Chromatographia最新文献

A novel, environment friendly high-performance liquid chromatography method for the determination of Ganciclovir in drug and formulations. Current HPLC methods often rely on acetonitrile, a solvent known to pose environmental and health hazards. Despite extensive literature review ganciclovir was estimated using only traditional HPLC solvents no studies were reported using ethanol. The developed method utilizes a simple mobile phase consisting of ethanol and acidic water (pH 3.0) at an optimized ratio of 80:20 v/v. Separation is achieved on a Zorbax eclipse plus C18 column (4.6 × 150 mm, 5 μm) with a flow rate of 1.0 mL/min. The proposed method demonstrates excellent linearity, and precision, assessed by (r² ≥ 0.999) and %RSD by below 2%, with recovery 98–102%. The method’s greenness was evaluated using established assessment tools such as AGREE, GAPI, and COMPLEX GAPI confirming the method’s adherence to 12 green analytical principles. The proposed method’s capability of separation from degradation products and no significant change of peak area and retention time was observed. This study explores the feasibility of substituting the acetonitrile with an eco-friendly greener alternative, ethanol recognized for its low toxicity and environmental impact.

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The primary objective of this study is to implicate the Quality by Design (QbD) principle to develop a simple and stability—indicating High Performance liquid Chromatography (HPLC) method for analysing and quantifying Eltrombopag olamine. Initially, a comprehensive risk assessment was conducted using an Ishikawa (fish-bone) diagram. Following this, an Analytical Target Profile (ATP) was established, with desired specification and Critical Analytical Attributes (CAAs) were identified to fulfil these requirements. Additionally, Critical Material Attributes (CMAs) and Critical Process Attributes (CPPs) were chosen, as they can influence the CAAs. Subsequently, a three-level factorial design was utilized to optimize the primary contributing factors both numerically and graphically. The validation study was performed according to International Council for Harmonisation (ICH) guidelines and forced degradation studies were performed under various stress conditions. Optimal chromatographic separation was done using a mobile phase comprising acetonitrile and water with 0.3% formic acid in both phases at a ratio of 80:20% v/v, with 1.2 mL/min flow rate and UV detection at 248 nm. The developed method exhibited high sensitivity and specificity, with a linear range of 10–70 µg/mL and a correlation coefficient (R2) of 0.9999. It demonstrated accuracy with % recovery ranging from 98–100% and the detection and quantification limits of 0.2443 µg/mL and 0.7403 µg/mL, respectively. The forced degradation studies indicated that the drug is vulnerable to all stress conditions. Overall, the developed method proves to be suitable for estimation of Eltrombopag olamine in its marketed formulation, with potential applicability for analysing it in other dosage form and various biological samples available.

Combining anticancer drugs and phytomolecules with anticancer activity has opened up new avenues for cancer treatment and could be a potent alternative to conventional cancer therapy. Quercetin (QUR) and Erlotinib (ERB) exhibit potential anticancer properties. However, both drugs manifest low oral bioavailability due to low aqueous solubility, and interestingly, there is not a single validated UHPLC-PDA method for quantifying QUR and ERB simultaneously. Thus, the current study aims to address pharmaceutical challenges by encapsulating the two drugs in liquid crystalline nanoparticles (LCNPs) and to develop and validate a sensitive, accurate analytical, and bioanalytical method, as per guidelines, to quantify QUR and ERB simultaneously in LCNPs. Effective chromatographic elution of QUR and ERB has been achieved using a C8 reversed-phase column with an isocratic mobile phase at a flow rate of 1 mL/min, and both drugs were detected at 252 nm wavelength. The retention time was 5.3 and 7.7 min for QUR and ERB, respectively, while LOQ was less than 0.5 µg/mL for both drugs, appropriate for monitoring therapeutic drugs in preclinical and clinical research settings. The validated method was successfully applied to estimate the %drug entrapment efficiency, %drug loading, and %drug release for the simultaneous analysis of QUR and ERB in the LCNPs. The technique investigated both drugs’ pharmacokinetic characteristics in Sprague–Dawley rats. The results were deemed reliable, and the validated method was found to be precise and accurate as per guidelines for the simultaneous estimation of QUR and ERB, which have applications in formulation development and bioanalytical studies.

The aim of this study was to find lipid metabolite concentrations differences between healthy subjects and colorectal cancer patients. A novel high performance liquid chromatography–electrospray ionization tandem mass spectrometry (HPLC–ESI–MS/MS) analytical method was developed for the analysis of nine lipid series (two sphingolipids, seven phospholipids) using the multiple reaction monitoring mode (MRM) on dried plasma spots. The extracted lipids were separated by HPLC using an Imtakt Unison UK-C8. The developed method was applied to human plasma samples obtained from healthy subjects (n = 40) and colorectal cancer patients (n = 40). A partial least squares discriminant analysis (PLS-DA) model, which is a multivariate statistical analysis method, was employed to analyse the quantitative results. The VIP score of the PLS-DA model was employed to effectively discriminate colorectal cancer patients from healthy subjects. Furthermore, a random forest classification method was employed. Through statistical processing, the lipid 18:1 Lyso PC in accordance with VIP score > 1 was identified, and four lipids in accordance with p-value < 0.05, 15:0–18:1 PC, 18:1 Lyso PC, 18:1 Lyso PE, and C15 Ceramide (d18:1/15:0) were identified. The results of this study corresponded to study of Zhao et al.(2007) that 18:1 LPC can be potential biomarker between normal and colorectal cancer patients. This method is expected to be practically useful due to its simple dried plasma spot use and excellent sensitivity for lipid screening when applied to various diseases, including colorectal cancer.

