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Liposomes prepared from lipids dipalmitoylphosphatidylcholine (DPPC) and dipalmitoylphosphatidylglycerol (DPPG) with cholesterol were used to investigate the percentage of vinblastine encapsulation and the influence of lipid composition on the retention properties of vinblastine in buffer as well as in cell culture medium. Differential scanning calorimetry (DSC) was applied, to study the effect of cholesterol on the phase transition temperature and on the AH of the two liposome formulations. The cytotoxic and cytostatic activity of the liposome-encapsulated vinblastine was also examined against six leukaemic human cell lines. The results showed that encapsulation of vinblastine into liposomes was greater than 98% with a drug-phospholipid molar ratio of 0.13-0.18. The major improvement in vinblastine retention in buffer as well as in culture medium was achieved by employing DPPG. The DSC data showed that vinblastine exerted a more perturbing effect in DPPC-cholesterol bilayers than in DPPG-cholesterol bilayers and this may explain their lower retention time. The 50% growth-inhibiting (GI50) and cytostatic (TGI) activity of liposomal vinblastine did not seem to be affected by the type of the liposome while the 50% cytotoxic activity (LC50) was affected in four out of the six cell lines tested. The parameters GI50, TGI and LC50 were estimated according to the instructions given by the NCI.

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The application of the principal neural network architecture, namely the multilayer perceptron (MLP), have been developed for obtaining sufficient quantitative structure-binding relationships (QSBR) with high accuracy. To this end a dataset of 17 barbiturates as guests complexing to alpha- and beta-cyclodextrins was examined and the results compared to that of Lopata et al (J. Pharm. Sci., 74, (1995)) who studied the same problem using multiple regression analysis. A series of new and improved algorithms other than the "old fashion" and problematic steepest descent were examined for training the MLP networks. The proposed methods led to substantial gain in both the prediction ability and the computation speed of the resulting models. A specific ANN architecture (4-4-1) trained with the Levenberg-Marquardt algorithm diminished the number of outliers, during its implementation to unseen data (barbiturates), to zero.

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The application of an adaptive neuro-fuzzy inference system (ANFIS) has been developed for obtaining sufficient quantitative structure-activity relationships (QSAR) with high accuracy. To this end, a data set of 68 pyrimidines derivatives as DHFR inhibitors, described first in the excellent independent studies of Hansch et al. (J. Med. Chem. 1982, 25, 777-784 and J. Med. Chem. 1991, 34, 46-54) and later by So and Richards (J. Med. Chem. 1992, 35, 3201-3207), was examined. The ANFIS system, first time applied in the literature to QSAR studies, was trained using a hybrid algorithm consisting of back-propagation and least-squares estimation while the optimum number and shape of membership functions were obtained through the subtractive clustering algorithm. Prior to the development and evaluation of the ANFIS system, geometry optimization of the examined compounds was performed, deriving a series of diverse descriptors from which the best subset was selected by using a hybrid genetic algorithm system. The predictive abilities of the resulting models compared to those produced from classical multivariate regression such as linear and nonlinear (quadratic) partial least squares regression (PLS and QPLS, respectively). The ANFIS method outperformed both the PLS models as well as the published results, leading to substantial gain in both the prediction ability and the computation speed (almost instant training).

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A computer-based technique was applied for the optimization of recently described multicomponent protective liposomal formulations. These formulations contain riboflavin in either free form or complexed with gamma-cyclodextrin as a model drug, sensitive to photochemical degradation, as well as various light absorbers and antioxidants incorporated into the lipid bilayer and/or the aqueous phase of liposomes. During the liposomal preparation, a series of 11 factors were isolated as important to affect their effectiveness as stabilization systems. These factors were related, first, to the composition of liposomes and, second, to variations during the preparation procedure. The Plackett--Burnam design described in this study was applied for the isolation of the significant factors in order to concentrate more on them. The stabilization ratio of the vitamin was the response variable of the system to be optimized. In order to assure the presence of the examined components in liposomes, the entrapment values were calculated for all the materials, either spectrophotometrically or using second-order derivative spectrophotometry. The optimum formulation should be characterized from the higher protection of the drug.

