Journal of pharmaceutical and biomedical analysis最新文献

In urine drug testing, a cut-off value is often imposed to determine whether the sample is negative or positive. A matrix containing a reference substance helps counteract the adverse effects of the urine matrix across different laboratories to improve the consistency of final results. However, as a biological matrix, urine is prone to corruption and other problems that make it difficult to use as a reference sample. In this study, morphine, nitrazepam, lorazepam, buprenorphine, zolpidem, midazolam, diazepam, and clozapine commonly used in clinical practice were selected as target analytes, and the preparation process was further optimized to repeated lyophilization, in order to obtain more effective, stable, and accurate urine matrix reference materials (mRMs). The appropriate urine density (1.010–1.017 kg/m³) for preparing lyophilized samples was investigated through density determination. Conducting repeated lyophilizations resulted in a denser powder with reduced susceptibility to collapse and improved the quality of lyophilized urine samples. Lyophilized urine mRMs could be stored at room temperature for one month or under refrigeration conditions (4 ℃) for six months.

Peptide therapeutics have emerged as an appealing modality in the pharmaceutical industry. Understanding peptide conformation in solution remains one of the most critical areas for peptide drug development. Circular dichroism (CD) spectroscopy is a useful technique to study the secondary structure of proteins and peptides, but the current approaches are limited to protein-focused models to predict high-order structures of peptides, and the models were built based on X-ray crystallography instead of solution-based technique, as a result, such models may have poor predictions for peptides. In this study, we present a novel CD deconvolution model to determine peptide conformation in solution. To quantitatively obtain secondary structure information using CD, a calibration model is needed beforehand to establish the relationship between each secondary structure feature and the corresponding CD response. A reference set containing the majority of cyclic peptides with known structures from solution-state NMR spectroscopy was used to build the calibration model for CD deconvolution. Improved prediction accuracy on the secondary structure determination for cyclic peptides was achieved by this model compared to the commercial standard model using commercially available platforms. This new CD deconvolution method is crucial for peptide conformational analysis in solution, and has the potential to greatly accelerate peptide drug candidate optimization in the pharmaceutical drug discovery field.

N-Phenylacetyl-L-prolylglycine ethyl ester (Noopept, GVS-111, omberacetam) is an orally available active pharmaceutical ingredient (API), with neuroprotective properties and ability to enhance cognitive function. It belongs to nootropic family of drugs and is included in the group of racetams, although its chemical structure is quite different than the other compounds from this group, including the most popular one – piracetam. The mechanism of action of this API is multifaced and is considered to be involving modulation of various neurotransmitter systems within the brain. Despite the significant amount of works devoted to the pharmacodynamics of Noopept, very little is known about its structural and physicochemical properties. Therefore, the aim of current study was to investigate this API in a very thorough way. In this work, the detailed physicochemical analysis of Noopept has been done using TGA/DSC, ¹H and ¹³C liquid state NMR, ¹³C CP/MAS NMR, SEM, SCXRD, and PXRD. Additionally, quantum chemical DFT computations under periodic boundary conditions, using CASTEP, were conducted to facilitate the analysis of experimental results. Besides, we’ve performed a polymorphism screening of this molecule.

In recent years, the expanding array of psychotropic medications has led to an increase in drug-drug interactions, particularly with combinations of different antipsychotics or psychotropic medications in clinical practice. However, the potential pharmacokinetic interactions between Lurasidone and Clozapine have not been extensively studied. Thus, this study aims to investigate these potential interactions by analyzing their pharmacokinetics in rat plasma after single oral administrations using developed LC-MS/MS methods. The study revealed notable changes in Lurasidone's pharmacokinetic parameters between single and combination administrations. Specifically, there were significant reductions in t_1/2 and V_d by 3.3 and 1.5-fold (p < 0.05) respectively, while C_max and AUC_0-t proved a significant increase by 1.8 and 1.6-fold (p < 0.05) respectively following the combination administration. Furthermore, separate co-administration markedly decreased Clozapine's C_max and AUC 0-t by 1.6 and 1.3-fold (p < 0.05) respectively, after the combination administration. Moreover, the AUC ratio for Lurasidone was 0.2, indicating a diminished therapeutic effect, whereas the AUC ratio for Clozapine suggested an elevated risk of adverse effects. These findings confirm the presence of drug-drug interactions between Lurasidone and Clozapine, suggesting potential implications for treatment efficacy. Recommendations for future clinical research include conducting pharmacodynamic studies to evaluate the impact of Lurasidone and Clozapine combination therapy. This underscores the importance of thoroughly assessing these interactions for clinical relevance and provides a scientific foundation for future evaluations of this drug combination.

