carboxy-primaquine plasma levels determinations: one sample was collected before primaquine administration and six after primaquine administration according to partially overlapping sampling schedules. Physiological population pharmacokinetic modeling was used to assess the impact of weight, age, and CYP2D6 genotype on primaquine and carboxy-primaquine pharmacokinetics. Despite linear weight normalized dosing, the areas under the plasma concentration-time curves and the peak concentrations for both primaquine and carboxy-primaquine increased with age and body weight. Children who were CYP2D6 poor metabolizers had higher levels of the parent compound, indicating a lower primaquine CYP2D6-mediated metabolism. Our data indicate that primaquine and carboxy-primaquine pharmacokinetics are influenced by age, weight, and CYP2D6 genotype and suggest that dosing strategies may have to be reconsidered to maximize the transmission-blocking properties of primaquine. (This study has been registered at ClinicalTrials.gov under registration no. NCT01935882.)

The effect of using a robust optimality criterion in model based adaptive optimization

Optimizing designs using robust (global) optimality criteria has been shown to be a more flexible approach compared to using local optimality criteria. Additionally, model based adaptive optimal design (MBAOD) may be less sensitive to misspecification in the prior information available at the design stage. In this work, we investigate the influence of using a local (lnD) or a robust (ELD) optimality criterion for a MBAOD of a simulated dose optimization study, for rich and sparse sampling schedules. A stopping criterion for accurate effect prediction is constructed to determine the endpoint of the MBAOD by minimizing the expected uncertainty in the effect response of the typical individual. 50 iterations of the MBAODs were run using the MBAOD R-package, with the concentration from a one-compartment first-order absorption pharmacokinetic model driving the population effect response in a sigmoidal EMAX pharmacodynamics model. The initial cohort consisted of eight individuals in two groups and each additional cohort added two individuals receiving a dose optimized as a discrete covariate. The MBAOD designs using lnD and ELD optimality with misspecified initial model parameters were compared by evaluating the efficiency relative to an lnD-optimal design based on the true parameter values. For the explored example model, the MBAOD using ELD-optimal designs converged quicker to the theoretically optimal lnD-optimal design based on the true parameters for both sampling schedules. Thus, using a robust optimality criterion in MBAODs could reduce the number of adaptations required and improve the practicality of adaptive trials using optimal design.

Evaluation of a Reduced Sampling Schedule for Assessment of Pancreatic Beta‐Cell Function with the Intravenous Glucose Tolerance Test During a Dietary Intervention

Pancreatic beta‐cell function is a key determinant of glucose tolerance. The intravenous glucose tolerance test (IVGTT) can be used to assess both the insulin sensitivity index (Si) and the acute insulin response to glucose (AIRg). The disposition index (DI = Si × AIRg) reflects the adequacy of pancreatic beta‐cell response for the level of insulin sensitivity. The aim of this analysis was to compare the AIRg and DI values calculated using a reduced early test sampling schedule (t = 0, 5, 10 min), to those from the full sampling schedule (t = 0, 3, 5, 7, and 10 min). Participants included men (n = 8) and women (n = 16) with mean (SD) age 48.9 (9.9) y and body mass index 30.8 (4.9) kg/m2. Subjects consumed 0, 15, and 30 g/d high‐amylose resistant starch (RS) for 4 weeks each, in a double‐blind, randomized, crossover trial, and underwent a 180‐min IVGTT at the end of each treatment period. The Minmod Millenium program was used to derive Si. AIRg was calculated as the mean increment in plasma insulin during the first 10 min of the test for the full and reduced sampling schedules. The median (interquartile range) full schedule AIRg values during the control, 15, and 30 g/d RS conditions were 43 (29, 103), 47 (23, 67) and 44 (30, 94) mU/L, respectively. Mean (95% confidence interval) percentages of the full schedule values for the reduced schedule values were 82 (79–86), 87 (76–98) and 83 (80–85) for the control, 15 and 30 g/d RS conditions, respectively, all p < 0.05 vs. the full schedule. Correlations between the AIRg and DI values from the two schedules during each RS condition were high (Pearson r values all ≥0.98, p < 0.001). Thus, although AIRg and DI values cannot be directly compared between sampling schedules, the reduced sampling schedule accurately reflects relative AIRg and DI values, and may thus be a time and cost‐effective option when conducting the IVGTT in clinical and epidemiological studies.Support or Funding InformationIngredion Inc., Westchester, IL

Scheduling multiple, resource-constrained, iterative, product development projects with genetic algorithms

