  The need for analysis of toxicity in new drug candidates and the requirement
of doing it fast have asked the consideration of scientists towards the use of
artificial intelligence tools to examine toxicity levels and to develop models
to a degree where they can be used commercially to measure toxicity levels
efficiently in upcoming drugs. Artificial Intelligence based models can be used
to predict the toxic nature of a chemical using Quantitative Structure Activity
Relationship techniques. Convolutional Neural Network models have demonstrated
great outcomes in predicting the qualitative analysis of chemicals in order to
determine the toxicity. This paper goes for the study of Simplified Molecular
Input Line-Entry System (SMILES) as a parameter to develop Long short term
memory (LSTM) based models in order to examine the toxicity of a molecule and
the degree to which the need can be fulfilled for practical use alongside its
future outlooks for the purpose of real world applications.
