DEVELOPMENT OF SIMPLE HPLC METHOD TO ESTIMATE THE BLOOD PLASMA CONCENTRATION OF EFAVIRENZ IN RAT AFTER ORAL ADMINISTRATION

Objective: The present study was design with an objective of developing a simple and rapid high performance liquid chromatography (HPLC) method for the determination of Efavirenz (EFA) in rat plasma.Methods: Chromatographic separation was achieved on C18 column using acetonitrile-50 mM potassium phosphate (55:45 v/v) as mobile phase at a flow rate of 1 ml/min and UV detection at 250 nm.Results: The retention time of EFA was found to be 13.2 min. The developed method was validated for linearity, limit of quantification (LOQ), limit of detection (LOD), Stability and selectivity. Linearity studies were found to be acceptable over the range of 5-50 μg/ml.Conclusion: The present analytical method was found to be specific, sensitive, accurate and precise for quantification of EFA in rat plasma. It can be successively applied for pharmacokinetics studies also.Â

Probabilistic Solar Proxy Forecasting with Neural Network Ensembles

Space weather indices are used commonly to drive forecasts of thermosphere density, which directly affects objects in low-Earth orbit (LEO) through atmospheric drag. One of the most commonly used space weather proxies, $F_{10.7 cm}$, correlates well with solar extreme ultra-violet (EUV) energy deposition into the thermosphere. Currently, the USAF contracts Space Environment Technologies (SET), which uses a linear algorithm to forecast $F_{10.7 cm}$. In this work, we introduce methods using neural network ensembles with multi-layer perceptrons (MLPs) and long-short term memory (LSTMs) to improve on the SET predictions. We make predictions only from historical $F_{10.7 cm}$ values, but also investigate data manipulation to improve forecasting. We investigate data manipulation methods (backwards averaging and lookback) as well as multi step and dynamic forecasting. This work shows an improvement over the baseline when using ensemble methods. The best models found in this work are ensemble approaches using multi step or a combination of multi step and dynamic predictions. Nearly all approaches offer an improvement, with the best models improving between 45 and 55\% on relative MSE. Other relative error metrics were shown to improve greatly when ensembles methods were used. We were also able to leverage the ensemble approach to provide a distribution of predicted values; allowing an investigation into forecast uncertainty. Our work found models that produced less biased predictions at elevated and high solar activity levels. Uncertainty was also investigated through the use of a calibration error score metric (CES), our best ensemble reached similar CES as other work.Comment: 23 pages, 12 figures, 5 Table

Dry Powder Inhalers: A Focus on Advancements in Novel Drug Delivery Systems

Administration of drug molecules by inhalation route for treatment of respiratory diseases has the ability to deliver drugs, hormones, nucleic acids, steroids, proteins, and peptides, particularly to the site of action, improving the efficacy of the treatment and consequently lessening adverse effects of the treatment. Numerous inhalation delivery systems have been developed and studied to treat respiratory diseases such as asthma, COPD, and other pulmonary infections. The progress of disciplines such as biomaterials science, nanotechnology, particle engineering, molecular biology, and cell biology permits further improvement of the treatment capability. The present review analyzes modern therapeutic approaches of inhaled drugs with special emphasis on novel drug delivery system for treatment of various respiratory diseases

Set up errors in Brain tumours – A retrospective study to review the current practice of PTV margins in the institution

Set up errors in Brain tumours – A retrospective study to review the current practice of PTV margins in the institution Chaturvedi D.1 , Mehta A.2 , Kumar P.3*   1 Diksha Chaturvedi, Junior Resident, Department of Radiation Oncology, Shri Ram Murti Institute of Medical Sciences, Bareilly, Uttar Pradesh, India. 2 Ankita Mehta, Senior Resident, Department of Radiation Oncology, Shri Ram Murti Institute of Medical Sciences, Bareilly, Uttar Pradesh, India. 3* Piyush Kumar, Professor and Head, Department of Radiation Oncology, Shri Ram Murti Institute of Medical Sciences, Bareilly, Uttar Pradesh, India. Corresponding Author: Dr. Piyush Kumar, Professor and Head, Department of Radiation Oncology, all authors are affiliated to Shri Ram Murti Institute of Medical Sciences, Bareilly, Uttar Pradesh, India, E-mail: [email protected]   Abstract Background Radiotherapy in brain tumors needs accuracy and reproducibility of the patient’s position. There may be set up errors which are taken care by adding planning target volume (PTV) margin. Lesser PTV margins may lead to tumor miss or greater margins may lead to unnecessary radiation of normal brain tissue. The present study is done to evaluate whether the current practice of PTV margins in our institute is optimum or not. Materials and methods Eleven patients of brain tumours who received adjuvant radiotherapy were retrospectively selected for determining the setup errors. These patients were immobilised in supine position and contrast enhanced CT of head was taken for radiotherapy planning. Delineation of gross tumor volume and clinical target volume was done with 5 mm PTV margin. The treatment was delivered by 3-Dimensional Conformal Radiotherapy or Intensity Modulated Radiotherapy Technique. The set up errors in three dimensions were determined retrospectively for all images. PTV margins were calculated using International Commission on Radiation Units And Measurements Report 62, Stroom’s and Van Herk formulae. Results The overall population set up error was 0.034,-0.048, 0.028 in X, Y, Z directions respectively. The population systematic error was calculated to be 0.107, 0.069, 0.092 and population random error was 0.221, 0.202, 0.217 in X, Y, Z directions respectively. The calculated setup margin as per the three formulas was less than 5 mm in all directions. Conclusion The present study showed that the institutional protocol of 5 mm is optimum to counter the setup errors.&nbsp