Many product development (PD) projects rely on a common pool of scarce resources. In addition to resource constraints, there are precedence constraints among activities within each project. Beyond the feed-forward dependencies among activities, in PD projects it is common for feedback dependencies to exist that can result in activity rework or iteration.In such a multi-project, resource-constrained, iterative environment, this paper proposes two new genetic algorithm (GA) approaches for scheduling project activities. The objective is to minimize the overall duration of the portfolio of PD projects. These proposed GAs are tested on sample scheduling problems with and without stochastic feedback. We show that these algorithms provide quick convergence to a globally optimal solution.Furthermore, we conducted a comparative analysis of the proposed GAs with 31 published priority rules (PRs), using test problems generated to the specifications of project, activity, and resource-related characteristics such as network density (complexity), resource distribution, resource contention, and rework probability (amount of iteration). The GAs performed better than the PRs as each of these factors increased. We close the paper by providing managers with a decision matrix showing when it is best to use the published PRs and when it is best to use the GAs.

Temporal variations in water quality in a brackish tidal pond: Implications for governing processes and management strategies

Brackish tidal ponds have been constructed along coastal areas in many parts of the world for aquaculture, including some Ramsar Sites. Such ponds are considered a sustainable, wise use of wetlands if managed properly, but they can also pose serious environmental problems if mismanaged. To understand the governing processes and to promote sustainable management strategies, this study examines the different temporal variations in water quality parameters in a brackish tidal pond located within the wetland complex of the Mai Po Ramsar Site in Hong Kong, China. The variations are compared with those of the receiving bay, and the water channel that connects the pond and the bay. Equations are then developed to link the dissolved oxygen (DO) concentrations in the pond with the governing processes, and to analyze their relative contributions to DO levels. Field data show seasonal patterns in water temperature and salinity in response to the seasonal variations in solar radiation and rainfall. For the pond and the channel, DO, chlorophyll and pH exhibit fortnightly variations due to the bi-weekly water exchange between the pond and the bay. There were also diurnal variations in water temperature and DO in response to changes in solar radiation for both locations, and the tidal flushing for the water channel. Analysis of the findings indicates that water exchange influences the DO concentration more strongly than solar radiation. The DO equation links pond water quality with the time of day, and the time in a water exchange cycle, and thus provides some guidance for determining water exchange and water sampling schedules. The study sheds light on the governing processes and management strategies related to the sustainable management of a brackish tidal pond. The results are thus beneficial in elucidating and promoting the sustainable management and wise use of wetlands in other locations.

A Toolkit for Nursing Clinical Instructors

Many nursing clinical instructors enter into the role without any teaching experience. This article outlines a toolkit for new clinical faculty based on in-the-trenches teaching knowledge, including sample schedules and handouts that are ready to implement. It also offers concrete suggestions for instructor preparation, organization, and collaboration with hospital staff.

Dissipation of Chlorpyrifos in a Malaysian Agricultural Soil: A Comparison between a Field Experiment and Simulation by the VARLEACH and PERSIST Models

A comparison of the dissipation of chlorpyrifos in a Malaysian agricultural soil was undertaken using data from a field experiment and simulation by the PERSIST model. The study was carried out at an oil palm estate located close to the Kuala Lumpur International Airport (KLIA), Sepang, Selangor (for field experiment). The plots were treated with chlorpyrifos at the manufacturer’s recommended dosage. Soil samples were collected according to the sampling schedule at intervals of 0, 1, 3, 7, 14, 21, 30, 60 and 90 days. Residues of chlorpyrifos in soil from the field trial were analyzed in the laboratory. Simulation of chlorpyrifos leaching and persistency was done using two computer-run software VARLEACH and PERSIST. Generally, predicted data for chlorpyrifos residue obtained using the VARLEACH and PERSIST models was found to be well matched with the observed data from the field trial. The PERSIST Prediction for chlorpyrifos residue in soils planted with oil palm trees was found to be accurate and conformed to the results observed in the field trial.