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The present study examines the complexation of beta-cyclodextrin (beta-CD) with 6-p-toluidinylnaphthalene-2-sulfonate (TNS), a fluorescent probe for exploring hydrophobic regions of several biological substances. The complexation was monitored in aqueous solution by ultraviolet spectrophotometry. At first, the stoichiometry of the formed complex was examined by applying the continuous variation (Job plot) method. Next, the kinetic of the complex formation as well as the determination of the stability constant were calculated by monitoring the spectrophotometric properties of TNS in the presence of increasing concentrations of beta-CD applying both linear and nonlinear models. The results suggested that TNS forms a stable complex with beta-CD with a stability constant of 1109 M(-1) and 1:1 molar ratio, at least at the examined concentrations.

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The application of the principal neural network architecture, namely the multilayer perceptron (MLP), has been developed for obtaining sufficient quantitative structure-retention relationships (QSRR) with high accuracy. The present study is an extension to the excellent study of Cserhati et al. [LC-GC Int., 11 (1998) 240] for the retention behavior of solutes based on their structure. To this end, a dataset of 25 substances as solutes to two different stationary phases (polyethylene-silica and polyethylene-alumina) were analyzed to their structural descriptors and related to their retention behavior as expressed by the logarithms of their capacity factors (log k'). The results were compared to those of Cserhati et al. who studied the same problem using as many as ten different equations based on multiple regression analysis. In the present study a series of new and improved algorithms other than the 'old-fashioned' and problematic steepest descent were examined for training the MLP networks. The proposed methods led to substantial gain in both the prediction ability and the computation speed of the resulting models. For the development and evaluation of the artificial neural network (ANN) systems the same (eight) descriptors proposed by Cserhati were used also in this study. Furthermore, the results were compared to those produced from classical linear multivariate regression such as partial least squares regression (PLS). Some of the proposed ANN models diminished the number of outliers, during their implementation to unseen data (solutes), to zero.

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A computer-based technique based on a 2(k - p) fractional factorial design was applied for the optimization of recently described multicomponent protective liposomal formulations. These formulations contain sodium ascorbate (vitamin C) as a model drug sensitive to photochemical oxidation, as well as oil red O and/or oxybenzone as oil soluble light absorbers, incorporated into the lipid bilayers and sulisobenzone as a water soluble light absorber incorporated into the aqueous phase of liposomes. The three light absorbers (present or absent) incorporated in multilamellar liposomes and the drug in free or in complexed with alpha-cyclodextrin form comprised the four factors of the system. The stabilization ratio and the percentage entrapment in the liposomes of the vitamin were the two response variables of the system to be optimized. The entrapment values were calculated for all the materials either spectrophotometrically or by using second order derivative spectrophotometry. The response variables were predicted by multiple regression equations comprising combinations of the four formulation factors. Both the higher entrapment and the higher protection for the drug should characterize the optimum formulation.

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Equations are derived that allow the determination of guest-cyclodextrin primary (K(11)), secondary (K(12)), and higher order (K(1)(n)) binding constants as well as the degree of complexation n̄ (the percent of complexed guest), by monitoring the observed capacity factor k'(obs) for guests that can be structural, geometric, or optical isomers. The retention behavior (elution order) in a mixture of isomers is dependent on the cyclodextrin concentration in the mobile phase as well as on the stoichiometry and the binding constant of the guest-cyclodextrin (G-CD) complex. The simplification of higher order complexes (G-CD(n)) to that with 1:1 stoichiometry can lead to erroneous results; therefore, it is important for the stoichiometry to be determined accurately, prior to any binding constant calculations, following the continuous variation method. The proposed models are solved iteratively using nonlinear least-squares analysis and following specific algorithms.

