Quantification Of Ingredients Research Articles

Purchasing “Nootropics” Online: Identification and Quantification of Ingredients in Phenibut-Containing Products

Background and Objectives: Phenibut is a central nervous system drug that is registered and used in clinical practice as a prescription medication. In recent decades, the drug has become popular as a “nootropic and cognition enhancer” because of its active marketing as a dietary or food supplement sold online. This has resulted in a growing number of case reports on acute toxicity and withdrawal symptoms and has raised concerns about the quality of phenibut-containing products. Materials and Methods: We used high-performance liquid chromatography with diode-array detection and ultra-performance liquid chromatography–mass spectrometry to investigate the quality of six phenibut-containing samples purchased from three internet suppliers. Results: Substantially lower levels of the active pharmaceutical ingredient than claimed on the packaging were found for three of the supplements tested. A considerably higher level of phenibut was present in one product. All online-purchased phenibut-containing capsules included declared and undeclared ingredients found in various dietary supplements claiming to have metabolic, neurotropic, antioxidant, anti-inflammatory, and neuroprotective properties. Conclusions: The online-purchased phenibut products contained undeclared ingredients and the content of phenibut differed from the declared. The combinations of these additional ingredients with phenibut have not been tested for activity or safety and their use warrants further attention to avoid potential health problems.

Quality evaluation of ginkgo biloba leaves based on non-targeted metabolomics and representative ingredient quantification

Ultra-performance liquid chromatography coupled with time-of-flight mass spectrometry (UPLC-Q-TOF-MS/MS) combined with multivariate statistical analysis was applied to the study of plant metabolomics to reveal the factors affecting the content of ginkgo leaf compounds. As a follow-up analysis, the terpene lactones and ginkgolic acids were quantified simultaneously using ultra-performance liquid chromatography coupled with triple quadrupole mass spectrometry (UPLC-QqQ-MS/MS), and subsequently total flavonol glycosides were quantified by high-performance liquid chromatography (HPLC). The results revealed that a total of 52 compounds were potentially identified by establishing a database, and 10 compounds were verified by reference standards; terpene lactones, ginkgolic acids, and flavonoids were the differential compounds; and ginkgolide A was identified as an important indicator compound for tree age. In addition, quantitative analysis showed that the contents of total flavonol glycosides and terpene lactones were highest during April and August in young ginkgo leaves, and differed based on origin. In summary, numerous compounds were rapidly detected by liquid chromatography coupled with MS, the ginkgo leaf samples were compared, and the differential metabolites were screened out. The content changing rules of the target compounds in ginkgo leaves from different regions with different tree ages and harvesting periods were clarified.

Comparative study on brain pharmacokinetics of Buyang Huanwu Decoction in normal and cerebral ischemia rats using brain microdialysis combined with LC-MS/MS

ObjectiveTo conduct a comparative study on the brain pharmacokinetics of seven ingredients (i. e. senkyunolide A, ferulic acid, formononetin, calycosin, ononin, calycosin-O-β-D-glucopyranoside, and paeoniflorin), which were the compounds of Buyang Huanwu Decoction (BHD), in normal and cerebral ischemia rats administrated intragastrically with BHD. MethodsThe samples of normal and permanent middle cerebral artery occlusion (pMCAO) rats were collected by using brain microdialysis technique. The concentrations of seven ingredients were determined by the HPLC-MS/MS method. After the BHD were administrated intragastrically to the rats for seven consecutive days, brain microdialysis probes were inserted into the hippocampus of rats, and then the brain microdialysates were collected at 20 min time intervals for 5 h. The separation of the seven ingredients and internal standard (IS) was carried out on an ACQUITY UPLC BEH C18 (2.1 mm × 100 mm, 1.7 μm) chromatographic column, using a mobile phase consisting of acetonitrile (containing 0.1% formic acid) and water (containing 0.1% formic acid) for gradient elution within 13 min. The ionization was conducted using an ESI source in positive ion mode. Multiple reaction monitoring mode was used for quantification of ingredients in BHD. ResultsLinearity, accuracy, precision, matrix effect and stability of LC-MS/MS method were all satisfactory, successfully applied to compare the pharmacokinetics of the analytes between normal and model rats after intragastric administration of BHD. Compared with the normal group, the model group after the administration of the BHD showed that T1/2 of formononetin and ononin were longer, and except for calycosin-O-β-D-glucopyranoside (P < 0.01), there was no significant difference between the normal group and the model group. The Cmax of senkyunolide A and calycosin of model group were increased, while the Tmax of senkyunolide A was decreased, and except for the Tmax of PF, the differences between the two groups were statistically significant (P < 0.01). ConclusionThe LC-MS/MS method combined with microdialysis was successfully applied to the comparative study of brain pharmacokinetics of seven ingredients in BHD. After intragastric administration of BHD, there were differences in the pharmacokinetics of seven ingredients in the brain hippocampus between normal rats and model rats, probably related to the characteristics of the ingredients and the effects of cerebral ischemia on the absorption and distribution of the ingredients.