Semi-global output feedback nonlinear stabilization of variable speed grid connected direct drive wind turbine generator systems

The goal of the present work is to achieve nonlinear semi-global output feedback stabilization of variable speed grid connected direct drive wind turbine generator DDWTG systems under wind energy conversion systems to provide the electricity demand for electrical networks. The study will address the sensorless control of variable speed wind energy generation systems, namely optimized rotor speed and direct-axis current control to determine the most appropriate structure and to improve both robustness and reliability of this kind of distributed generators. The proposed nonlinear observer is robust with respect to measurements error and perturbations of the sampling schedule. The simulation results of the case study support the presented main theorem that reflects the effect of measurement errors and the improvement with respect to global convergence properties. The novelty of the present study resides in taking into account the difficulties and control problem complexity that faced the nonlinear output feedback control undergo: (i) the proposed system nonlinearity and loss the observability of sensorless PMSG near the singularity point of the rotor speed; (ii) inaccessibility measurements for all system state variables; (iii) maximum power point tracking of optimum reference angular rotor speed; (IV) magnetizing and demagnetizing direct-axis current at standstill; (V) the proposed semi-global observer has dynamic high-gain design parameter DHGO. The simulation results of variable speed grid connected DDWTG, in general, confirm the main theorem developed under DHGO parameter and lead us to enlarge and prolongation the admissible sampling period using nonlinear Lyapunov stability control techniques.

Data Analysis Protocol for the Development and Evaluation of Population Pharmacokinetic Models for Incorporation Into the Web-Accessible Population Pharmacokinetic Service - Hemophilia (WAPPS-Hemo).

BackgroundHemophilia is an inherited bleeding disorder caused by a deficiency in a specific clotting factor. This results in spontaneous bleeding episodes and eventual arthropathy. The mainstay of hemophilia treatment is prophylactic replacement of the missing factor, but an optimal regimen remains to be determined. Rather, individualized prophylaxis has been suggested to improve both patient safety and resource utilization. However, uptake of this approach has been hampered by the demanding sampling schedules and complex calculations required to obtain individual estimates of pharmacokinetic (PK) parameters. The use of population pharmacokinetics (PopPK) can alleviate this burden by reducing the number of plasma samples required for accurate estimation, but few tools incorporating this approach are readily available to clinicians.ObjectiveThe Web-accessible Population Pharmacokinetic Service - Hemophilia (WAPPS-Hemo) project aims to bridge this gap by providing a Web-accessible service for the reliable estimation of individual PK parameters from only a few patient samples. This service is predicated on the development of validated brand-specific PopPK models.MethodsWe describe the data analysis plan for the development and evaluation of each PopPK model to be incorporated into the WAPPS-Hemo platform. The data sources and structure of the dataset are discussed first, followed by the procedures for handling both data below limit of quantification (BLQ) and absence of such BLQ data. Next, we outline the strategies for building the appropriate structural and covariate models, including the possible need for a process algorithm when PK behavior varies between subjects or significant covariates are not provided. Prior to use in a prospective manner, the models will undergo extensive evaluation using a variety of techniques such as diagnostic plots, bootstrap analysis and cross-validation. Finally, we describe the incorporation of a validated PopPK model into the Bayesian post hoc model to produce individualized estimates of PK parameters.ResultsDense PK data has been collected for more than 20 brands of factor concentrate from both industry-sponsored and investigator-driven studies. The model development process is underway for the majority of molecules, with refinement and validation to be completed in 2017. Further, the WAPPS-Hemo co-investigator network has contributed more than 300 PK assessments for use in model development and evaluation. This constitutes the largest repository of this type of PK data globally.ConclusionsThe WAPPS-Hemo service aims to eliminate barriers to the uptake of individualized PK-tailored hemophilia treatment. By incorporating this tool into routine practice, clinicians can implement a personalized dosing strategy without performing rigorous sampling or complex calculations. This service is centred on validated models developed according to the robust approach to PopPK modeling described herein.ClinicalTrialClinicalTrials.gov NCT02061072; https://clinicaltrials.gov/ct2/show/NCT02061072 (Archived by WebCite at http://www.webcitation.org/6mRIXJh55)

Pharmacodynamic Profile of a Recombinant ADAMTS13 (BAX930) in Hereditary Thrombotic Thrombocytopenic Purpura (Upshaw-Schulman Syndrome (USS))

Pharmacodynamic Profile of a Recombinant ADAMTS13 (BAX930) in Hereditary Thrombotic Thrombocytopenic Purpura (Upshaw-Schulman Syndrome (USS))

Vzhe-039, a Novel Structurally-Enhanced Allosteric Hemoglobin Effector Inhibits Sickling of SS Erythrocytes In Vitro, and Exhibits Improved Pharmacologic Properties In Vivo

