Development of Analytical Quality by Design Compliant Chaotropic Chromatography Method for Ziprasidone and Its Five Impurities Determination.

In this study, an AQbD-compliant chaotropic chromatography method for ziprasidone and the determination of its five impurities was developed. The influence of critical method parameters (initial and final methanol fraction in the mobile phase, gradient duration) on the set of selected critical method attributes (t_imp. V, t_imp. V - t_imp. I, S and ) was studied by Box-Behnken design. The errors resulting from the calculation of the model coefficients were propagated to the selected responses by Monte Carlo simulations, and their predictive distribution was obtained. The design space was computed (π ≥ 80%), and a working point was selected: initial methanol fraction 38.5%, final methanol fraction 77.5%, and gradient duration 16.25 min. Furthermore, the quantitative robustness of the developed method was tested using the Plackett-Burman design. P_imp II and P_imp V were found to be significantly affected, the first by mobile phase flow rate and the second by gradient duration. Finally, the method was validated, and its reliability for routine quality control in capsules was confirmed.

Analytical method development supported by DoE-DS approach for enantioseparation of (S,S)- and (R,R)-moxifloxacin.

In this paper, method for enantiomeric purity testing of fourth-generation fluoroquinolone, moxifloxacin hydrochloride, was developed and validated. Exceptional enantioselectivity for this assay was achieved using cyclodextrin type Chiral Stationary Phase (CSP), phenylcarbamate-ß-cyclodextrin CSP, and mobile phase consisted of acetonitrile and triethylammonium acetate (TEAA) buffer. Analytical Quality by Design (AQbD) methodology, comprising Design of Experiments (DoE) - Design Space (DS) approach, was used for method development. In order to select appropriate Critical Method Parameters (CMPs), risk assessment was done using combined three step strategy that involved Ishikawa diagram - CNX (Control, Noise and eXperimental) - FMEA (Failure Mode and Effect Analysis). Three CMPs were further selected and investigated in this study: acetonitrile content in the mobile phase (30-50%, v/v), triethylamine content in the TEAA buffer (0.1-1.5%, v/v) and aqueous phase pH (3.5-4.5). Monte Carlo simulations were performed and 3D-DS was computed. One point situated in the center of 3D-DS was selected as working point for method validation, with the following values of CMPs: acetonitrile content in the mobile phase set to 37% (v/v), triethylamine content in TEAA 0.8% and pH value of the aqueous phase set at 4.0. Also, 2D-DS was created (with fixed one factor - pH value of aqueous phase at 4.0) which also gave us confirmation that the selection of working conditions was suitable. The proposed enantioselective method was further on tested for its quantitative robustness, as well as for its suitability for the intended purpose through validation studies.

Generic approach in a gradient elution HPLC method development that enables troubleshooting free method transfer.

Nowadays, method development is strongly focused on reducing time needed for method development and execution. This subject specially concerns gradient elution methods regarding the usual need for troubleshooting assistance with uncertain outcome during the method transfer from one laboratory to another. One of the main reasons for this situation is the dwell volume difference between HPLC systems. Therefore, the aim of this study was to propose a novel method development methodology that would integrate the dwell volumes differences in the optimization process. The proposed approach could be quite useful in industry that has insight in HPLC instruments planned to be used during the method life cycle. It was tested on the model mixture consisting of dabigatran etexilate mesylate and its nine impurities by use of experimental design methodology. Three different (U)HPLC instruments with high dwell volume differences were selected to challenge the methodology. Plan of experiments was defined with Plackett-Burman design for screening phase and D-optimal design for optimization phase. Initial and final amount of organic modifier, time of the gradient elution and pH value of the aqueous phase were selected as variables significant for the gradient programme profile and included in the optimization stage along with dwell volume values. The separation criteria s between critical peak pairs was selected as output for method optimization while indirect modelling together with Monte Carlo simulations enabled selection of optimal and robust chromatographic conditions. They included 24% (v/v) of initial amount of acetonitrile, 54% (v/v) of the final amount of acetonitrile, 15 min of gradient elution run time and pH value equal to 4.9. The proposed method was successfully validated, met all validation criteria and thus proved its utility.

A comprehensive study on retention of selected model substances in ß-cyclodextrin-modified high performance liquid chromatography.