Fast ingredient quantification in multigrain flour mixes using hyperspectral imaging

In the past decade, hyperspectral imaging has emerged and matured into one of the most powerful and rapidly growing methods for non-destructive food quality analysis and control. This paper demonstrates fast and automatic quantification of food ingredients with hyperspectral imaging in the visible and near-infrared range in combination with chemometrics and image processing techniques. The application of ingredient quantification in bread flour recipes requires high spatial resolution in addition to spectral discrimination power. Our results show that automatic and accurate quantification of all ingredients can be done, reaching pixel discrimination accuracies above 90% and ingredient quantification errors within the required 1% absolute error in weight. The classification accuracy obtained using 15 wavebands on the test images is around 15% higher than what was obtained with colour imaging.

Investigation of Direct Model Transferability Using Miniature Near-Infrared Spectrometers.

Recent developments in compact near infrared (NIR) instruments, including both handheld and process instruments, have enabled easy and affordable deployment of multiple instruments for various field and online or inline applications. However, historically, instrument-to-instrument variations could prohibit success when applying calibration models developed on one instrument to additional instruments. Despite the usefulness of calibration transfer techniques, they are difficult to apply when a large number of instruments and/or a large number of classes are involved. Direct model transferability was investigated in this study using miniature near-infrared (MicroNIR™) spectrometers for both classification and quantification problems. For polymer classification, high cross-unit prediction success rates were achieved with both conventional chemometric algorithms and machine learning algorithms. For active pharmaceutical ingredient quantification, low cross-unit prediction errors were achieved with the most commonly used partial least squares (PLS) regression method. This direct model transferability is enabled by the robust design of the MicroNIR™ hardware and will make deployment of multiple spectrometers for various applications more manageable.

A qHNMR method for simultaneous quantification of terpenoids from Ferula ovina (Boiss.) Boiss roots

Ferula ovina (Boiss.) Boiss is one of the most important endemic medicinal plants in Iran, which has three main terpenoid compounds including ferutinin, stylosin and tschimgine. Ferutinin is the strongest natural phytoestrogen that has agonistic activity on estrogen receptors, particularly α-receptors. To determine the amount of ferutinin in F. ovina roots, we firstly used HPLC-UV method. In the HPLC method, the resolution of ferutinin from the two other compounds, stylosin and tshimgine, was poor. Therefore, we decided to use qHNMR method for simultaneous quantification of ferutinin, stylosin and tshimgine in the plant roots. Quantitative 1H-NMR (qHNMR) was carried out based on the relative ratio of signal integration of each compound [(H-1 for tschimgine (δH 4.94–5.03), OCH3 for stylosin (δH 3.8), and H-9 for ferutinin (δH 5.58)] to certain amount of the internal standard dimethyl sulfone (DMSO2). The qHNMR method showed good precision (intra-day RSD ≤ 2.31%, inter-day RSD ≤ 2.72%), linearity (in the ranges of 1.3–10.41, 1.2–9.7 and 1.1–9.02 mg/mL with correlation coefficients at 0.9991), repeatability (RSD ≤ 2.99%) and stability (RSD ≤ 2.4%) for the quantification of the compounds. This work confirmed that qHNMR represents a feasible alternative to high-performance liquid chromatography based methods for simultaneous quantification of ingredients in plant extracts.