Allosteric effectors of hemoglobin (AEH) remain promising as a viable therapeutic approach for the management of sickle cell disease (SCD). AEH bind to hemoglobin (Hb) in a transiently covalently manner, increasing Hb affinity for oxygen (O2), with concomitant inhibition of polymerization of deoxygenated sickle Hb (HbS) and erythrocyte sickling. As part of our ongoing efforts to surmount well-known AEH druggability challenges, we have designed and synthesized VZHE-039, a novel substituted benzaldehyde with potent in-vitro anti-polymerization activity, as well as more favorable in-vivopharmacokinetic and pharmacodynamic (PK/PD) properties. Here, we report the results of our early findings.The anti-sickling properties of VZHE-039 were tested in-vitro by incubating 0.5, 1, and 2 mM concentrations with blood suspensions from a subject with homozygous SCD (hematocrit: 20%) under hypoxic conditions (4% O2/96% N2) at 37°C for 2 h. At conclusion, aliquots were drawn into a fixative (2% glutaraldehyde solution), and sickling was assessed by microscopy. Aliquot samples were also subjected to cation-exchange HPLC analyses to measure the degree of Hb modification (Hb adduct formation), as well as standard O2 equilibrium curves (OEC) to assess p50 shifts. Subsequently, we conducted in-vivo PK/PD studies in wild-type mice that received single doses of VZHE-039 via the intravenous (I.V.: 25 and 50 mg/kg), intraperitoneal (I.P.: 100-150 mg/kg) and oral (P.O.: 100-200 mg/kg) routes. Serial blood samples were collected up to 24 h after I.V. and P.O., and up to 6 h after I.P. administration, respectively; aliquots were hemolyzed, de-proteinized and subjected to reverse-phase HPLC-UV assay to quantify VZH-039 blood concentrations. Residual blood samples were also hemolyzed, and clarified lysates were assayed for in-vivoHb adduct formation, and the corresponding change in Hb oxygen affinity (Δp50, %).The results of our in-vitrostudies demonstrated a concentration-dependent inhibition of SS cell sickling: 39±1.4%, 68.6±4.9%, and 89.9±5.2%, at 0.5, 1 and 2 mM of VZHE-039, respectively. HbS was modified correspondingly (46±7.4%, 83.6±6.4%, and 96.4±6.2%), and this adduct formation was correlated linearly with the left shift in OEC (Δp50 values of 34.3±8.7%, 63.6±2.4%, and 76.6±2.5%).Noncompartmental PK analysis showed that, after I.V. administration, systemic PK was dose-independent with a CLtot of 0.5 mL/min/kg, resulting in a terminal half-life of 9 h. After I.P. administration, AUCtrap increased supra-proportionally with dose; the limited sampling schedule suggested an I.P. bioavailability of >20%. After P.O. administration, AUCtrap increased supra-proportionally with dose as well due to an increase in oral bioavailability to ~ 10%, with peak blood concentrations up to ~ 0.25 mM; the terminal half-lives were prolonged (relative to I.V.) to 14 h. The PD effect-time course of change in %Hb adduct paralleled (and was reasonably linearly related to) blood concentrations for all routes. Baseline-corrected peak PD effects after I.V. administration were 15.7% and 31.9%, after 25 and 50 mg/kg respectively; after P.O. administration of 200 mg/kg, the peak change was 17.6%. Overall, VZHE-039 exhibited a low (metabolic) clearance, presumably reflecting high-affinity and sustained Hb (and possibly albumin) binding, leading to the observed extended terminal half-life and duration of action. While its oral bioavailability is low (likely due to limited GI solubility) and there is evidence of saturable first-pass effects and possibly enterohepatic recycling, oral in-vivo exposures were associated with PD effects that were consistent with the results from the in-vitrostudies.In conclusion, the results of our current studies establish VZHE-039 as a novel, potent anti-sickling agent, confirm its proposed mechanism of action in-vitro and in-vivo, and suggest that therapeutically-relevant blood concentrations may be achieved after daily oral doses. Therefore, VZHE-039 is our new lead drug candidate that may require further modifications and studies to (a) improve its GI solubility and oral bioavailability; (b) elucidate atomic level structural interactions and kinetics of its Hb binding; and (c) formally investigate its biological activity after repeat-doses in a SCD mouse model. DisclosuresNo relevant conflicts of interest to declare.

The effect of Fisher information matrix approximation methods in population optimal design calculations.