The quantitative structure-retention relationship (QSRR) models are not only employed in retention behaviour prediction, but also in an in-depth understanding of complex chromatographic systems. The goal of the present research is to enable the comprehensive understanding of retention underlying the separation in ß-cyclodextrin (CD) modified reversed-phase high performance liquid chromatography (RP-HPLC) systems, through the development of mixed QSRR models. Moreover, the amount of ß-CD adsorbed on the stationary phase surface (ß-CDA) is added as the model's input in order to evaluate its contribution to both model performances and retention. Nuclear magnetic resonance (NMR) experiments were conducted to confirm the predicted inclusion complex structures and support the application of in silico tools. The most significant descriptors revealed that retention is governed by the steric factors 7.5 Å distant from the geometrical centre of a molecule, 3D arrangement of atoms determining the molecular size and shape, lipophilicity indicated by topological distances, as well as the unbound system's energy, related to the inclusion complex formation. In addition, a notable effect of the pH of the aqueous phase on the retention of ionizable analytes was shown. In the case of pH of the aqueous phase and ß-CDA the change in retention behaviour of the studied analytes was observed only at the highest ß-CDA value (5.17 µM/m2), but it was not related to the ionization state of analytes. When the analytes did not change the ionization form across the investigated studied pH range, and the acetonitrile content in the mobile phase was 25% (v/v), the retention factor had low values regardless of the ß-CDA; under these circumstances the retention is probably acetonitrile driven.

Corona Charged Aerosol Detector in studying retention and ß-cyclodextrin complex stability using RP-HPLC.

Binding between cyclodextrin (CD) cavity and guest molecule in Reversed Phase High-Performance Liquid Chromatography (RP-HPLC) is dynamic process. In general, increasing CD concentration is inducing inclusion complex formation, leading to reduction of analyte's retention time. Consequently, the shortness in retention time is a measure of complex stability in HPLC. However, under certain experimental conditions, the retention of some analytes could be prolonged even when concentration of CD in the mobile phase is increased. In order to reveal the cause of this unexpected retention behavior, the present study was carried on. The model mixture consisted of risperidone, olanzapine and their related impurities, while ß-CD was selected among CDs, as in the previous study. In order to achieve fast equilibrium between free analyte and ß-CD-analyte complex, ß-CD was not added to the mobile phase, but only to the sample. Detection was performed with Corona Charged Aerosol Detector (CAD), suitable for non-chromophoric ß-CD. When analyzing olanzapine impurity B-ß-CD sample, three peaks were detected, namely free ß-CD, ß-CD-analyte complex and free analyte. The complex stability constant was calculated employing a modification of the Benesi-Hildebrandt equation and CAD has proven to be useful in complex stability constants assessment if retention of free analyte and ß-CD-analyte complex is distinguished. For all other analytes only two peaks could be detected, because free analyte and formed complex are eluting at the same retention time. Under such circumstances, the authors proposed the methodology for calculating stability constants and confirmed its applicability to studied model mixture.

Performance comparison of nonlinear and linear regression algorithms coupled with different attribute selection methods for quantitative structure - retention relationships modelling in micellar liquid chromatography.

In micellar liquid chromatography (MLC), the addition of a surfactant to the mobile phase in excess is accompanied by an alteration of its solubilising capacity and a change in the stationary phase's properties. As an implication, the prediction of the analytes' retention in MLC mode becomes a challenging task. Mixed Quantitative Structure - Retention Relationships (QSRR) modelling represents a powerful tool for estimating the analytes' retention. This study compares 48 successfully developed mixed QSRR models with respect to their ability to predict retention of aripiprazole and its five impurities from molecular structures and factors that describe the Brij - acetonitrile system. The development of the models was based on an automatic combining of six attribute (feature) selection methods with eight predictive algorithms and the optimization of hyper-parameters. The feature selection methods included Principal Component Analysis (PCA), Non-negative Matrix Factorization (NMF), ReliefF, Multiple Linear Regression (MLR), Mutual Info and F-Regression. The series of investigated predictive algorithms comprised Linear Regressions (LR), Ridge Regression, Lasso Regression, Artificial Neural Networks (ANN), Support Vector Regression (SVR), Random Forest (RF), Gradient Boosted Trees (GBT) and K-Nearest neighbourhood (k-NN). A sufficient amount of data for building the model (78 cases in total) was provided by conducting 13 experiments for each of the 6 analytes and collecting the target responses afterwards. Different experimental settings were established by varying the values of the concentration of Brij L23, pH of the aqueous phase and acetonitrile content in the mobile phase according to the Box-Behnken design. In addition to the chromatographic parameters, the pool of independent variables was expanded by 27 molecular descriptors from all major groups (physicochemical, quantum chemical, topological and spatial structural descriptors). The best model was chosen by taking into consideration the Root Mean Square Error (RMSE) and cross-validation (CV) correlation coefficient (Q2) values. Interestingly, the comparative analysis indicated that a change in the set of input variables had a minor impact on the performance of the final models. On the other hand, different regression algorithms showed great diversity in the ability to learn patterns conserved in the data. In this regard, testing many regression algorithms is necessary in order to find the most suitable technique for model building. In the specific case, GBT-based models have demonstrated the best ability to predict the retention factor in the MLC mode. Steric factors and dipole-dipole interactions have proven to be relevant to the observed retention behaviour. This study, although being of a smaller scale, is a most promising starting point for comprehensive MLC retention prediction.

