PubMed · 5481628
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S L Shapiro. 1970. Vacuum headache.. https://pubmed.ncbi.nlm.nih.gov/5481628/
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A liquid chromatographic-mass spectrometric (LC-MS) method with rapid automated sample preparation was developed and validated for determination of glybenclamide in human serum. Glybenclamide and its deuterated labelled internal standard were extracted from human serum samples by automated solid-phase extraction. The extract was injected into the LC-MS system for analysis. Glybenclamide and its internal standard were measured in multiple ion monitoring mode. The method was validated over a range of 10-1000 ng/ml with good accuracy and precision and was applicable for pharmacokinetic studies.
A generic isocratic HPLC-APCI-MS-MS method has been developed for the determination of plasma concentrations of bioactive compounds for the selection of potential new drug discovery candidates. A 4.6 x 50 mm cyano phase column eluted with an acetonitrile/water mobile phase containing 20 mM ammonium acetate and 0.4% TFA produces retention times of 1 min or less for a wide range of compounds. This is a great advantage in new drug discovery where many compounds are analyzed once and eliminated. No time is consumed developing chromatographic conditions for each new compound. The mass spectrometer can be optimized and the samples can be processed and analyzed, all in the same day. Multiple assays can be run consecutively without changing the column or mobile phase between assays.
Modeling systems for analyzing the consequences of chemical emergencies require as input values a number of physico-chemical substance properties, commonly as a function of temperature at atmospheric pressure. This paper presents a mathematical model "CHEMIC", which can be used for evaluating such substance properties, assuming that six basic constant quantities are available (molecular weight, freezing or melting point, normal boiling point, critical temperature, critical pressure and critical volume). The model has been designed to yield reasonably accurate numerical predictions, while at the same time keeping the amount of input data to a minimum. The model is based on molecular theory or thermodynamics, together with empirical corrections. Mostly, model equations are based on the so-called law of corresponding states. The model evaluates substance properties as a function of temperature at atmospheric pressure. These include seven properties commonly required by consequence analysis and heavy gas dispersion modeling systems: vapor pressure, vapor and liquid densities, heat of vaporization, vapor and liquid viscosities and binary diffusion coefficient. The model predictions for vapor pressure, vapor and liquid densities and heat of vaporization have been evaluated by using the Clausius-Clapeyron equation. We have also compared the predictions of the CHEMIC model with those of the DATABANK database (developed by the AEA Technology, UK), which includes detailed semi-empirical correlations. The computer program CHEMIC could be easily introduced into consequence analysis modeling systems in order to extend their performance to address a wider selection of substances.