With the increasing popularity of optimal design in drug development it is important to understand how the approximations and implementations of the Fisher information matrix (FIM) affect the resulting optimal designs. The aim of this work was to investigate the impact on design performance when using two common approximations to the population model and the full or block-diagonal FIM implementations for optimization of sampling points. Sampling schedules for two example experiments based on population models were optimized using the FO and FOCE approximations and the full and block-diagonal FIM implementations. The number of support points was compared between the designs for each example experiment. The performance of these designs based on simulation/estimations was investigated by computing bias of the parameters as well as through the use of an empirical D-criterion confidence interval. Simulations were performed when the design was computed with the true parameter values as well as with misspecified parameter values. The FOCE approximation and the Full FIM implementation yielded designs with more support points and less clustering of sample points than designs optimized with the FO approximation and the block-diagonal implementation. The D-criterion confidence intervals showed no performance differences between the full and block diagonal FIM optimal designs when assuming true parameter values. However, the FO approximated block-reduced FIM designs had higher bias than the other designs. When assuming parameter misspecification in the design evaluation, the FO Full FIM optimal design was superior to the FO block-diagonal FIM design in both of the examples.

Improving resolution in multidimensional NMR using random quadrature detection with compressed sensing reconstruction

NMR spectroscopy is central to atomic resolution studies in biology and chemistry. Key to this approach are multidimensional experiments. Obtaining such experiments with sufficient resolution, however, is a slow process, in part since each time increment in every indirect dimension needs to be recorded twice, in quadrature. We introduce a modified compressed sensing (CS) algorithm enabling reconstruction of data acquired with random acquisition of quadrature components in gradient-selection NMR. We name this approach random quadrature detection (RQD). Gradient-selection experiments are essential to the success of modern NMR and with RQD, a 50 % reduction in the number of data points per indirect dimension is possible, by only acquiring one quadrature component per time point. Using our algorithm (CSRQD), high quality reconstructions are achieved. RQD is modular and combined with non-uniform sampling we show that this provides increased flexibility in designing sampling schedules leading to improved resolution with increasing benefits as dimensionality of experiments increases, with particular advantages for 4- and higher dimensional experiments.

Target attainment analysis and optimal sampling designs for population pharmacokinetic study on piperacillin/tazobactam in neonates and young infants.

Population pharmacokinetic (popPK) analyses for piperacillin/tazobactam in neonates and infants of less than 2months of age have been performed by our group previously. The results indicate that a dose of 44.44/5.56mg/kg piperacillin/tazobactam every 8 or 12h may not be enough for controlling infection in this population. In order to determine the appropriate dosing regimen and to provide a rationale for the development of dosing guidelines suitable for this population, further popPK studies of piperacillin/tazobactam would need to be conducted. The aim of the present study was to determine the appropriate dosing regimen and optimal sampling schedules in neonates and infants of less than 2months of age. Pharmacodynamic profiling of piperacillin using Monte Carlo simulation was performed to explore the target attainment probability of different dosing regimens for infections caused by different isolated pathogens. D-optimal designs for piperacillin and tazobactam were conducted separately, and the times that overlapped were chosen as the final sampling scheme for future popPK studies in neonates and young infants of less than 2months of age. Our findings revealed that compared to the current empirical piperacillin/tazobactam dose regimen (50mg/kg every 12h by 5-min infusion in our hospital), the clinical outcome could be improved by increasing doses, increasing administration frequency, and prolonging intravenous infusion in neonates and infants of less than 2months of age. The following optimal sampling windows were chosen as the final sampling scheme: 0.1-0.11, 0.26-0.29, 0.97-2.62, and 7.95-11.9h administered every 12h with 5-min infusion; 0.1-0.12, 0.39-0.56, 2.86-4.95, and 8.91-11.8h administered every 12h with 3-h infusion; 0.1-0.11, 0.22-0.29, 0.91-1.96, and 5.56-7.93h administered every 8h with 5-min infusion; 0.1-0.11, 0.38-0.48, 2.54-3.82, and 6.86-7.93h administered every 8h with 3-h infusion; 0.1-0.11, 0.25-0.28, 0.84-1.69, and 4.55-5.94h administered every 6h with 5-min infusion; and 0.1-0.11, 0.37-0.54, 3.13-3.72, and 5.57-5.99h administered every 6h with 3-h infusion. The dosing regimen and sampling schedules proposed in this study should be evaluated in future popPK studies of piperacillin/tazobactam in neonates and infants. To the best of our knowledge, this is the first study that combined optimal sampling design with Monte Carlo simulation for designing popPK studies of piperacillin/tazobactam.

Time-integrated activity coefficient estimation for radionuclide therapy using PET and a pharmacokinetic model: A simulation study on the effect of sampling schedule and noise.