Quantitative structure retention relationship modeling as potential tool in chromatographic determination of stability constants and thermodynamic parameters of ß-cyclodextrin complexation process.

When cyclodextrins (CDs) are used in chromatography analytes' retention time is decreased with an increase in concentration of CD in the mobile phase. Thus complex stability constants can be determined from the change in retention time of the ligand molecule upon complexation. Since the preceding approach implies extensive and time-consuming HPLC experiments, the goal of this research was to investigate the possibility of using in silico prediction tools instead. Quantitative structure-retention relationship (QSRR) model previously developed to explain the retention behavior of risperidone, olanzapine and their structurally related impurities in ß-CD modified HPLC system was applied to predict retention factor under different chromatographic conditions within the examined domains. Predicted retention factors were further used for calculation of stability constants and important thermodynamic parameters, namely standard Gibbs free energy, standard molar enthalpy and entropy, contributing to inclusion phenomenon. Unexpected prolonged retention with an increase in ß-CD concentration was observed, in contrast to the employed chromatographic theory used for the calculation of the stability constants. Consequently, it led to failure in stability constants and thermodynamic parameters calculation for almost all analytes when acetonitrile content was 20% (v/v) across the investigated pH range. Moreover, ionization of investigated analytes and free stationary phase silanol groups are pH dependent, leading to minimization of secondary interactions if free silanol groups are non-ionized at pH lower than 3. In order to prove accuracy of predicted retention factors, HPLC verification experiments were performed and good agreement between predicted and experimental values was obtained, confirming the applicability of proposed in-silico tool. However, the obtained results opened some novel questions and revealed that chromatographic method is not overall applicable in calculation of stability constants and thermodynamic parameters indicating the complexity of ß-CD modified systems.

Analytical quality by design development of an ecologically acceptable enantioselective HPLC method for timolol maleate enantiomeric purity testing on ovomucoid chiral stationary phase.

Official method in Ph. Eur. for evaluation of timolol enantiomeric purity is normal-phase high performance liquid chromatography (NP-HPLC) method. Compared to other HPLC modes, NP is depicted as quite expensive with high consumption of organic solvents which leads to chronic exposure of analysts to toxic and carcinogenic effects. In order to overcome above-mentioned drawbacks, the aim of this study was to develop new method with better eco-friendly features. This was enabled by using protein type Chiral Stationary Phase (CSP) in reversed-phase mode that required up to 10 % (v/v) of organic solvent. Therefore, an enantioselective HPLC method was developed and validated for quantification of (S)-timolol and its chiral impurity, (R)-isomer. Optimized separation conditions on ovomucoid column were set using Analytical Quality by Design (AQbD) approach in method development. Optimization step was performed following the Box-Behnken experimental plan and the influence of three critical method parameters (CMPs) towards enantioseparation of the above-mentioned peak pair was examined. CMPs included variation of acetonitrile content in the mobile phase (5-10 %, v/v), pH value of the aqueous phase (6.0-7.0) and ammonium chloride concentration in the aqueous part of the mobile phase (10-30 mmol L-1). The most relevant critical method attributes (CMAs) in this case were the separation criterion between studied critical pair and retention factor of the second eluting peak, (S)-timolol. Qualitative Design Space (DS) was defined by Monte Carlo simulations providing adequate assurance of method's qualitative robustness (π = 95 %). The selected working point situated in the middle of the DS was characterized by following combination of CMPs: acetonitrile content in the mobile phase 7 % (v/v), pH value of the aqueous phase 6.8 and concentration of ammonium chloride in aqueous phase 14 mmol L-1. In the next step, the quantitative robustness was tested by Plackett-Burman experimental design. The validation studies confirmed adequacy of the proposed method for its intended purpose. Finally, Analytical Eco-Scale metric tool was applied to confirm that developed method represents excellent green analytical method compared to the official one.

