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Charles University Faculty of Pharmacy in Hradec Králové Department of Biophysics and Physical Chemistry Candidate: Tomas Kouril Consultant: Ing. Vladimir Kubicek, CSc. Title of Thesis: HPLC analysis of Drugs The diploma thesis describes selection of the most suitable conditions for determination of a two enantiomers of drugs betaxolol and bisoprolol with a method HPLC. The aim of the thesis was to find a suitable isocratic method for the substances for extraction from plasma. The chromatographic column Daicel Chiralcel ® OD-R 4,6 mm x 250 m was utilized. The best results were achieved with mobile phase consisting of acetonitrile and aqueous solution of sodium perchlorate (1 molar) in volume ratio 50:50 for betaxolol and 35:65 for bisoprolol. The column was thermostated at 25 řC. UV detection (λ = 190 nm) was applied to get a sufficient sensitivity. Tramadol and O-desmethyltramadol was tested as an internal standard. Biological samples were tested by LLE before the HPLC analyses. Furthermore, the LLE method for biological samples was tested before performing HPLC.

Charles University Faculty of Pharmacy in Hradec Králové Department of Biophysics and Physical Chemistry Candidate: Monika Dohnalová Supervisor: Ing. Vladimír Kubíček, CSc. Title of Diploma Thesis: HPLC analysis of drugs The diploma thesis deals with the development and optimization of HPLC method for simultaneous determination of selected polyphenolic compounds: apigenin, acteoside and luteolin. During the experiments, the most suitable conditions for separation were sought, various mobile phases and various types of gradient elution were tested. The Zorbax Eclipse XBD C18 column 250 x 4.6 mm; 5 µm was used for analysis. The detection was performed with diode array detector at wavelengths 249 nm and 350 nm,the column was thermostated at 30 řC. The injected volume was 10 µl. The best results were achieved using mobile phase consisting of acetonitrile and aqueous solution of formic acid (0.03 mol/l) at a flow rate 1ml/min.

1 ABSTRACT Charles University Faculty of Pharmacy in Hradec Králové Department of Biophysics and Physical Chemistry Candidate: Karolina Palickova Consultant: Ing. Vladimir Kubicek, CSc. Title of Thesis: HPLC Determination of Potencial Drugs The diploma thesis describes selection of the most suitable conditions for HPLC determination of a recently prepared potential bronchodilatans. The aim of the thesis was to find a suitable isocratic method for the HPLC determination of the substance in rat plasma to be used during pharmacokinetic experiments. The chromatographic column Ascentis® Express RP - Amide was utilized. Best results were achieved with mobile phase consisting of acetonitrile and phosphate buffer (pH = 3,0) in volume ratio 12:88. The column was thermostated at 20 řC. Fluorescence detection (λex = 228 nm, λem = 380 nm) was applied to get a sufficient sensitivity. 4-quinazolinole was chosen as an internal standard. Biological samples were processed by LLE before the HPLC analyses. The proposed method was validated successfully and then employed in pharmacokinetic studies.

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Gas Chromatography (GC) is an analytical technique in the chemistry field widely used to separate compounds present in a sample mixture. Conventional GC systems are an extremely versatile and powerful tool to perform complex separations. However, these systems come with the cost of being bulky and requiring a high amount of power for operation. With considerable research for over 40 years, the advent of Micro-Gas Chromatography (µGC) made it possible for miniaturized, compact, low-power, and field portable GC systems. This thesis presents a portable µGC system that enables real-time analysis of complex compound separations, made possible with the use of multiple separation columns and a novel multidimensional compound identification algorithm. The system architecture and the software design with multiple features enabling portability of the µGC system are discussed. A set of microfabricated separation columns (µSCs) and photoionization detectors (PIDs) are integrated to realize a fully functional µGC system that is tested with different types of complex compound mixtures. An in-depth analysis of processing the output chromatograms obtained from the setup for signal filtering and peak detection is described in this thesis. A multidimensional analysis for compound identification in complex mixtures is presented. / Master of Science / Volatile organic compounds (VOCs) are generally chemicals that have high vapor pressure and low boiling points used and produced in the processing of petroleum products, paint, refrigerants, pharmaceuticals, and adhesives. VOCs are emitted as gases from certain solids or liquids, some of which may have short- and long-term adverse health effects even with minute exposure. Gas Chromatography (GC) is a common analytical technique used to detect, identify, and quantify VOCs in the environment, and conventional GC Systems have been utilized for this purpose. The separation of compounds occurs inside an analytical column that has selective interaction between the column and the analytes passing through. However, these systems are expensive, bulky, consume high power, and require expertise to operate. Recently, advancements in the Microelectromechanical systems (MEMS) field has paved the way to create Micro-Gas Chromatography (µGC) systems with improved performance when compared to traditional systems. Active research is ongoing to improve the portability of µGC systems for reliable and quick on-field analysis. In this thesis, we present a µGC system that has a robust and scalable design that allows the development of a portable µGC system. The compound separation of complex mixtures is showcased using the portable µGC system setup. The output chromatograms obtained from the µGC system are pre-processed, which involves noise filtering and peak detection, followed by an analysis using a multidimensional compound identification algorithm.

Mass spectrometry facilitates cutting edge advancements in many fields. Although instrumentation has advanced dramatically in the last 100 years, data processing algorithms have not kept pace. Without sensitive and accurate signal segmentation algorithms, the utility of mass spectrometry is limited. In this dissertation, we provide an overview and analysis of mass spectrometry data processing. A tutorial to ease the learning curve for those outside the field is provided. We draw attention to the lack of critical evaluation in the field and describe the resulting effects, including a glut of algorithm contributions of questionable novel contribution. To facilitate increased critical evaluation, we show the importance of a modular paradigm for mass spectrometry data processing through highlighting the impact of data processing algorithm choice upon experimental results. Our novel controlled vocabulary is presented with the aim of facilitating literature reviews for comparisons. We propose a novel nomenclature and mathematical characterization of mass spectrometry data. We present several novel algorithms for mass spectrometry data segmentation that outperform existing standard approaches. We end with an overview of future research which will continue to advance the state of the art in mass spectrometry data processing.

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