Dexmedetomidine Clearance Decreases with Increasing Drug Exposure: Implications for Current Dosing Regimens and Target-controlled Infusion Models Assuming Linear Pharmacokinetics

Background Numerous pharmacokinetic models have been published aiming at more accurate and safer dosing of dexmedetomidine. The vast majority of the developed models underpredict the measured plasma concentrations with respect to the target concentration, especially at plasma concentrations higher than those used in the original studies. The aim of this article was to develop a dexmedetomidine pharmacokinetic model in healthy adults emphasizing linear versus nonlinear kinetics. Methods The data of two previously published clinical trials with stepwise increasing dexmedetomidine target-controlled infusion were pooled to build a pharmacokinetic model using the NONMEM software package (ICON Development Solutions, USA). Data from 48 healthy subjects, included in a stratified manner, were utilized to build the model. Results A three-compartment mamillary model with nonlinear elimination from the central compartment was superior to a model assuming linear pharmacokinetics. Covariates included in the final model were age, sex, and total body weight. Cardiac output did not explain between-subject or within-subject variability in dexmedetomidine clearance. The results of a simulation study based on the final model showed that at concentrations up to 2 ng · ml–1, the predicted dexmedetomidine plasma concentrations were similar between the currently available Hannivoort model assuming linear pharmacokinetics and the nonlinear model developed in this study. At higher simulated plasma concentrations, exposure increased nonlinearly with target concentration due to the decreasing dexmedetomidine clearance with increasing plasma concentrations. Simulations also show that currently approved dosing regimens in the intensive care unit may potentially lead to higher-than-expected dexmedetomidine plasma concentrations. Conclusions This study developed a nonlinear three-compartment pharmacokinetic model that accurately described dexmedetomidine plasma concentrations. Dexmedetomidine may be safely administered up to target-controlled infusion targets under 2 ng · ml–1 using the Hannivoort model, which assumed linear pharmacokinetics. Consideration should be taken during long-term administration and during an initial loading dose when following the dosing strategies of the current guidelines. Editor’s Perspective What We Already Know about This Topic What This Article Tells Us That Is New

Devil in the details: Mechanistic variations impact information transfer across models of transcriptional cascades

The transcriptional network determines a cell’s internal state by regulating protein expression in response to changes in the local environment. Due to the interconnected nature of this network, information encoded in the abundance of various proteins will often propagate across chains of noisy intermediate signaling events. The data-processing inequality (DPI) leads us to expect that this intracellular game of “telephone” should degrade this type of signal, with longer chains losing successively more information to noise. However, a previous modeling effort predicted that because the steps of these signaling cascades do not truly represent independent stages of data processing, the limits of the DPI could seemingly be surpassed, and the amount of transmitted information could actually increase with chain length. What that work did not examine was whether this regime of growing information transmission was attainable by a signaling system constrained by the mechanistic details of more complex protein-binding kinetics. Here we address this knowledge gap through the lens of information theory by examining a model that explicitly accounts for the binding of each transcription factor to DNA. We analyze this model by comparing stochastic simulations of the fully nonlinear kinetics to simulations constrained by the linear response approximations that displayed a regime of growing information. Our simulations show that even when molecular binding is considered, there remains a regime wherein the transmitted information can grow with cascade length, but ends after a critical number of links determined by the kinetic parameter values. This inflection point marks where correlations decay in response to an oversaturation of binding sites, screening informative transcription factor fluctuations from further propagation down the chain where they eventually become indistinguishable from the surrounding levels of noise.

Packed Bed Column Adsorption of Phenol Onto Corn Cob Activated Carbon: Linear and Nonlinear Kinetics Modeling

The authors have requested that this preprint be withdrawn due to author disagreement.

Solute Transport in the Element of Fractured Porous Medium with an Inhomogeneous Porous Block

In this paper, the problem of solute transport in a fractured-porous medium taking into account the non-equilibrium adsorption kinetic is studied. The solute transport in fractured-porous medium consisting of two fractures and a porous block between them located in a symmetric form is considered. The problem is then solved numerically by using the finite difference method. Based on the numerical results, the solute concentration and adsorption fields in the fractures and porous blocks are shown in graphical form. The effect of adsorption on the solute transport in a fractured-porous medium is then analyzed. In the case of different parameters in two zones, asymmetric distribution of the solute concentration and adsorption is obtained. The nonlinear kinetics of adsorption leads to an increase in the adsorption effects, conversely slowing down the rate of the distribution of concentration of the solute in the fluid.

Incorporating Nonlinear Kinetics to Improve the Predictive Performance of Population Pharmacokinetic Models for Ciclosporin in Adult Renal Transplant Recipients: A Comparison of Modelling Strategies

AimCiclosporin (CsA) has been shown to follow nonlinear pharmacokinetics in renal transplant recipients who received Neoral-based triple immunosuppressive therapy. Some of these nonlinear properties have not been fully considered in population pharmacokinetic (popPK) analysis. Therefore, the aim of this study was to determine the potential influence of nonlinearity and the functional forms of covariates on model predictability.MethodsA total of 2969 CsA whole-blood measurements, including 1328 pre-dose and 1641 2-h post-dose concentrations, were collected from 173 patients who underwent their first renal transplantation. Four popPK models based on different modelling strategies were developed to investigate the discrepancy between empirical and theory-based, linear and nonlinear compartmental kinetic models and empirical formulae on model predictability. Prediction-based and simulation-based diagnostics (prediction-corrected visual predictive checks) were performed to determine the stability and predictive performance of these four models.ResultsModel predictability improved when nonlinearity was considered. The theory-based nonlinear model which incorporated nonlinear property based on known theoretical relationships performed better than the other two compartmental models. The nonlinear Michaelis-Menten model showed a remarkable improvement in predictive performance over that of the other three compartmental models. The saturated binding of CsA to erythrocytes, and auto-inhibition that arose from the inhibitory effects of CsA on CYP3A4/P-gp and CsA-prednisolone drug interaction may have contributed to the nonlinearity.ConclusionsIncorporating nonlinear properties are likely to be a promising approach for improving CsA model predictability. However, CsA nonlinear kinetics resources need further investigation. Until then, Michaelis-Menten empirical model can be used for CsA dose adjustments.What is already known about this subjectCsA in renal transplant recipients receiving Neoral-based triple immunosuppressive therapy followed nonlinear pharmacokinetics.Nonlinearity is rarely incorporated into CsA population pharmacokinetic (popPK) modelling processes.What this study addsFour popPK models based on different modelling strategies were developed to investigate the discrepancy between empirical and theory-based compartmental kinetic models and empirical formulae, as well as the effect of nonlinearity on CsA model predictability.Based on the four models, incorporating nonlinear properties is likely to be a promising approach for improving CsA model predictability.Saturated distribution into red blood cells, and auto-inhibition that arose from the inhibitory effects of CsA on CYP3A4/P-gp and CsA-prednisolone drug interaction may be the main sources of CsA PK nonlinearity.Principal Investigator statementThe authors confirm that the Principal Investigator for this paper is Zheng Jiao and that he had direct clinical responsibility for patients.