Quantitative structure -retention relationship modeling of selected antipsychotics and their impurities in green liquid chromatography using cyclodextrin mobile phases.

Applying green chromatography methods is currently one of the challenges in liquid chromatography. Among different strategies, using cyclodextrin (CD) mobile phase modifiers was applied in this paper. CDs can form inclusion complexes with a wide variety of hydrophobic organic compounds and, consequently, affect their retention behavior. CD-containing mobile phases possess complicated complexation and adsorption equilibria so retention is dependent not only on chromatographic parameters and properties of the compound but also on properties of compound-CD complex. Docking study was used to calculate association constants of the selected antipsychotics (risperidone, olanzapine, and their impurities) and ß-CD complexes and predict which part of the molecule structure will most likely incorporate into the ß-CD cavity. Quantitative structure-retention relationship model (QSRR) for selected model substances was built employing artificial neural network (ANN) technique. Reliable QSRR model was obtained using molecular descriptors, complex association constants, and chromatographic factors. The multilayer perceptron network with 11-8-1 topology, trained with back propagation algorithm, showed the best performance. Root mean square error for training, validation, and test was 0.2954, 0.3633, and 0.4864, respectively. The correlation coefficient (R2) between experimentally obtained retention factor values [k(exp)] and values computed or predicted by ANN [k(ANN)] was 0.9962 for training, 0.9927 for validation, and 0.9829 for test, indicating good predictive ability of the model. The optimized network was used for development of green chromatography method for separation of risperidone and its related impurities, as well as olanzapine and its related impurities in a relatively short run time and with low consumption of organic modifier. The developed methods were validated in accordance with ICH Q2 (R1) quideline and all parameters fulfilled the defined criteria. The greenness of the proposed methods has also been demonstrated. Graphical Abstract Complex association constants as inputs of QSRR model in ß-cyclodextrin modified HPLC system and development of green chromatography methods.

Multicriteria Optimization Methodology in Stability-Indicating Method Development of Cilazapril and Hydrochlorothiazide.

Multicriteria optimization methodology was applied in development of UHPLC-UV-MS method for separation of cilazapril, hydrochlorothiazide and their degradation products. This method is also applicable for analysis of cilazapril, hydrochlorothiazide and their degradation products in combined tablet formulation. Prior to method optimization forced degradation studies were conducted. Cilazapril and hydrochlorothiazide were subjected to acidic (0.1, 0.5 and 1.0 M HCl), basic (0.1, 0.5 and 1.0 M NaOH), thermal (70°C), oxidative (3-30% H2O2) degradation and photodegradation (day light). Cilazapril appeared to be unstable toward acid and base and resulted in formation of cilazaprilat. Hydrochlorothiazide significantly degraded after acid, base and thermal hydrolysis and formed degradation product was 4-amino-6-chlorobenzene-1.3-disulfonamide. For both substances, after oxidative degradation unknown products have arisen. Initial percentage of acetonitrile in mobile phase, final percentage of acetonitrile in mobile phase, time of gradient elution and column temperature were defined as variables to be optimized toward two chromatographic responses by means of central composite design and Derringer's desirability function. The satisfactory chromatographic analysis was achieved on Kinetex C18 (2.6 µm, 50 × 2.1 mm) column with temperature set at 25°C. The final mobile phase consisted of acetonitrile and 20 mM ammonium formate buffer (pH adjusted to 8.5). The flow rate of the mobile phase was 400 µL min-1 and it was pumped in a gradient elution mode.

Structure-response relationship in electrospray ionization-mass spectrometry of sartans by artificial neural networks.