The research presents a novel application of the QbD technique to develop and validate a stability-indicating method for terlipressin quantification in injection form, aligning with ICH Q2 (R2) guidelines using the HPLC method. Terlipressin, a synthetic drug recently approved by the FDA for treating hepatorenal syndrome, lacks an official monograph in any pharmacopeia, and the existing stability indicating methods for its quantification were limited. The primary objective is to establish a method using the QbD approach and ICH Q8 (R2) guidelines, emphasizing accuracy, simplicity, rapidity, and robustness. The method is optimized through the design of experiments, including response surface plots, contour plots, and overlay plots. Successful development of this method results in a shorter retention time (less than 4 min) using a SunFire C₁₈ column with dimensions 250 mm × 4.6 mm and particle size of 5µm, mobile phase consisting of acetonitrile and 0.1% orthophosphoric acid (11:89 v/v), flow rate of 1 ml/min, and the PDA detection at 216 nm, with an injection volume of 8 µl and a column heater temperature of 30 °C. This method’s total run time was 6 min, using water as a diluent. Forced degradation experiments have verified that the approach is stability-indicating for the terlipressin injection dosage form assay. The analytical method has demonstrated a linear response over the 0.25–1.5 µg/ml concentration range, exhibiting an R² of 0.9994 and recovery percentage was 99.09–100.43%.

Polygonati Rhizoma, as a traditional medicinal herb, possesses pharmacological effects enhancing physical strength and immunity. In this study, a systematic analysis of the monosaccharide and non-polysaccharides components in Polygonati Rhizoma was conducted using pre-column derivatization high-performance liquid chromatography (HPLC–DAD) and liquid chromatography coupled to electrostatic orbitrap high-resolution mass spectrometry (LC–Orbitrap-MS) techniques. The polysaccharides from Polygonati Rhizoma were initially extracted, hydrolyzed, and derivatized with 1-phenyl-3-methyl-5-pyrazolone (PMP), resulting in the successful detection of five monosaccharides. The high sensitivity and specificity of the HPLC–DAD method were confirmed. Furthermore, by comparing the external standard method (ESM) and the quantitative analysis of multi-components by single-marker (QAMS) revealed that D-mannose is the most abundant monosaccharide in Polygonati Rhizoma. The LC–Orbitrap-MS analysis of Polygonati Rhizoma led to the identification of 53 compounds, including organic acids, amino acids, amides, saponins, alkaloids, esters, and others. This research provided significant data for the chemical composition analysis and the pharmacological basis study of Polygonati Rhizoma.

The aim of this paper was to present a rapid, simple, and straightforward high-performance liquid chromatography (HPLC) method for the determination of robenacoxib in plasma. Robenacoxib is a member of the COXIB group of nonsteroidal anti-inflammatory drugs developed for veterinary use. The method was validated based on the FDA Guidance for Industry: Bioanalytical Method Validation for selectivity, linearity, accuracy, precision, stability, and recovery. Methylene chloride was used in a liquid–liquid extraction that produced an average recovery of 97%. Chromatographic separation occurred on a Sunfire C₁₈ column (4.6 × 150 mm) using an isocratic combination of 0.025% trifluoroacetic acid in water and acetonitrile (50:50, v/v). Ultraviolet absorbance was measured at 275 nm and the flow rate was 1.1 mL/min. The method was linear in the concentration range of 0.1 to 50 µg/mL. The assay variability ranged from 2.2% to 9.2% while the accuracy was 100%. The lower limit of quantification for a 0.1 mL sample size was 0.1 µg/mL. The method was used for the determination of robenacoxib in plasma samples.

The demand for novel flavors and fragrance (F&F) compounds has increased, highlighting the need for a systematic design approach. Currently, the F&F industry relies heavily on experimental approaches without considering the potential consequences of altering the features that contribute to the fragrance of the compound. In silico approaches have great potential to identify the necessary features for creating novel F&F compounds. In the present study, Quantitative Structure–Property Relationship (QSPR) models were developed using 1208 compounds and simple 2D descriptors, focusing on the RI (retention index) as the endpoint to predict the olfactory properties of molecules. Feature selection was initially carried out by multi-layered stepwise regression followed by feature thinning using the Genetic Algorithm (GA) and optimal feature combination selection using the BSS (best subset selection) method. Final models were developed using the Partial Least Squares (PLS) method. Additionally, internal and external validation of the models was performed using different validation metrics suggesting that the developed models are reliable, predictive, reproducible, and robust. To enhance the external prediction of the developed models, an Intelligent Consensus Prediction (ICP) method was employed and CM3 (consensus model 3) (best selection of predictions (compound-wise) from individual models) was found to provide the best predictivity. The modeling descriptors suggested that the hydrophobicity, high molecular weight, aromaticity, and presence of large-size fragments (high percentage of carbon) enhance the RI values. Conversely, polarity and hydrophilicity decrease the RI values. This study can be used to optimize the stationary phase according to the flavor and fragrance compounds to obtain the desired retention index (RI values).

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