High Performance Thin Layer Chromatography: A Mini Review

High Performance Thin layer Chromatography (HPTLC) technique is a sophisticated and automated form of the thin-layer chromatography (TLC) with better and advanced separation efficiency and detection limits, and is often an excellent alternative to GC and HPLC. Applications of HPTLC include phytochemical and biomedical analysis, herbal drug quantification, active ingredient quantification, fingerprinting of formulations, and check for adulterants in the formulations. HPTLC is useful in detecting chemicals of forensic concern. Various advance techniques in reference to HPTLC like hyphenations in HPTLC-MS, HPTLC-FTIR and HPTLC-Scanning Diode Laser have made HPTLC a power analytical tool in the field of analysis. Experts are of the opinion that HPTLC future to combinatorial approach and the utilization of instrumental HPTLC toward the analysis of drug formulations, bulk drugs, and natural products will increase in the future

Method development and validation for pharmaceutical tablets analysis using transmission Raman spectroscopy

The objective of the study is to demonstrate the development and validation of a transmission Raman spectroscopic method using the ICH-Q2 Guidance as a template. Specifically, Raman spectroscopy was used to determine niacinamide content in tablet cores. A 3-level, 2-factor full factorial design was utilized to generate a partial least-squares model for active pharmaceutical ingredient quantification. Validation of the transmission Raman model was focused on figures of merit from three independent batches manufactured at pilot scale. The resultant model statistics were evaluated along with the linearity, accuracy, precision and robustness assessments. Method specificity was demonstrated by accurate determination of niacinamide in the presence of niacin (an expected related substance). The method was demonstrated as fit for purpose and had the desirable characteristics of very short analysis times (∼2.5s per tablet). The resulting method was used for routine content uniformity analysis of single dosage units in a stability study.

Interference-blind microfluidic sensor for ascorbic acid determination by UV/vis spectroscopy

A microfluidic sensor is developed and targeted at specific ingredients determination in drug/food/beverage matrices. The surface of a serpentine polydimethylsiloxane (PDMS) microchannel is modified by enzyme via physisorption. When solutions containing target ingredients pass through the microfluidic channel, enzyme-catalyzed reaction occurs and only converts the target molecules to its products. The whole process is monitored by an end-channel UV/vis spectroscopic detection. Ascorbate oxidase and l-ascorbic acid (AA) are taken as enzyme-substrate model in this study to investigate the feasibility of using the developed strategy for direct quantification of AA in standard solutions and complex matrices. A dietary supplement product, Vitamin C tablet, is chosen as a model matrix to test the microfluidic bio-sensor in real-sample analysis. The results illustrate that the established microfluidic bio-sensor exhibits good reproducibility, stability, and anti-interference property. Technically, it is easy to realize, depends on low investment in chip fabrication, and simple instrumental procedure, where only UV/vis spectrophotometer is required. To sum up, the developed strategy is economical, specific, and accurate, and can be potentially used for fast quantification of ingredient in samples with complex matrix background. It is promising to be widely spread in food industry and quality control department.

Validation of an in-line Raman spectroscopic method for continuous active pharmaceutical ingredient quantification during pharmaceutical hot-melt extrusion