Formulation and characterization of caffeine biodegradable chewing gum delivery system for alertness using plasticized poly (D,L-lactic acid) as gum base

Purpose: To formulate and evaluate biodegradable plasticized poly(D,L-lactic acid) as a base for caffeine-medicated chewing gums (MCGs) to increase alertness.Methods: Biodegradable plasticized poly(D,L-lactic acid) caffeine-MCGs were formulated with a fixed concentration (15 % w/w) of different plasticizers for different formulations. Substances used as plasticizers were triacetin, stearic acid, PEG-600, tributyl citrate, soya oil, sunflower oil, glycerol, triethyl citrate, PEG-4000, and castor oil. The characteristics of the gum formulations were examined using texture profile analysis (TPA), and also evaluated for biodegradation, microstructure`, in vitro drug release, and sensory features.Results: The MCG-1 and MCG-7 formulations with triacetin and glycerol as plasticizers, respectively, exhibited a biodegradation score of 1 and 2, respectively, indicating considerable biodegradation. The formulation with triacetin as a plasticizer exhibited TPA values of 3750.52 g, -51.13 g.s, 1580.88, 1526.23, and 0.364 for hardness, adhesiveness, gumminess, chewiness, and cohesiveness, respectively; these values are similar to those of the Military Energy Gum. The microstructure of the gum base was characterized using scanning electron microscopy to determine surface properties. The in vitro drug release was determined as 97 % after a mean chewing time of 15 min by using a specially designed in vitro chewing machine.Conclusion: Plasticized poly (D,L-lactic acid) gum formulation is suitable for the delivery of caffeine and can be used as an alternative MCG for effective management of fatigue

Pharmacokinetic profile of phytoconstituent(s) isolated from medicinal plants—A comprehensive review

AbstractHerbal medicine, the backbone of traditional medicine, has played an important role in human health and welfare for a long period. Traditional therapeutic approaches of regional significance are found in Africa, South and Central America, China, India, Tibet, Indonesia, and the Pacific Islands. The considerable scientific significance and commercial potential of traditional medicines have resulted in increased international attention and global market demands for herbal medicines, especially Chinese herbal medicines. Herbal medicines currently are the primary form of health care for the poor in the developing countries, and also are widely used as a supplement or substitute for conventional drugs in developed countries. These traditional medicines have a pivotal role in the treatment of various ailments and more than 50% of drugs used in Western pharmacopoeia are isolated from herbs or derived from modifications of chemicals found in plants. Herbal medicines usually contain a complex mixture of various bioactive molecules, which make its standardization complicated, and there is little information about all compounds responsible for pharmacological activity. Several research papers have been published that claim pharmacological activity of herbal medicines but few are discussing the role of the exact phytoconstituent. Understanding the pharmacokinetic profile of such phytoconstituents is essential. Although there are research papers that deal with pharmacokinetic properties of phytoconstituents, there are a number of phytoconstituents yet to be explored for their kinetic properties. This article reviews the pharmacokinetic profile of 50 different therapeutically effective traditional medicinal plants from the year 2003 onward

TECHNIQUES USED FOR BIOCHEMICAL INVESTIGATION IN RELATION TO FORENSIC ANALYSIS

The aim of this review was to apply the knowledge & technology of science for the definition & enforcement of such laws. The forensic analysis is investigation the crime and examines material evidence. In forensic analysis various biochemical investigation techniques are used to examine the crimes like Hair analysis, Polygraphic test, serology test and finger print analysis. Several instruments are used in forensic analysis like IR, Chromatography, UV and Mass spectrophotometer. The characterization results showed that Forensic pharmacists engage in work relating to litigation, the regulatory process, or the criminal justice system

Advanced Ensemble Modeling Method For Space Object State Prediction Accounting For Uncertainty In Atmospheric Density

For objects in the low Earth orbit region, uncertainty in atmospheric density estimation is an important source of orbit prediction error, which is critical for space traffic management activities such as the satellite conjunction analysis. This paper investigates the evolution of orbit error distribution in the presence of atmospheric density uncertainties, which are modeled using probabilistic machine learning techniques. The recently proposed HASDM-ML, CHAMP-ML, and MSIS-UQ machine learning models for density estimation (Licata and Mehta, 2022b; Licata et al., 2022b) are used in this work. The investigation is convoluted because of the spatial and temporal correlation of the atmospheric density values. We develop several Monte Carlo methods, each capturing a different spatiotemporal density correlation, to study the effects of density uncertainty on orbit uncertainty propagation. However, Monte Carlo analysis is computationally expensive, so a faster method based on the Kalman filtering technique for orbit uncertainty propagation is also explored. It is difficult to translate the uncertainty in atmospheric density to the uncertainty in orbital states under a standard extended Kalman filter or unscented Kalman filter framework. This work uses the so-called consider covariance sigma point (CCSP) filter that can account for the density uncertainties during orbit propagation. As a testbed for validation purposes, a comparison between CCSP and Monte Carlo methods of orbit uncertainty propagation is carried out. Finally, using the HASDM-ML, CHAMP-ML, and MSIS-UQ density models, we propose an ensemble approach for orbit uncertainty quantification for four different space weather conditions