Quantitative structure-property relationship (QSPR) methods are based on the hypothesis that changes in the molecular structure are reflected in changes in the observed property of the molecule. Artificial neural network is a technique of data analysis, which sets out to emulate the human brain's way of working. For the first time a quantitative structure-response relationship in electrospray ionization-mass spectrometry (ESI-MS) by means of artificial neural networks (ANN) on the group of angiotensin II receptor antagonists--sartans has been established. The investigated descriptors correspond to different properties of the analytes: polarity (logP), ionizability (pKa), surface area (solvent excluded volume) and number of proton acceptors. The influence of the instrumental parameters: methanol content in mobile phase, mobile phase pH and flow rate was also examined. Best performance showed a multilayer perceptron network with the architecture 6-3-3-1, trained with backpropagation algorithm. It showed high prediction ability on the previously unseen (test) data set with a coefficient of determination of 0.994. High prediction ability of the model would enable prediction of ESI-MS responsiveness under different conditions. This is particularly important in the method development phase. Also, prediction of responsiveness can be important in case of gradient-elution LC-MS and LC-MS/MS methods in which instrumental conditions are varied during time. Polarity, chargeability and surface area all appeared to be crucial for electrospray ionization whereby signal intensity appeared to be the result of a simultaneous influence of the molecular descriptors and their interactions. Percentage of organic phase in the mobile phase showed a positive, while flow rate showed a negative impact on signal intensity.

Quantitative structure-retention relationships applied to development of liquid chromatography gradient-elution method for the separation of sartans.

QSRR are mathematically derived relationships between the chromatographic parameters determined for a representative series of analytes in given separation systems and the molecular descriptors accounting for the structural differences among the investigated analytes. Artificial neural network is a technique of data analysis, which sets out to emulate the human brain's way of working. The aim of the present work was to optimize separation of six angiotensin receptor antagonists, so-called sartans: losartan, valsartan, irbesartan, telmisartan, candesartan cilexetil and eprosartan in a gradient-elution HPLC method. For this purpose, ANN as a mathematical tool was used for establishing a QSRR model based on molecular descriptors of sartans and varied instrumental conditions. The optimized model can be further used for prediction of an external congener of sartans and analysis of the influence of the analyte structure, represented through molecular descriptors, on retention behaviour. Molecular descriptors included in modelling were electrostatic, geometrical and quantum-chemical descriptors: connolly solvent excluded volume non-1,4 van der Waals energy, octanol/water distribution coefficient, polarizability, number of proton-donor sites and number of proton-acceptor sites. Varied instrumental conditions were gradient time, buffer pH and buffer molarity. High prediction ability of the optimized network enabled complete separation of the analytes within the run time of 15.5 min under following conditions: gradient time of 12.5 min, buffer pH of 3.95 and buffer molarity of 25 mM. Applied methodology showed the potential to predict retention behaviour of an external analyte with the properties within the training space. Connolly solvent excluded volume, polarizability and number of proton-acceptor sites appeared to be most influential paramateres on retention behaviour of the sartans.

Liquid chromatography/tandem mass spectrometry for simultaneous determination of undeclared corticosteroids in cosmetic creams.

RATIONALE: Undeclared corticosteroids in creams intended for frequent use might cause serious side-effects, especially in children. In order to prevent this or find the cause, it was essential to develop a method for quick detection and quantification of low levels of corticosteroids. METHODS: Eleven corticosteroids were used in this study: prednisolone, methylprednisolone, prednisolone-21-acetate, fluocinolone acetonide, fluocinolone acetonide-21-acetate, hydrocortisone-21-acetate, dexamethasone, betamethasone, betamethasone dipropionate, clobetasol propionate and triamcinolone. Separation was achieved via liquid chromatography (LC), and mass spectrometric analysis was conducted by electrospray ionization triple-quadrupole mass spectrometry (MS/MS) in the multiple reaction monitoring mode using corticosterone as internal standard. RESULTS: Good separation by using a gradient-elution LC/MS/MS method with run time of 25 min enabled the use of a segmented detection method and consecutive decrease in detection limits. The proposed method has been validated in the linearity range of 10-1000 ng/mL with coefficients of determination higher than 0.990. The method has shown to have very low limits of quantification (0.75-3 ng/mL) with satisfactory precision and accuracy for each of the corticosteroids. CONCLUSIONS: An LC/MS/MS method for the rapid and simultaneous determination of low levels of eleven topical corticosteroids in creams was developed, optimized and validated. The proposed method can be used for testing of different products indicated for the treatment of atopic dermatitis, including "natural products", and "herbal creams" with "miraculous effects".

Quantitative structure-retention relationships of azole antifungal agents in reversed-phase high performance liquid chromatography.

