Xanthohumol (XN) is a prenylated chalcone with antimutagenic and anticancer activity from hops. A nonaqueous reverse polarity capillary electrophoretic method for the determination of XN in hop extract was developed and validated. The optimal parameters were a 64.5 cm long fused-silica capillary with 50 microm id at 25 degrees C; 30 kV negative voltage (anode at detector side of the capillary); nonaqueous buffer with 75 mM NaOH and 50 mM boric acid in methanol; hydrodynamical injection with 10 mbar for 40 s; and detection at 440 nm. XN, isoxanthohumol (IX), colupulone, adlupulone, and n-lupulone were well resolved on the electropherogram. The LOD for XN was 0.05 mg/L and RSD for peak area was below 3%. The amount of XN in different samples of hop pellets varied from 0.14 to 0.42%.

The effects of seven different chromatographic parameters and five sample preparation parameters in a high performance liquid chromatography (HPLC) method for assay determination of benzalkonium chloride (BKC) in a nasal formulation were evaluated using two fractional factorial experimental designs. The design space of the analytical method was modeled using Umetrics Modde software and the optimal method conditions were predicted. The optimum HPLC chromatographic conditions were obtained using a Luna CN column (150 × 4.6 mm, 3 μm). The results show that mobile phase pH, amount of acetonitrile in the mobile phase and column temperature are the most important factors in obtaining good separation of BKC homologs from an interfering peak. In the sample preparation step, the use of an aqueous solution for dissolving the samples was the most important factor since it eliminated the interfering effect of the active compound. The optimal method was validated for linearity, accuracy and precision. The use of experimental designs enables obtaining the maximum amount of information with the least possible number of experiments. Such designs are an economical manner in evaluating a variety of different factors and their interactions.

An ultra-performance liquid chromatographic method for simultaneous determination of rosuvastatin and rosuvastatin degradation products was developed and optimized by using fractional factorial experimental design. Optimized method is capable to accurately determine all potential degradation products of rosuvastatin. During the optimization the effect of four chosen chromatographic factors was evaluated. The analytical method operational design region was modeled using Umetrics MODDE software and optimal chromatographic conditions were predicted. The results of the model show that the most important factors to reach good separation between the peaks of rosuvastatin impurities are the pH of buffer solution and the amount of ACN and THF in the mobile phase. The final optimized method using QbD approach was validated for linearity, accuracy and precision for determination of rosuvastatin and rosuvastatin degradation products in rosuvastatin pharmaceutical dosage forms. Limit of detection and quantification were determined for two known specified impurities. The use of experimental designs enabled us to obtain the maximum amount of information about the analytical method design region. Optimization of the method was done without additional experiments, only weighing the responses and rebuilding the statistical model. This approach is very cost-effective when evaluating a variety of different factors and their interactions.

The aim of the present research is to show that the methodology of Design of Experiments can be applied to stability data evaluation, as they can be seen as multi-factor and multi-level experimental designs. Linear regression analysis is usually an approach for analyzing stability data, but multivariate statistical methods could also be used to assess drug stability during the development phase. Data from a stability study for a pharmaceutical product with hydrochlorothiazide (HCTZ) as an unstable drug substance was used as a case example in this paper. The design space of the stability study was modeled using Umetrics MODDE 10.1 software. We showed that a Partial Least Squares model could be used for a multi-dimensional presentation of all data generated in a stability study and for determination of the relationship among factors that influence drug stability. It might also be used for stability predictions and potentially for the optimization of the extent of stability testing needed to determine shelf life and storage conditions, which would be time and cost-effective for the pharmaceutical industry.

No abstract