This article deals with the in – silico techniques for predicting the toxicity of chemical compounds. Toxicology is the branch of biology
that deals with the study of adverse effect of chemical substances on the living organisms and the practice of treating and preventing
such adverse effects. Predicting toxicity of a new drug to be produced is the first aim of preclinical trials. It is achieved by in-silico
methods. There are several in - silico technique softwares which are used for the prediction of ADME and hence toxicity of drugs. In
– silico methods involves the use of various softwares to calculate and then predict the toxicity of a compound by first determining
its structural and pharmacokinetic and pharmacodynamic properties and then it correlates this information with already existing
drugs and molecules and thus gives us conclusion. The article focuses on QSAR and its techniques, HQSAR, several other methods like
structural alerts and rule-based models, chemical category and read across model, dose and time response model, virtual ligand
screening, docking, 3D pharmacophore mapping, simulation approaches, PKPD models and several other approaches like
bioinformatics. After reviewing and studying various in silico techniques the conclusion comes out to be that, in-silico methods of
predictive toxicology are more better than in-vitro and in-vivo methods since they are much more safe (as animals are not harmed),
economic, fast and accurate w.r.to, results/output in predicting toxicity of compounds by computational methods and hence are
widely used in the production of new drug for accessing its toxicity
Predicting Absorption-Distribution Properties of Neuroprotective Phosphine-Borane Compounds Using In Silico Modeling and Machine Learning
