Ljiljana Zivanovic

Prediction of drug transfer into human milk from theoretically derived descriptors

Abstract The goal of this study was to develop a genetic neural network (GNN) model to predict the degree of drug transfer into breast milk, depending on the molecular structure descriptors, and to compare it with the current model. A supervised network with back-propagation learning rule and multilayer perceptron (MLP) architecture was used to correlate activity with descriptors that were preselected by a genetic algorithm. The set of 60 drug compounds and their experimentally derived M / P values used in this study were gathered from literature. A total of 61 calculated structural features including constitutional, topological, chemical, geometrical and quantum chemical descriptors were generated for each of the 60 compounds. The M / P values were used as the ANNs output and calculated molecular descriptors as the inputs. The best GNN model with 26 input descriptors is presented, and the chemical significance of the chosen descriptors is discussed. Strong correlation of predicted versus experimentally derived M / P values ( R 2 >0.96) for the best ANN model (26-5-5-1) confirms that there is a link between structure and M / P values. The strength of the link is measured by the quality of the external prediction set. With the RMS error of 0.425 and a good visual plot, the external prediction set ensures the quality of the model. Unlike previously reported models, the GNN model described here does not require experimental parameters and could potentially provide useful prediction of M / P ratio of new potential drugs and reduce the need for actual compound synthesis and experimental M / P ratio determination.

Application of artificial neural networks in HPLC method development

The use of artificial neural networks (ANNs) for response surface modelling in HPLC method development for amiloride and methychlothiazide separation is reported. The independent input variables were pH and methanol percentage in mobile phase. The outputs were capacity factors. The results were compared with a statistical method (multiple nonlinear regression analysis). Networks were able to predict the experimental responses more accurately than the regression analysis.

Validation of an HPLC method for the simultaneous determination of eletriptan and UK 120.413

Arapid and sensitive RPHPLCmethod was developed for the routine control analysis of eletriptan hydrobromide and its organic impurity UK 120.413 in Relpax® tablets. The chromatography was performed at 20°C using a C18 XTerra ™ (5 µm, 150 x 4,6 mm) column at a flow rate 1.0 ml/min. The drug and its impurity were detected at 225 nm. The mobile phase consisted of TEA (1 %) - methanol (67.2:32.8 v/v), the pH of which was adjusted to 6.8 with 85 % orthophosphoric acid. Quantification was accomplished by the internal standard method. The developed RP HPLC method was validated by testing: accuracy, precision, repeatability, specificity, detection limit, quantification limit, linearity, robustness and sensitivity. High linearity of the analytical procedure was confirmed over the concentration range of 0.05 - 1.00 mg/ml for eletriptan hydrobromide and from 0.10 - 1.50 µg/ml for UK 120.413, with correlation coefficients greater than r = 0.995. The low value of the RSD expressed the good repeatability and precision of the method. Experimental design and a response surface method were used to test robustness of the analytical procedure and to evaluate the effect of variation of the method parameters, namely the mobile phase composition, pH and temperature. They showed small deviations from the method setting. The good recovery and low RSD confirm the suitability of the proposed RP HPLC method for the routine determination of eletriptan hydrobromide and its impurity UK 120.413 in Relpax® tables.

FORCED DEGRADATION STUDY OF TORASEMIDE: CHARACTERIZATION OF ITS DEGRADATION PRODUCTS

Torasemide was subjected to forced degradation studies. Stress conditions were varied concerning hydrolysis (acid, base, and neutral), oxidation, photolysis, and thermal degradation in order to identify the potential degradation products and consequently establish the possible degradation pathways and intrinsic stability of the drug. The study was performed according to ICH guidelines and drug was found to be relatively stable in the solid form. It showed that torasemide degraded significantly under acidic, neutral and alkaline conditions and resulted in formation of degradation product R2. When temperature was increased the degradation was accelerated. Also, the drug showed slight instability under extreme oxidative stress conditions which resulted in formation of two degradation products in total. The drug and degradation products have been separated employing gradient elution method on Zorbax SB C18 analytical column. To characterize the degradation products LC–MSn was applied. The mass fragmentation pattern was established using single quadrupole and ion trap mass analyzers. Finally, the most possible degradation mechanism of torasemide in different experimental conditions was proposed.

Chemometrically Assisted Development and Validation of LC–UV and LC–MS Methods for Simultaneous Determination of Torasemide and its Impurities

Complete evaluation of chromatographic behavior and establishment of optimal experimental conditions for determination of torasemide and its four impurities are determined by experimental design. Fractional factorial and 3(n) full factorial design were employed for efficient and rapid optimization of liquid chromatography-ultraviolet and liquid chromatography-mass spectrometry (LC-MS) methods. Separation is achieved on a Zorbax SB C(18) analytical column (250 x 4.6 mm, 5 µm) with mobile phase consisting of acetonitrile and 10 mM ammonium formate (pH 2.5 with formic acid) in gradient mode. The flow rate is 1 mL min(-1), the temperature of the column is 25 °C and UV detection is performed at 290 nm. The efficiency of ionization in electrospray ionization is higher than in atmospheric pressure chemical ionization mode; therefore, it is further used for analysis of torasemide and its impurities. Both methods meet all validation criteria. The calibration curves show high linearity with the coefficients of correlation (r) greater than 0.9982. The obtained recovery values (95.78-104.92%) and relative standard deviation values (0.12-5.56%) indicate good accuracy and precision. Lower limit of detection (LOD) and limit of quantitation (LOQ) values are obtained with the LC-MS method, indicating higher sensitivity of the proposed method.

IMPURITY PROFILING OF MYCOPHENOLATE MOFETIL WITH THE ASSISSTANCE OF DESIRABILITY FUNCTION IN METHOD DEVELOPMENT

Multicriteria decision making methodology in combination with experimental design has been applied for optimization of stability-indicating LC/DAD method of Mycophenolate mofetil and its degradation products. Via fractional factorial design variables with statistically significant impact on retention parameters of the investigated substances were defined and then thoroughly optimized toward four chromatographic responses combining central composition design and desirability function. The separation was achieved on Chromolith column (C18e, 100 × 4.6 mm) with the mobile phase consisted of acetonitrile—0.015 M KH2PO4 (pH 4.4) (28:72, v/v). The flow rate of the mobile phase was 2 mL/min and the detection was performed using PDA detector at 215 nm. The method has been suitably modified for LC/MS/MS analysis. The ammonium-acetate buffer was used instead of phosphate buffer and pH of the water phase was adjusted with acetic acid. The flow rate was 1 mL min−1. The substance was subjected to stress conditions (0.01 M NaOH, 1 M HCl, 3–30% H2O2, 70°C and day light). It resulted in formation of Mycophenolic acid and two oxidation products. The substance showed to be stable only towards photolysis. The LC/MS/MS values and fragmentation pattern of two unknown oxidation products were used in its characterization.