No abstract

With the increased reliance on in vitro dissolution testing as an indicator of in vivo drug behavior and the trend towards the in silico modeling of dosage form performance, the need for bioperformance dissolution methodology development has been enhanced. Determination of the in vivo drug delivery profile is essential for the bioperformance dissolution test development and in vitro/in vivo correlation modeling, as well as the understanding of absorption mechanisms. The aim of this study was to compare different methods in terms of their usefulness and applicability in deciphering in vivo delivery of nifedipine administered in modified release dosage forms. A detailed survey of publications on nifedipine pharmacokinetics was done and used to identify the magnitude of food effect. In vitro dissolution testing was performed under various experimental conditions. Obtained results indicate the potential for using the developed in silico model coupled with discriminative in vitro dissolution data for identification of the in vivo drug product behavior

The knowledge of the structural and chemical properties of biochars is decisive for their application as technical products. For this reason, methods for the characterization of biochars that are generally applicable and allow quality control are highly desired. Several methods that have shown potential in other studies were used to investigate two activated carbons and seven biochars from different processes and feedstock. The chars were chosen to cover a wide range of chemical composition and structural properties as a hardness test for the analytical methods used in this study. Specific problems connected with the pretreatment of samples and drawbacks of some methods for some types of chars could be identified in an integrated consideration of the results from different methods. None of the spectroscopic methods was found to be suitable for the quality control of all types of chars. The most valuable results were obtained by chemical analysis that, however, required the complete determination of the main elements, including that of oxygen, and of inorganic components for adequate results. The combination of X-ray photoelectron spectroscopy (XPS) and FT-IR spectroscopy allows a rough characterization of surface functional groups, but cannot discriminate aliphatic and aromatic OH groups. FT-IR might be a suitable method for the quality control of biochars made at lower temperature. The results of Raman spectroscopy did not well correlate with the amount of sp2 hybridized carbon determined by XPS. A better correlation of XPS data was found with the electrical polarization determined by the method of spectral induced polarization that was used for the first time in conjunction with extensive analytical characterization.

Sensory analysis is the best mean to precisely describe the eating quality of fresh foods. However, it is expensive and time-consuming method which cannot be used for measuring quality properties in real time. The aim of this paper was to contribute to the study of the relationship between sensory and instrumental data, and to define a proper model for predicting sensory properties of fresh tomato through the determination of the physicochemical properties. Principal Component Analysis (PCA) was applied to the experimental data to characterize and differentiate among the observed genotypes, explaining 73.52% of the total variance, using the first three principal components. Artificial neural network (ANN) model was used for the prediction of sensory properties based on the results obtained by basic chemical and instrumental determinations. The developed ANN model predicts the sensory properties with high adequacy, with the overall coefficient of determination of 0.859.