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Haloperidol (Hal), a highly hydrophobic drug, was complexed with two beta-cyclodextrin (beta-CD) derivatives. Hal solubility was increased 20-fold in the presence of a 10-fold excess of methyl beta-CD (Me beta-CD) and 12-fold in the presence of a 10-fold excess of 2-hydroxypropyl beta-CD (HP beta-CD). The stoichiometries and stability constants of Hal-Me beta-CD (1:1 and 2345 M-1 at 27 degrees C) and Hal-HP beta-CD (1:1 and 2112 M-1 at 27 degrees C) complexes were calculated by the continuous variation and phase solubility methods respectively. Differential scanning calorimetry and 1H-NMR were used to confirm the formation of inclusion complexes. Moreover, the enthalpy and entropy of the complexation process were calculated for both complexes in order to obtain such information as the main 'driving force' and whether or not complex formation is thermodynamically favoured. This was achieved by monitoring the isothermic solubility lines at various temperatures.

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The interaction of the antitumor agent chlorambucil (CHL) with three different cyclodextrins (CD), namely methyl-beta CD (Me beta CD) polymer-beta CD (poly-beta CD) and gamma CD, is examined kinetically and spectrophotometrically, monitoring the hydrolysis and the changes in the UV absorbance of CHL respectively, in the presence of increasing concentrations of the examined CD. The stoichiometry coefficient for all the CHL-CD complexes was calculated and found to be 1:1, using the continuous variation method based on the UV data. Also, the stability constant Kst for the CHL-CD complexes was calculated and evaluated using the above mentioned two methods, each one based on linear and nonlinear mathematical models. All studies demonstrate that the interaction of CHL with the methylated derivative (Me beta CD) is stronger (the highest Kst value), probably due to the enhanced hydrophobic character of this derivative.

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The molecular association of haloperidol with hydroxypropyl-beta-cyclodextrin, expressed by the binding constant of the inclusion complex formed, was calculated from the changes on the 1H NMR spectra of the drug in the presence of the cyclodextrin. The stoichiometry of the complex was calculated by use of the continuous variation method (Job plot), and found to be 1:1. The binding constant for the 1:1 complex was calculated using improved non-linear models, which were solved by non-linear least-squares regression analysis, applying an iteration procedure. Three improved mathematical models for more accurate calculation of binding constants are proposed. The models are free from any assumptions and from practical or theoretical shortcomings.

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The non-linear least-squares model for calculation of the stability constant (Kst) of a drug-cyclodextrin complex has been used in fluorimetry studies. Complexation of riboflavin with beta-cyclodextrin (beta-CyD) was monitored fluorimetrically by measuring changes in the fluorescence intensity of the vitamin in the presence of various amounts of beta-CyD. Formation of an inclusion complex was confirmed in the solid state by differential scanning calorimetry (DSC) and in aqueous solution by proton nuclear magnetic resonance spectroscopy (1H NMR). The experimental Kst value (2112 M-1) derived from the fluorimetry studies appeared to fit well to a 1:1 drug-to-cyclodextrin molar ratio according to the non-linear mathematical model. The model is particularly suitable for fluorescent compounds of which fluorescence intensity is influenced by the presence of cyclodextrins.

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A computer-based technique based on a 2(k-p) fractional factorial design was applied for the optimization of recently described multicomponent protective liposomal formulations. These formulations contain riboflavin (vitamin B2) as a model, photosensitive drug, in addition to Oil Red O, deoxybenzone, oxybenzone and beta-carotene as oil-soluble light absorbers and antioxidants incorporated into the lipid bilayer, and sulisobenzone as a water-soluble light absorber incorporated into the aqueous phase of liposomes. The presence or absence of these five different light absorbers in multilamellar liposomes containing the vitamin free or complexed with gamma-cyclodextrin comprised the six factors of the system, each one examined at two levels. The stabilization ratio of the vitamin and its percentage entrapment in liposomes were the two response variables of the system to be optimized. The entrapment values were calculated for all the materials, either spectrophotometrically, using second-order derivative spectrophotometry, or fluorimetrically. The response variables were predicted by multiple regression equations comprising combinations of the six formulation factors. Higher entrapment and higher protection for the drug should characterize the optimum formulation.

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