Adsorption Studies of Crystal Violet From Aqueous Solution Using Low Cost Material: Equilibrium and Kinetics Studies

Crystal violet (CV), one of the toxic dyes which are extensively used for dyestuffs, textile, paper and plastics industries. CV does not easily biodegrades in aqueous medium and show harmful effect on aquatic as well as human life. In the present work adsorption studies of CV onto husk powder of Red gram crop (Cajanuscajan) seed was examined in aqueous solution at 27.8ºC. The effects of initial concentration, adsorbent dose, temperature, and contact time etc were determined. Highest 81.49% adsorption efficiency recorded was for 50 mg/L solution concentration onto 2.5g of husk powder of Red gram crop seed. The applicability of Langmuir and Freundlich isotherm model was investigated, and the Langmuir adsorption isotherm model exhibited the best fit than Freundlich isotherm model with the experimental data. The adsorption follows pseudo-second-order kinetics

High Performance Liquid Chromatography-Size Exclusion Chromatography (Hplc-Sec) As an Efficient Tool for The Quantification of Polymers

Poly (lactide-co-glycolide acid) ( PLGA) is an extraordinary well-described polymer and has excellent pharmaceutical properties like high biocompatibility and good biodegradability. Hence, it is one of the most used materials for drug delivery and biomedical systems, also being present in several US Food and Drug Administration approved carrier systems and therapeutic devices. For both applications, the quantification of polymer is important. During the development of the production process, parameters like yield or loading efficacy are essential to be determined. Although PLGA is a well-defined biomaterial, it still lacks a sensitive and convenient quantification approach for PLGA-based systems. Thus, we present a new method for fast and precise quantification of PLGA by HPLC-SEC. The method includes a shorter run time of 20 minutes with a size exclusion column of 300mm x 8.0mm diameter, tetrahydrofuran as mobile phase and diluent, the detection was carried out using the refractive index detector. The developed method has a detection limit of 0.1 ppm, enabling the quantification of low amounts of PLGA. Compared to existing approaches, like gravimetric or nuclear magnetic resonance measurements, which are tedious or expensive, the developed method is fast, ideal for routine screening and it is selective since no interference. The developed method is validated in terms of selectivity, precision, linearity, accuracy and solution stability. Due to the high sensitivity and rapidity of the method, it is suitable for both, laboratory and industrial use  &nbsp

DEVELOPMENT AND VALIDATION OF A GRADIENT HPLC METHOD FOR QUANTIFICATION OF EDETATE DISODIUM IN LYOPHILIZED INJECTABLE DRUG PRODUCT

Objective: The present study was aimed to validate a developed reversed phase gradient high-performance liquid chromatography method for the quantitative determination of Edetate Disodium in the lyophilized injectable drug product. Methods: The amount of total Edetate disodium was analysed by HPLC assay using Edetate disodium USP as a reference standard. Injectable product was dissolved in acetone and Edetate disodium is separated out from API and then dissolved in water. Analysis was carried out using ferric chloride as a precolumn derivatizing reagent and YMC Pack ODS-A, 5 µm column with mobile phase as a mixture of tetrabutylammonium bromide buffer pH 2.8 and acetonitrile as the solvent, water used as diluent. The Edetate disodium quantified by U. V. wavelength at 254 nm. Results: The method was suitably validated with respect to specificity, linearity, precision, accuracy and solution stability, using this method the average recovery from spike sample is 98.2%, with a relative standard deviation of<3%. The minimal quantifiable level was 1.5 µg/ml. The results show that the procedure is accurate, precise and reproducible. Conclusion: In the present study an attempt has been made to develop and validate the analytical method for lyophilised injectable formulations and to generate the scientific database for formulation and evaluation of various lyophilised injectable containing Edetate disodium

Exploiting Anti-monotonicity of Multi-label Evaluation Measures for Inducing Multi-label Rules

