DEVELOPMENT OF ORALLY DISINTEGRATING TABLETS OF MEMANTINE HYDROCHLORIDE-A REMEDY FOR ALZHEIMER’S DISEASE

Objective: The study is directed towards the development of an orally disintegrating drug delivery system of memantine hydrochloride which can be commercially exploited for the well-being of society for the treatment of Alzheimer’s disease, which is a most common form of dementia. Methods: Orally disintegrating immediate-release tablets of memantine hydrochloride were prepared and optimized for disintegration time and in vitro drug release. The top spray granulation method was used for the preparation of granules. Subsequently, these granules were compressed to tablets. The levels of diluent, disintegrant and taste-masking agents were optimized using the design of experiments. The resulting tablets were evaluated for disintegration time and in vitro drug release. The optimized formulation was subjected to accelerated stability study for 3 mo. Results: The optimized orally disintegrating tablet formulation exhibited a disintegration time of 2-3 min and complete drug release i.e. more than 85 % drug release within 10 min while performing in vitro drug release study. This is a prerequisite for faster action in the case of patients suffering from Alzheimer’s disease. Accelerated stability studies indicated good physical and chemical stability of the optimized formulation. Conclusion: Developed orally disintegrating tablet formulation of memantine hydrochloride could release the drug faster compared to conventional immediate-release tablets which is useful in paediatric, geriatric and psychiatric patients

Modeling of Late Blooming Phases and Precipitation Kinetics in Aging Reactor Pressure Vessel (RPV) Steels

The principle work at the atomic scale is to develop a predictive quantitative model for the microstructure evolution of RPV steels under thermal aging and neutron radiation. We have developed an AKMC method for the precipitation kinetics in bcc-Fe, with Cu, Ni, Mn and Si being the alloying elements. In addition, we used MD simulations to provide input parameters (if not available in literature). MMC simulations were also carried out to explore the possible segregation/precipitation morphologies at the lattice defects. First we briefly describe each of the simulation algorithms, then will present our results

Formulation Development Of Nanoparticulate Formulation In Ophthalmic Drug Delivery System

The major challenge faced by today’s pharmacologist and formulation scientist is ocular drug delivery. Topical eye drop is the most convenient and patient compliant route of drug administration, especially for the treatment of anterior segment diseases. Delivery of drugs to the targeted ocular tissues is restricted by various precorneal, dynamic and static ocular barriers. Also, therapeutic drug levels are not maintained for longer duration in target tissues. So, the present work on ocular drug delivery research make advanced towards developing a novel, safe and patient compliant formulation and drug delivery devices/techniques, which may surpass these barriers and maintain drug levels in tissues. Anterior segment drug delivery advances are witnessed by modulation of conventional topical solutions with permeation and viscosity enhancers. Also, it includes development of nano formulations have also been introduced for anterior segment ocular drug delivery. these novel devices and/or formulations are easy to formulate, no/negligibly irritating, possess high precorneal residence time, sustain the drug release, and enhance ocular bioavailability of therapeutics. An update of current research advancement in ocular drug delivery necessitates and helps drug delivery scientists to modulate their process and develop novel and safe drug delivery strategies followed by current nanotechnology-based formulation developments and also, recent developments with other ocular drug delivery strategies employing in situ formulation. &nbsp

Fast Association Tests for Genes with FAST

Gene-based tests of association can increase the power of a genome-wide association study by aggregating multiple independent effects across a gene or locus into a single stronger signal. Recent gene-based tests have distinct approaches to selecting which variants to aggregate within a locus, modeling the effects of linkage disequilibrium, representing fractional allele counts from imputation, and managing permutation tests for p-values. Implementing these tests in a single, efficient framework has great practical value. Fast ASsociation Tests (Fast) addresses this need by implementing leading gene-based association tests together with conventional SNP-based univariate tests and providing a consolidated, easily interpreted report. Fast scales readily to genome-wide SNP data with millions of SNPs and tens of thousands of individuals, provides implementations that are orders of magnitude faster than original literature reports, and provides a unified framework for performing several gene based association tests concurrently and efficiently on the same data. Availability: https://bitbucket.org/baderlab/fast/downloads/FAST.tar.gz, with documentation at https://bitbucket.org/baderlab/fast/wiki/Hom

A Brief Review of the Medicinally Important Indole Derivatives

Indole is an exceptional heterocyclic molecule with a broad spectrum of pharmacological activity owing to various modes of action. It is also a versatile pharmacophore and a favored scaffold. For drug development, it is an excellent moiety whose only characteristic is that it resembles many protein structures. Plenty of research has been taking place in recent years to synthesize and explore the various therapeutic prospective of this moiety. This review summarizes some of the recent effective chemical synthesis (2014-2018) for indole ring. Some of the most recent efficient chemical synthesis for the indole ring (from 2014 to 2018) is compiled in this review. The structure-activity relationship (SAR) was also given a lot of weight in this review in order to pinpoint the active pharmacophores of different indole analogues that have been the subject of studies for the past five years and are responsible for a variety of effects, including antiviral, antitubercular, anticancer, and anticonvulsant ones. The goals and framework of every research issue are explained in detail to help medicinal chemists have a deeper understanding of the circumstances contextually. Researchers will undoubtedly use this review as a platform to strategically design a variety of novel indole derivatives with lower toxicity and side effects and a range of intriguing pharmacological activit

Modeling the Ductile Brittle Fracture Transition in Reactor Pressure Vessel Steels Using a Cohesive Zone Model Based Approach

Fracture properties of Reactor Pressure Vessel (RPV) steels show large variations with changes in temperature and irradiation levels. Brittle behavior is observed at lower temperatures and/or higher irradiation levels whereas ductile mode of failure is predominant at higher temperatures and/or lower irradiation levels. In addition to such temperature and radiation dependent fracture behavior, significant scatter in fracture toughness has also been observed. As a consequence of such variability in fracture behavior, accurate estimates of fracture properties of RPV steels are of utmost importance for safe and reliable operation of reactor pressure vessels. A cohesive zone based approach is being pursued in the present study where an attempt is made to obtain a unified law capturing both stable crack growth (ductile fracture) and unstable failure (cleavage fracture). The parameters of the constitutive model are dependent on both temperature and failure probability. The effect of irradiation has not been considered in the present study. The use of such a cohesive zone based approach would allow the modeling of explicit crack growth at both stable and unstable regimes of fracture. Also it would provide the possibility to incorporate more physical lower length scale models to predict DBT. Such a multi-scale approach would significantly improve the predictive capabilities of the model, which is still largely empirical