Modelling by partial least squares the relationship between the HPLC mobile phases and analytes on phenyl column

Method to evaluate the quality of herbal medicines based on the dynamic changes of chemical compounds and pharmacological activity

Quality control has been one of the key scientific issues in the modernization of traditional Chinese medicine. This study explored a novel method for quality evaluation of herbal medicines. High-performance liquid chromatography fingerprints and the osteoblast proliferation activity of 18 batches of Achyranthes bidentata, which were prepared with salt, were determined to establish a chromatographic database and an activity database. Correlation analyses of these databases were performed using partial least squares to obtain regression coefficients (positive and negative correlation coefficients). Then, the sums of the products of the positive and negative correlation peak areas and the corresponding coefficients, respectively, were calculated for each sample. The absolute value of the ratios of the sums of the positive and negative products were calculated, our studies showed that this ratio was significantly correlated with the proliferation activity, particularly when the activity was in the best and worst ranges. Therefore, we developed a parameter that was used to evaluate the quality of samples osteoblast proliferation activity. The quality of another ten batches of samples was assessed to verify this method. The results indicated that this method can be used for quality evaluation of herbal medicines according to the dynamic changes in the chemical compounds and activity.

A single step reversed-phase high performance liquid chromatography separation of polar and non-polar lipids

This paper reports a simple chromatographic system to separate lipids classes as well as their molecular species. By the use of phenyl coated silica as stationary phase in combination with a simple mobile phase consisting of methanol and water, all tested lipid classes elute within 30 min. Furthermore, a method to accurately predict retention times of specific lipid components for this type of chromatography is presented. Common detection systems were used, namely evaporative light scattering detection (ELSD), charged aerosol detection (CAD), electrospray mass spectrometry (ESI-MS), and UV detection.

Modeling the drugs' passive transfer in the body based on their chromatographic behavior

One of the most challenging aims in modern analytical chemistry and pharmaceutical analysis is to create models for drugs' behavior based on simulation experiments. Since drugs' effects are closely related to their molecular properties, numerous characteristics of drugs are used in order to acquire a model of passive absorption and transfer in the human body. Importantly, such direction in innovative bioanalytical methodologies is also of stressful need in the area of personalized medicine to implement nanotechnological and genomics advancements. Simulation experiments were carried out by examining and interpreting the chromatographic behavior of 113 analytes/drugs (400 observations) in RP-HPLC. The dataset employed for this purpose included 73 descriptors which are referring to the physicochemical properties of the mobile phase mixture in different proportions, the physicochemical properties of the analytes and the structural characteristics of their molecules. A series of different software packages was used to calculate all the descriptors apart from those referring to the structure of analytes. The correlation of the descriptors with the retention time of the analytes eluted from a C4 column with an aqueous mobile phase was employed as dataset to introduce the behavior models in the human body. Their evaluation with a Partial Least Squares (PLS) software proved that the chromatographic behavior of a drug on a lipophilic stationary and a polar mobile phase is directly related to its drug-ability. At the same time, the behavior of an unknown drug in the human body can be predicted with reliability via the Artificial Neural Networks (ANNs) software.