The aim of this study was to investigate the accuracy of PET-based treatment planning for predicting the time-integrated activity coefficients (TIACs). The parameters of a physiologically based pharmacokinetic (PBPK) model were fitted to the biokinetic data of 15 patients to derive assumed true parameters and were used to construct true mathematical patient phantoms (MPPs). Biokinetics of 150 MBq (68)Ga-DOTATATE-PET was simulated with different noise levels [fractional standard deviation (FSD) 10%, 1%, 0.1%, and 0.01%], and seven combinations of measurements at 30 min, 1 h, and 4 h p.i. PBPK model parameters were fitted to the simulated noisy PET data using population-based Bayesian parameters to construct predicted MPPs. Therapy simulations were performed as 30 min infusion of (90)Y-DOTATATE of 3.3 GBq in both true and predicted MPPs. Prediction accuracy was then calculated as relative variability vorgan between TIACs from both MPPs. Large variability values of one time-point protocols [e.g., FSD = 1%, 240 min p.i., vkidneys = (9 ± 6)%, and vtumor = (27 ± 26)%] show inaccurate prediction. Accurate TIAC prediction of the kidneys was obtained for the case of two measurements (1 and 4 h p.i.), e.g., FSD = 1%, vkidneys = (7 ± 3)%, and vtumor = (22 ± 10)%, or three measurements, e.g., FSD = 1%, vkidneys = (7 ± 3)%, and vtumor = (22 ± 9)%. (68)Ga-DOTATATE-PET measurements could possibly be used to predict the TIACs of (90)Y-DOTATATE when using a PBPK model and population-based Bayesian parameters. The two time-point measurement at 1 and 4 h p.i. with a noise up to FSD = 1% allows an accurate prediction of the TIACs in kidneys.

Assessing the impact of fine particulate matter (PM2.5) on respiratory-cardiovascular chronic diseases in the New York City Metropolitan area using Hierarchical Bayesian Model estimates

An enhanced research paradigm is presented to address the spatial and temporal gaps in fine particulate matter (PM2.5) measurements and generate realistic and representative concentration fields for use in epidemiological studies of human exposure to ambient air particulate concentrations. The general approach for research designed to analyze health impacts of exposure to PM2.5 is to use concentration data from the nearest ground-based air quality monitor(s), which typically have missing data on the temporal and spatial scales due to filter sampling schedules and monitor placement, respectively. To circumvent these data gaps, this research project uses a Hierarchical Bayesian Model (HBM) to generate estimates of PM2.5 in areas with and without air quality monitors by combining PM2.5 concentrations measured by monitors, PM2.5 concentration estimates derived from satellite aerosol optical depth (AOD) data, and Community-Multiscale Air Quality (CMAQ) model predictions of PM2.5 concentrations. This methodology represents a substantial step forward in the approach for developing representative PM2.5 concentration datasets to correlate with inpatient hospitalizations and emergency room visits data for asthma and inpatient hospitalizations for myocardial infarction (MI) and heart failure (HF) using case-crossover analysis. There were two key objective of this current study. First was to show that the inputs to the HBM could be expanded to include AOD data in addition to data from PM2.5 monitors and predictions from CMAQ. The second objective was to determine if inclusion of AOD surfaces in HBM model algorithms results in PM2.5 air pollutant concentration surfaces which more accurately predict hospital admittance and emergency room visits for MI, asthma, and HF. This study focuses on the New York City, NY metropolitan and surrounding areas during the 2004–2006 time period, in order to compare the health outcome impacts with those from previous studies and focus on any benefits derived from the changes in the HBM model surfaces. Consistent with previous studies, the results show high PM2.5 exposure is associated with increased risk of asthma, myocardial infarction and heart failure. The estimates derived from concentration surfaces that incorporate AOD had a similar model fit and estimate of risk as compared to those derived from combining monitor and CMAQ data alone. Thus, this study demonstrates that estimates of PM2.5 concentrations from satellite data can be used to supplement PM2.5 monitor data in the estimates of risk associated with three common health outcomes. Results from this study were inconclusive regarding the potential benefits derived from adding AOD data to the HBM, as the addition of the satellite data did not significantly increase model performance. However, this study was limited to one metropolitan area over a short two-year time period. The use of next-generation, high temporal and spatial resolution satellite AOD data from geostationary and polar-orbiting satellites is expected to improve predictions in epidemiological studies in areas with fewer pollutant monitors or over wider geographic areas.