Artificial neural network (ANN) is a learning system based on a computational technique which can simulate the neurological processing ability of the human brain. It was employed for building of the quantitative structure-retention relationships (QSRRs) model of antifungal agents-imidazoles or triazoles by structure. Computed molecular descriptors together with the percentage of acetonitrile in mobile phase (v/v) and buffer pH, being the most influential HPLC factors, were used as network inputs, giving the retention factor as model output. The multilayer perceptron network with a 9-5-1 topology was trained by using the back propagation algorithm. Good correlation between experimentally obtained data and ones predicted by using QSRR-ANN on previously unseen data sets indicates good predictive ability of the model.

Development and validation of reversed phase high performance liquid chromatographic method for determination of moxonidine in the presence of its impurities.

A simple, rapid, isocratic reversed-phase high-performance liquid chromatographic method was developed and validated for the analysis of moxonidine and its impurities in tablet formulations. The chromatographic separation was achieved on a Symmetry shield C18 column (250 mm × 4.6 mm, 5 µm) by employing a mobile phase consisting of methanol-potassium phosphate buffer (0.05 M) mixture (15:85, v/v) (pH 3.5) at a flow rate of 1 ml min⁻¹; detection at 255 nm. Central composite design technique and response surface method were used to evaluate the effects of variations of selected factors (buffer pH value, column temperature, methanol content) in order to achieve the best isocratic separation within short analysis time (less than 10 min), as well as for robustness test considerations. The method fulfilled the validation criteria: specificity, linearity, accuracy, precision, limit of detection and limit of quantitation. The method was successfully applied for the analysis of commercial moxonidine tablets.

Determination of carbamazepine and its impurities iminostilbene and iminodibenzyl in solid dosage form by column high-performance liquid chromatography.

An accurate and precise RP-HPLC method was developed and validated for the determination of carbamazepine and its impurities iminostilbene and iminodibenzyl in a tablet formulation with fluphenazine as an internal standard. Buffer-methanol (50 + 50, v/v) was used as the mobile phase. During validation, specificity, linearity, precision, accuracy, LOD, LOQ, and robustness of the method were tested. The method was proven to be specific against placebo interference. Linearity was evaluated over the concentration range of 100-500, 0.05-0.25, and 0.1-0.5 microg/mL, and the r values were 0.9994, 0.9997, and 0.9979 for carbamazepine, iminostilbene, and iminodibenzyl, respectively. Intraday precision of the method was good, and RSD was below 2% for all analytes. The accuracy of the method ranged from 100.69 to 102.10, 99.76 to 102.66, and 99.26 to 100.08% for carbamazepine, iminostilbene, and iminodibenzyl, respectively. LOD was 0.0125, 0.025, and 0.05 microg/mL and LOQ was 0.05, 0.05, and 0.1 microg/mL for carbamazepine, iminostilbene, and iminodibenzyl, respectiviely. Robustness of the method was proven by using a chemometric approach. The method was successfully applied to the analysis of commercially available carbamazepine tablets and showed good repeatability, with RSD below 2%.

Study of forced degradation behavior of eletriptan hydrobromide by LC and LC-MS and development of stability-indicating method.

The objective of the present study was to report the stability profile of novel antimigrain drug Eletriptan hydrobromide based on the information obtained from forced degradation studies. The drug was subjected to acid (0.1-1 mol L(-1) HCl), neutral and base (0.1-1 mol L(-1) NaOH) hydrolysis and to oxidative decomposition (3-15% (v/v) H(2)O(2)). Photolysis and thermo degradation at 75 degrees C were carried out in methanol solution and in solid state with both Eletriptan hydrobromide bulk drug and the tablet formulation. The products formed under different stress conditions were investigated by LC and LC-MS. The experimental conditions for LC were chosen by employing experimental design and multicriteria decision making methodology. These powerful tools enabled the accomplishment of satisfactory resolution with the shortest possible analysis time. Analytes were separated on a C(18) column (XTerra, 150 mm x 3.9 mm, 5 microm) with the mobile phase composed of methanol-water solution of TEA (pH 6.52, 1%, v/v) (30:70, v/v) pumped at 1 mL min(-1) flow rate. The column temperature was set at 50 degrees C and the detection at 225 nm using DAD detector. The LC method was suitably modified for LC-MS analysis which was further used to characterize the arisen degradation products. The possible degradation pathway was outlined based on the results. The drug appeared to be instable towards every stress condition but oxidation. The stability was not jeopardized even under more exaggerated conditions such as increased temperature of the solutions to 75 degrees C, increased strength of acid/alkali solutions and prolonged testing period. Validation of the LC-DAD method was carried out in accordance with ICH guideline. The method met all required criteria and was applied when testing the commercially available tablets.

