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Quality by Design (QbD) has become popular within the pharmaceutical industry and the FDA has cited a risk-based approach to drug development as a desirable state for the near future.1 In this state, more complete information and transparency relating to risk assessment will be made available for new drug aplications speeding the approval process, and preventing late-stage failures.

Characterizing metabolite structures and metabolic pathways is essential to understanding the potential biological implications of compounds in drug discovery.

Characterizing metabolite structures and metabolic pathways is essential to understanding the potential biological implications of compounds in drug discovery.

Metabolic stability, determined in liver microsomes, is one of the primary assays used in early drug discovery. A key factor limiting compound half-life is the cytochrome P450 mediated metabolism. High clearance by these enzymes implies a higher and more frequent dosing as well as poses a risk for individual variations in exposure.

Analytical identification of metabolites for a drug candidate is usually a time consuming and low-throughput task which is performed only in late drug development phases. Therefore the ability to predict possible sites of human liver microsomal metabolism using in silico techniques would be highly beneficial for any medicinal chemist.

This study presents the application of recently introduced GALAS modeling methodology for estimating toxicity of chemicals to several aquatic species. Experimental data were expressed as median lethal concentration of test compound in water (LC50) and the data set contained 904 LC50 values for fishes (Pimephales promelas) and 589 LC50 values for crustaceans (Daphnia magna).

This study presents a novel approach to aid this assessment based on probabilistic predictors of mutagenicity in Ames test and binding to Estrogen Receptor, supplemented by a knowledge-based system of structural alerts.

A proprietary and structurally diverse fragment library has been created and screened for a variety of Gprotein coupled receptors (GPCRs) and a number of other drug targets. The data allows for a fragment-based chemogenomics study to interrogate the interactions of GPCRs and their ligands.

In this research analyzing of corporate social responsibility activities and impact of it on hotel industries has been examined through a case study.

A study of the Tuul River water pollution was carried out in surrounding area of Ulaanbaatar, the capital of Mongolia at 14 monitoring sites, using a dataset between 1998-2008. An index method applied to assess water quality and seven hydro-chemicals used in the index calculation. The research indicates that the river is not polluted until the Ulaanbaatar and the contamination level spike appears when the river entering the city.