Apart from operating productively in various other fields, artificial intelligence has been by the pharmaceutical companies. The pharmaceutical companies are putting AI to good use for the sake of developing new medicines. The MIT researchers have played a lead role in the development of the machine learning models through artificial intelligence. The machine learning model can put forward the new molecules which helps in fighting various diseases. Thus, AI is an effective way to drug development.
The machine learning model has found a new way to fight against the diseases speedily which the humans might take prolonged time to tackle. However, there is a major drawback within the model. The machine learning model frequently suggests those molecular structures which are difficult to prepare in the laboratory.
The researchers from the Massachusetts institute of technology has put major constraints in the machine learning model. The ML model can only suggests those molecular structures which can be prepared and tested by the chemist in the laboratory. Likewise, it only suggests those molecular structures whose materials are readily available and the chemists can test them in the laboratories according to the rules and regulations.
However, the technique the model opts is quite different from the other models. The model takes less than one second to propose a molecular structure which is flexible.
Making of Molecular Structures
To make the molecular structure, it is necessary to have the building blocks. The model provides with the suitable building blocks known as chemicals. Thus the chemists mix these molecular with the help of their hands to create a chemical reaction. The chemists add the molecule step by step. Likewise, with the advancement within the steps, the chemical reaction becomes complex.
According to Gao, it is important to design an action which successfully leads to the final output. It is the only way to ensure quality within the molecular structure.
Thus, new research from the Massachusetts institute of technology provides a machine learning model which decreases the time required to tackle the diseases. Apart from this, it provides the synthetic molecular structures which are quite flexible to be made in accordance with the existing circumstances.