J Pharm Pharm Sci
September 2014
Purpose: The purpose of this study was to develop an artificial neural network (ANN) model to predict drug removal during dialysis based on drug properties and dialysis conditions. Nine antihypertensive drugs were chosen as model for this study.
Methods: Drugs were dissolved in a physiologic buffer and dialysed in vitro in different dialysis conditions (UFRmin/UFRmax, with/without BSA).
Purpose: In order to update our data on drug dialyzability using the high-permeability dialysis membranes, atenolol elimination by an in vitro dialysis model was compared to that observed in six patients during high-permeability hemodialysis (HD), and the predictive value of the model was evaluated.
Methods: Atenolol clearance was evaluated in six patients undergoing chronic HD. They were considered as eligible candidates if they were between 18 and 80 years of age, had a body mass index between 19 and 30 kg/m2, underwent HD and were taking atenolol on a regular basis in oral tablet form for at least 1 month before the study started.
The purpose of this study was to determine the room temperature stability over a period of several months of commercially available intravenous succinylcholine dichloride (Quelicin, 20 mg/mL) in vials. A previously validated electro-spray tandem mass spectrometry method developed for the determination of succinylcholine dichloride in plasma was used. This method was based upon a stable isotope dilution assay using hexadeuterosuccinylcholine diiodide as the internal standard and was shown to be specific, sensitive, and reproducible.
View Article and Find Full Text PDFBackground: The pharmacokinetics and pharmacodynamics of succinylcholine were studied simultaneously in anesthetized patients to understand why the drug has a rapid onset and short duration of action. A quantitative model describing the concentration-effect relation of succinylcholine was proposed. The correlation between hydrolysis in plasma and elimination was also examined.
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