A calibration model for in-line API determination was developed based on Raman spectra collected during hot-melt extrusion. This predictive model was validated by calculating the accuracy profile based on the analysis results of validation experiments. Furthermore, based on the data of the accuracy profile, the measurement uncertainty was determined. Finally, the robustness of the model was evaluated.A Raman probe was implemented in the die of a twin-screw extruder, to monitor the drug concentration during extrusion of physical mixtures containing 15, 20, 25, 30 and 35% (w/w) metoprolol tartrate (MPT) in Eudragit® RS PO, an amorphous copolymer of acrylic and methacrylic acid esters with a low content of quaternary ammonium groups, which are present as salts. Several different calibration models for the prediction of the MPT content were developed, based on the use of single spectra or averaged spectra, and using partial least squares (PLS) regression or multivariate curve resolution (MCR). These predictive models were validated by extruding and monitoring mixtures containing 17.5, 22.5, 25.0, 27.5 and 32.5% (w/w) MPT. Each validated concentration was monitored on three different days, by two different operators. The β-expectation tolerance intervals were calculated for each model and for each of the validated MPT concentration levels (β was set at 95%), and acceptance limits were set at 10% (relative bias), indicating that at least 95% of future measurements should not deviate more than 10% from the true value. The only model where these acceptance limits were not exceeded was the MCR model based on averaged Raman spectra. The uncertainty measurements for this model showed that the unknown true value can be found at a maximum of ±7.00% around the measured result, with a confidence level of 95%. The robustness of this model was evaluated via an experimental design varying throughput, screw speed and barrel temperature. The robustness designs showed no significant influence of any of the process settings on the predicted concentration values.Raman spectroscopy proved to be a fast, non-destructive and reliable method for the quantification of MPT during hot-melt extrusion. From the accuracy profile of the MCR model based on averaged spectra, it was concluded that for each MPT concentration in the validated concentration range, 95 out 100 future routine measurements will be included within the acceptance limits (10%).

Pharmacodynamic Evaluation and Physical/Chemical Analysis of Two Formulations of Propofol used in Target-Controlled Infusion

Background and objectivesThere are several formulations of propofol available to the anesthesiologist for clinical use. The aim of this study was to analyze the physicochemical properties, pharmacodynamic effect, and pharmaceutical and clinical equivalence of the reference drug propofol as well as a similar formulation. MethodSixteen volunteers were enrolled in this randomized, double-blind, and paired study of Diprivan® and Propovan® formulations. Formulations were given as target-controlled infusion with target concentration of 3.0μg.mL−1 for 15 minutes. Variables studied were the area under the curve (AUC) of the bispectral index (BIS) graph regarding time, minimum BIS reached and time to reach it, and recovery time. The two formulations were sent to analysis of particle size of lipid emulsion, surface potential, and active principle quantification. ResultsThere was no difference between the formulations when comparing AUC, minimum BIS reached and time to reach it. The similar formulation recovery time was lower compared to the reference formulation (eight and 10min, respectively, p=0.014). Mean particle size of lipid emulsion, surface potential, and active ingredient quantification were similar for both formulations. ConclusionThere was no clinically significant difference between the use of propofol, reference Diprivan®, and the similar Propovan® during infusion. However, the recovery time was longer with the reference drug. Although analysis of both formulations studied show similar results regarding its physicochemical characterization, further studies should be conducted to justify this difference.

Pharmacodynamic Evaluation and Physical/Chemical Analysis of Two Formulations of Propofol used in Target-Controlled Infusion

Background and objectivesThere are several formulations of propofol available to the anesthesiologist for clinical use. The aim of this study was to analyze the physicochemical properties, pharmacodynamic effect, and pharmaceutical and clinical equivalence of the reference drug propofol as well as a similar formulation. MethodSixteen volunteers were enrolled in this randomized, double-blind, and paired study of Diprivan® and Propovan® formulations. Formulations were given as target-controlled infusion with target concentration of 3.0μg.mL-1 for 15minutes. Variables studied were the area under the curve (AUC) of the bispectral index (BIS) graph regarding time, minimum BIS reached and time to reach it, and recovery time. The two formulations were sent to analysis of particle size of lipid emulsion, surface potential, and active principle quantification. ResultsThere was no difference between the formulations when comparing AUC, minimum BIS reached and time to reach it. The similar formulation recovery time was lower compared to the reference formulation (eight and 10min, respectively, p = 0.014). Mean particle size of lipid emulsion, surface potential, and active ingredient quantification were similar for both formulations. ConclusionThere was no clinically significant difference between the use of propofol, reference Diprivan®, and the similar Propovan® during infusion. However, the recovery time was longer with the reference drug. Although analysis of both formulations studied show similar results regarding its physicochemical characterization, further studies should be conducted to justify this difference.