Exploiting dependencies between labels is considered to be crucial for multi-label classification. Rules are able to expose label dependencies such as implications, subsumptions or exclusions in a human-comprehensible and interpretable manner. However, the induction of rules with multiple labels in the head is particularly challenging, as the number of label combinations which must be taken into account for each rule grows exponentially with the number of available labels. To overcome this limitation, algorithms for exhaustive rule mining typically use properties such as anti-monotonicity or decomposability in order to prune the search space. In the present paper, we examine whether commonly used multi-label evaluation metrics satisfy these properties and therefore are suited to prune the search space for multi-label heads.Comment: Preprint version. To appear in: Proceedings of the Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD) 2018. See http://www.ke.tu-darmstadt.de/bibtex/publications/show/3074 for further information. arXiv admin note: text overlap with arXiv:1812.0005

The Development, Verification and Evaluation of Container Closure Integrity Assessment of Prefilled Syringes Using Fluorescence Spectroflurometer

The preference of Prefilled syringes is increased over all the vials as container closure systems for liquid injections, when facilitated or self-administration is required.However, prefilled syringes are more complex compared to container closure system(CCS) consisting of vial, rubber stopper and flip off. Container closure integrity assurance and verification has been a specific challenge for prefilled syringes as they feature several sealing areas. A comprehensive understanding of the container closure system is necessary for an appropriate container closure integrity assessment as well as for packagingdevelopment and qualification. Method for the measurement ofcontainer closure integrity(CCI) of prefilled syringes using fluorescence spectrophotometry was developed and validated with a spectroflurometer.Methylene blue solution was initially evaluated as the fluorophore ina syringe with excitation at 605 nm and emission at 678 nm, which generated a limit of detection of 0.06µg/mL. Furtherstudies were conducted using Rhodamine 123, a dye with stronger fluorescence. Using 482 nm excitation and 527 nmemission, the dye in the syringe could be easily detected at levels as low as 0.001 µg/mL. The relative standard deviationfor sixmeasurements of three different sample with different concentration was less than 2.8%. A number of operational parameters were optimized, including the photomultiplier tube voltage, excitation, andemission slit widths. The specificity of container closure integrity was checked by using marketed drug products sample,which showed no interference to the rhodamine detection. Results obtained from this study demonstrated that usingrhodamine 123 for container closure integrity testing with in syringe fluorescence measurements significantlyenhanced the sensitivity and robustness of the testing and effectively overcame limitations of the traditional methylene bluemethod with visual or UV-visible absorption detection

Exploring RP-HPLC Method for analysis of Axitinib in Bulk and in-house Tablets

Axitinib is a tyrosine kinase Inhibiter. In a commenced analysis, a effortless and responsive high-performance liquid-chromatography method was developed and validated for the quantitative estimation of Axitinib in bulk and in-house tablet dosage form. The present method was developed and validated using LC-GC Qualisil BDS C18 (250 mm × 4.6 mm, 5 μm). The separation of Axitinib was employed using a methanol: water 85:15% v/vas a mobile phase at optimal flow rate 1 mL/min and column oven temperature 30°C. While, Axitinib was examined at 330 nm with a photo diode array detector; retention timewas found to be 3.23 min.The intended method was validated by ICH rules for the accuracy, precision, sensitivity, and ruggedness. The linearity was followed in the concentration range of 4 - 24 μg/ mL as demonstrated by correlation coefficient (r2) of 0.9994. The robustness of proposed method was assessed by purposelyvarying the chromatographic conditions. Consequently, the intended method can routinely be subjected for th estimation of Axitinib in bulk and in tablets formulation

How Incorporating Feedback Mechanisms in a DSS Affects DSS Evaluations

Model-based decision support systems (DSSs) improve performance in many contexts that are datarich, uncertain, and require repetitive decisions. But such DSSs are often not designed to help users understand and internalize the underlying factors driving DSS recommendations. Users then feel uncertain about DSS recommendations, leading them to possibly avoid using the system. We argue that a DSS must be designed to induce an alignment of a decision maker’s mental model with the decision model embedded in the DSS. Such an alignment requires effort from the decision maker and guidance from the DSS. We experimentally evaluate two DSS design characteristics that facilitate such alignment: (i) feedback on the upside potential for performance improvement and (ii) feedback on corrective actions to improve decisions. We show that, in tandem, these two types of DSS feedback induce decision makers to align their mental models with the decision model, a process we call deep learning, whereas individually these two types of feedback have little effect on deep learning. We also show that deep learning, in turn, improves user evaluations of the DSS. We discuss how our findings can potentially lead to DSS design improvements and better returns on DSS investments