Multicriteria optimization methodology in development of HPLC separation of mycophenolic acid and mycophenolic acid glucuronide in human urine and plasma.

Multicriteria optimization methodology was applied for development of isocratic reversed-phased HPLC method for simultaneous determination of mycophenolic acid (MPA) and mycophenolic acid glucuronide (MPAG) in human urine and plasma. In the first stage of method development, pH value of the water phase, percentage of acetonitrile, temperature of the column and flow rate of the mobile phase were investigated using fractional factorial design. Afterwards, the optimal conditions were found employing central composite design and Derringer's desirability function. Two goals were considered, the retention factor of the MPAG to be in the range, between 0.8 and 1.118 which allowed well separation of MPAG from the urine and plasma peaks, and the shortest possible total analysis run time. Then, the obtained sigmoid functions were used to transform the optimization criteria into the desirability values. The satisfactory chromatographic conditions were obtained with mobile phase consisted of acetonitrile-phosphate buffer (pH 2.4; 0.04 M KH(2)PO(4)) (28:72, v/v). The separation was performed on C(18) Chromolith column (100 mm x 4.6 mm) with flow rate of 5 mL/min, the temperature of the column was 25 degrees C and the chosen wavelength for simultaneous determination of MPA and MPAG was 215 nm. The MPAG eluted at 0.552 min and the duration of run was 3.092 min. Afterwards, the method was subjected to validation. Linearity was observed over the concentration range of 1-50 microg/mL for MPA and 1-500 microg/mL for MPAG in urine and 1-60 microg/mL for MPA and 1-70 microg/mL for MPAG in plasma matrix. The method showed intra-day and inter-day precision with relative standard deviation lower then 5% and accuracy as recovery (%) between 100+/-5%.

Simultaneous determination of cefotaxime and desacetylcefotaxime in real urine sample using voltammetric and high-performance liquid chromatographic methods.

Two rapid, accurate and sensitive methods are developed and validated for the quantitative simultaneous determination of cefotaxime (CFX) and its active metabolite desacetylcefotaxime (DCFX) in urine. Based on the previous results which showed the four electron reduction of CFX at approximately -0.5 V, and the new findings that DCFX reduction occurred at more positive potential (-0.23 V), the new adsorptive stripping differential pulse voltammetric (AdSDPV) method was developed for determination of CFX in the presence of DCFX. Linear responses were observed over a wide concentration range (0.07-0.52 microg/ml for CFX and 0.22-1.3 microg/ml for DCFX) in urine. The second assay involves subsequent separation on a reversed-phase HPLC column, with ultraviolet detection at 262 nm. Retention times were 4.057 and 1.960 min for CFX and DCFX, respectively. Linear responses were observed over a wide range, 0.55-6.60 microg/ml for CFX and 1.10-11.00 microg/ml for DCFX, in urine. The statistical evaluation for both methods was examined by means of within-day repeatability (n=5) and day-to-day precision (n=3) and was found to be satisfactory with high accuracy and precision.

Application of experimental design in optimization of solid phase extraction of mycophenolic acid and mycophenolic acid glucuronide from human urine and plasma and SPE-RP-HPLC method validation.

The aim of this study was to develop and optimize a solid phase extraction (SPE) procedure for purification of mycophenolic acid (MPA) and its metabolite mycophenolic acid glucuronide (MPAG) in biological samples. During optimization process chemometric approach was applied. First, in screening experiments fractional factorial design (FFD) was used for selecting the variables which affected the extraction procedure. The ionic strength of the phosphate buffer in the washing step and the percentage of acetonitrile in the elution step were statistically significant for the recovery of MPAG while the percentage of acetonitrile and pH of the washing solution were statistically significant for that of MPA. Afterwards, the significant variables were optimized using central composite design (CCD). The developed SPE method included phosphate buffer (pH 2.4; 0.056 M) in the washing step, and the mixture of acetonitrile and phosphate buffer of which pH was adjusted to 2.4 (70:30, v/v) in the elution step. The investigation was applied to both urine and plasma and the nature of biological matrix appeared to be of no importance. The extraction from both matrixes showed good repeatability with relative standard deviations up to 6% for MPAG and 8% for MPA, and recovery around 100% for both substances. Furthermore, new SPE-RP-HPLC method for determination of MPA and MPAG in both humane urine and plasma has been validated. The great advantage of this method is the chromatographic run of only 3 min.