Individualization of a pharmacokinetic model by fractional and nonlinear fit improvement

Popović, Jovan; Poša, Mihalj; Popović, K; Popović, Dušica J.; Milošević, Nataša; Tepavčević, Vesna

doi:10.1007/s13318-012-0097-6

Cited by 13 publications

(7 citation statements)

References 27 publications

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“…In humans, the PBPK model of bumetanide was verified in healthy adult volunteers using intravenous data (Table , Figure ). The simulated output demonstrated a two‐compartment profile, consistent with published pharmacokinetic models (Jullien et al, ; Marcantonio et al, ; Popovic et al, ). Simulations of intravenous bolus injections generated reasonable pharmacokinetic predictions of area under the concentration–time curve (AUC) (0.71–1.15), peak plasma concentration (C max ) (0.62–1) and time to reach peak plasma concentration (t max ) (0.5–1) as shown by the predicted/observed ratios (Table ) and concentration–time profiles overlaid with observed data (Figure ).…”

Section: Resultssupporting

confidence: 83%

Application of a physiologically‐based pharmacokinetic model for the prediction of bumetanide plasma and brain concentrations in the neonate

Donovan

Abduljalil

Cryan

et al. 2018

Biopharm & Drug Disp

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Bumetanide is a loop diuretic that is proposed to possess a beneficial effect on disorders of the central nervous system, including neonatal seizures. Therefore, prediction of unbound bumetanide concentrations in the brain is relevant from a pharmacological prospective. A physiologically-based pharmacokinetic (PBPK) model was developed for the prediction of bumetanide disposition in plasma and brain in adult and paediatric populations. A compound file was built for bumetanide integrating physicochemical data and in vitro data. Bumetanide concentration profiles were simulated in both plasma and brain using the Simcyp PBPK model. Simulations of plasma bumetanide concentrations were compared against plasma levels published in the literature. The model performance was verified with data from adult studies before predictions in the paediatric population were undertaken. The adult and paediatric intravenous models predicted pharmacokinetic factors, namely area under the concentration-time curve, maximum concentration in plasma and time to maximum plasma concentration, within two-fold of observed values. However, predictions of plasma concentrations within the neonatal intravenous model did not produce a good fit with the observed values. The PBPK approach used in this study produced reasonable predictions of plasma concentrations of bumetanide, except in the critically ill neonatal population. This PBPK model requires more information regarding metabolic intrinsic clearance and transport parameters prior to further validation of drug disposition predictions in the neonatal population. Given the lack of information surrounding certain parameters in this special population, the model is not appropriately robust to support the recommendation of a suitable dose of bumetanide for use as an adjunct antiepileptic in neonates.

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Section: Resultssupporting

confidence: 83%

Application of a physiologically‐based pharmacokinetic model for the prediction of bumetanide plasma and brain concentrations in the neonate

Donovan

Abduljalil

Cryan

et al. 2018

Biopharm & Drug Disp

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“…Clinical evidences have shown that, in AIS patients, high NLR levels are associated with increased infarct volume and mortality (Celikbilek, Ismailogullari, & Zararsiz, 2014;Gökhan et al, 2013;Tokgoz et al, 2013). Furthermore, NLR is a predictor of recurrent ischemic stroke and 90-day poor functional outcome in AIS patients receiving endovascular stroke therapy or IVT or antiplatelet medications (Brooks et al, 2014;Duan et al, 2018;Malhotra et al, 2018;Qun et al, 2017).…”

Section: Discussionmentioning

confidence: 99%

Neutrophil–lymphocyte ratio predicts post‐thrombolysis early neurological deterioration in acute ischemic stroke patients

et al. 2019

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Background and purpose Intravenous thrombolysis (IVT) has become the standard treatment for acute ischemic stroke within 4.5 hr after symptoms onset. However, a fraction of patients would develop early neurological deterioration (END) after IVT. The aim of our study was to explore the utility of neutrophil–lymphocyte ratio (NLR) in predicting END. Methods From October 2016 to March 2018, 342 consecutive patients with thrombolytic therapy were prospectively enrolled in this study. Blood cell counts were sampled in stroke emergency room before IVT. END was defined as a National Institutes of Health Stroke Scale score increase of ≥4 points within 24 hr after IVT. Multiple regression analysis was used to investigate the potential risk factors of END. We also performed receiver operating characteristic curve analysis and nomogram analysis to assess the overall discriminative ability of the NLR in predicting END. Results Of the 342 patients, 86 (25.1%) participants were identified with END. Univariate logistic regression analysis demonstrated that patients with NLR in the third tertile, compared with the first tertile, were more likely to have END (odds ratio, 9.783; 95% confidence interval [CI], 4.847–19.764; p = .001). The association remained significant even after controlled for potential confounders. Also, a cutoff value of 4.43 for NLR was detected in predicting post‐thrombolysis END with a sensitivity of 70.9% and a specificity of 79.3% (area under curve, 0.779; 95% CI, 0.731–0.822). Furthermore, our established nomogram indicated that higher NLR was an indicator of post‐thrombolysis END (c‐index was 0.789, p < .001). Conclusions This study showed that elevated level of NLR may predict post‐thrombolysis END in ischemic stroke patients.

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“…In practice, non-linearities, anomalous diffusion, fractional-order kinetics, diffusion accross fractal manifolds, synergetic and competitive action and a great many other factors render this approach not applicable (see Dokoumetzidis and Macheras [2008]). Recently, a significant number of relevant publications has emerged; see Popović et al [2012], Verotta [2010a,b], Pereira [2010], Dokoumetzidis et al [2010b], Popović et al [2010].…”

Section: Motivationmentioning

confidence: 99%

Controlled Drug Administration by a Fractional PID

Sopasakis

Sarimveis

2014

IFAC Proceedings Volumes

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Amiodarone is an antiarrhythmic drug that exhibits highly complex and nonexponential dynamics whose controlled administration has important implications for its clinical use especially for long-term therapies. Its pharmacokinetics has been accurately modelled using a fractional-order compartmental model. In this paper we design a fractional-order PID controller and we evaluate its dynamical characteristics in terms of the stability margins of the closed loop and the ability of the controlled system to attenuate various sources of noise and uncertainty.

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Individualization of a pharmacokinetic model by fractional and nonlinear fit improvement

Cited by 13 publications

References 27 publications

Application of a physiologically‐based pharmacokinetic model for the prediction of bumetanide plasma and brain concentrations in the neonate

Application of a physiologically‐based pharmacokinetic model for the prediction of bumetanide plasma and brain concentrations in the neonate

Neutrophil–lymphocyte ratio predicts post‐thrombolysis early neurological deterioration in acute ischemic stroke patients

Controlled Drug Administration by a Fractional PID

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