Computer-assisted optimization for the selection of mobile phase in semi-preparative HPLC

A computer-assisted method is presented for optimization for the selection of mobile phase composition in semi-preparative HPLC.The optimization for the expected separation is based on a polynomial estimation from five preliminary runs.Statistical scanning technique was used for optimization.Double criteria simulation system (DCSS) is established for chromatographic perfor- mance measurement in this method.The validity of the optimization strategy is confirmed by applying it to a technical Cypermethrin separation.Excellent agreement is obtained between the predicted and experimental results.

Operational Laboratory Methods for GDGTs Groups Separation

Glycerol dialkyl glycerol tetraethers(GDGTs), specific membrane lipids synthesized mainly by bacteria and archaea, can be divided into isoprenoids and methyl branched alkyl GDGTs(i GDGTs and brGDGTs, respectively). Three GDGTs groups(i GDGTs, brGDGTs, and other membrane lipids) in a peat sample were separated and collected in this study using semi-preparative high-performance liquid chromatography(HPLC) and silica gel column chromatography. The obtained recoveries for the whole analytical procedure were 85% – 55% using semi-preparative HPLC and 70% – 20% using gel column chromatography. In addition, in each method, the recoveries of brGDGTs and iGDGTs were similar, regardless of the huge difference in their contents. High purity was found in the fractionated groups, determined based on ether cleavage and reduction. Moreover, the semi-preparative HPLC method could realize a better separation efficiency than the silica gel method, but it was time-consuming and required expensive equipment, while the silica gel chromatography method featured merits of time saving and convenient operation at the cost of a slight reduction in separation efficiency. The advantages of the silica gel method make it an operational laboratory method for batch experiments and isotopic studies.

Separation, Identification, Isolation and Characterization of Degradation Product of Osimertinib Tablets by UPLC-QTOF-MS/MS and NMR: Evaluation of <i>In-Silico</i>Safety Assessment for Osimertinib (OSM) and Degradation Product (DP)

The present work encompasses identification and characterization of major degradation product (DP) of OSM observed in base hydrolytic stress study. The separation of DP was carried out on a non-polar stationary phase by using high-performance liquid chromatography system (HPLC). Using waters X-bridge (250 mm × 4.6 mm, 5 μm) C18 column with gradient elution program. For the characterization study, stress samples were subjected to HPLC and UPLC-QTOF-MS/MS and based on mass fragmentation pattern, plausible structure was deduced. Further, the DP was isolated using semi-prepara- tive liquid chromatography and concentrated the fractions using lyophilization. The isolated DP was subjected to extensive 1D (1H, 13C, and DEPT-135) and 2D (COSY, HSQC and HMBC) nuclear magnetic resonance (NMR) studies to authenticate the structure. The impurity was unambiguously named as N-(2-((2-(dimethylamino)ethyl)(methyl)amino)-4-metho-xy-5-((4-(1-methyl-1H-indol-3-yl)pyrimidin-2-yl)amino)phenyl)-3-methoxypropanamide. Add- itionally, the In-Silico structure activity relation (QSAR) assessed through statistical based software’s DEREK NexusTM, and MultiCASE, Case UltraTM widely accepted and respected software’s for DP and OSM.

Rapid discovery and identification of the anti-inflammatory constituents in Zhi-Shi-Zhi-Zi-Chi-Tang

The anti-inflammatory active ingredients of Zhi-Shi-Zhi-Zi-Chi-Tang(ZSZZCT), a traditional Chinese medicine formula, were predicted and identified using an approach based on activity index, LC-MS, semi-preparative LC and NMR. Firstly, the whole extract of ZSZZCT was analyzed using liquid chromatography-quadrupole time of flight-mass spectrometry(LC-QTOF-MS) and liquid chromatography-ion trap mass spectrometry(LC-IT-MS), 79 constituents were detected and 39 constituents were identified unambiguously or tentatively. Subsequently, the whole extract of the formula was separated into multiple components and the activity index method was used to calculate index values of the 79 constituents by integrating the chemical and pharmacological information of multiple components. Four polymethoxyl flavones were predicted as the major active constituents according to the activity index values. Furthermore, three polymethoxyl flavones were prepared using the strategy with semipreparative LC guided by LC-MS, and their anti-inflammatory activities were validated. The results show that three polymethoxyl flavones with higher positive index values, i.e., 3, 5, 6, 7, 8, 3', 4'-heptamethoxyflavone, 3-hydroxynobiletein and tangeretin had significant anti-inflammatory effects. In conclusion, the predicted results indicated that the activity index method is feasible for the accurate prediction of active constituents in TCM formulae.