Aconiti Lateralis Radix Praeparata (Fuzi) is a traditional Chinese medicine (TCM) widely used in treating cancer. Our formerly investigations confirmed the anti-lung cancer efficacy of Fuzi, but systematic analysis of the ingredients of Fuzi absorbed into serum and the corresponding molecular mechanism in treating lung cancer remained unknown. In this work, UPLC-Q-TOF-MS was applied to detect the ingredients of Fuzi in rat serum. Next, the possible targets and key pathways of the components absorbed into serum of Fuzi were predicted by network pharmacology. Then, the binding activity of components and potential targets were performed by molecular docking. Afterwards, the proliferation, mitochondrial membrane potential (MMP), apoptosis and reactive oxygen species (ROS) of lung cancer cells after treatment with Fuzi-containing serum were determined by MTT assay, JC-1 fluorescent probe, Annexin V-FITC/PI double staining and DCFH-DA respectively. Finally, the predicted target was further validated with qRT-PCR. In total, identification of 20 components of Fuzi derived from rat serum were achieved. The prediction of network pharmacology indicated that these compounds might exert their therapeutic effects by modulating mTOR. The findings from molecular docking proved that fuziline, songorine, napelline and hypaconitine exhibited binding potential with the mTOR. Cancer cell experiments revealed that the Fuzi-containing serum inhibited cell proliferation, induced apoptosis, reduced MMP and increased ROS. Additionally, Fuzi-containing serum significantly reduced the mRNA expression of mTOR. This study revealed that fuziline, songorine, napelline and hypaconitine were the main ingredients of Fuzi absorbed into serum. Furthermore, Fuzi-containing serum demonstrated inhibitory effects on the proliferation of lung cancer cells and induced the apoptosis. Combined with the results of network pharmacology, molecular docking and biological verification, Fuzi-containing serum might exert its anti-lung cancer effect by inhibiting mTOR. This study would provide a deeper understanding of Fuzi in treating lung cancer and offer a scientific reference for its clinical utilization.

A transmission detection mode was investigated with SERS analyses (SETRS). A comparison between backscattering and transmission detection modes was conducted to demonstrate the feasibility of performing SETRS analyses. The impact of various parameters on the SERS signal intensity such as sample volume, lens collection optic, laser beam size and laser power were then examined. The analytical performances of SETRS were further evaluated through the quantification of an impurity (4-aminophenol) ranging from 3 to 20 µg/mL in a commercial pharmaceutical product using a total error risk-based approach. To account for expected variability of routine analysis, 9 batches of silver nanoparticles suspensions were used and experiments were performed over 5 different days and by 2 operators. Univariate spectral analysis based on a quadratic regression was compared to a multivariate approach using a partial least square regression. The presented results demonstrated that SETRS can be used to determine an impurity in a complex matrix opening new perspectives for quantitative applications.

Purine metabolism acts as the core role in human metabolic network. It offers purine metabolites as raw material for building blocks in cell survival and proliferation. Purine metabolites are the most abundant metabolic substrates in organisms. There are few reports to simultaneously quantify canonical purine metabolism in cells. A novel hydrophilic interaction liquid chromatography coupled with mass spectrometry (HILIC-MS/MS) method was developed to simultaneously determine purines profile in biological samples. Chromatographic separation was achieved using a HILIC (Waters Xbridge™ Amide) column. Different optimizing chromatographic conditions and mass spectrometric parameters were tested in order to provide the best separation and the lowest limit of quantification (LLOQ) values for targeted metabolites. The validation was evaluated according to the Food and Drug Administration guidelines. The limit of determination (LOD) and the LOQ values were in the range of 0.02–8.33 ng mL⁻¹ and 0.1–24.5 ng mL⁻¹, respectively. All calibration curves displayed good linear relationship of with excellent correlation coefficient (r) ranging from 0.9943 to 0.9999. Both intra-day and inter-day variability were below 15 %, respectively. Trueness, expressed as relative error, was always within ±15 %. In addition, no derivatization procedure and ion-pair reagents are in need. The innovated approach demonstrates high sensitivity, strong specificity, and good repeatability, making it suitable for absolute quantitative studies of canonical purine metabolism in cultured cells.