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The motive of this paper is to take the attention of the reader to how the infrastructure of pharmaceutical companies works on new technologies. How the modern world tackled the failure of the formation of vaccines in the phase of covid–19 viruses. For the underwriting of the review, the author team did a literary survey and explored ten research papers concerning points. This literary survey provides deep knowledge about drug discovery using various methods, such as machine learning and Bio-Activity detection.
The author and his team looked at how the manufacturing process for generating medications and preventative chemicals takes longer for each ailment. The researchers went on to explain that in order to successfully complete the medication development phase, target identification must come first. In addition to concentrating on some target variables like proteins, possible drugs (Bio-Activity), and DNA mutations, this phase must concentrate on the key chemicals (chemical compounds). For both machines and people, creating pharmaceuticals is not an easy task. creating a chemical compound combination and creating a potent and effective medicine.
The author team has described the procedure in which they have addressed the techniques utilized for the review. This study utilized the ML and AI-based basic examination of the data collected from the CHEMBL Database. The author and his team take the relevant data which is useful for their analysis and create a dataset and use it in their model.
Ethical Committee and Funding
The experiments don't include any human-related experiments and so no ethical constraints have been violated. Though the subjects performing the study were humans and air quality directly affects them but the study doesn’t violate any health-related measures. The Project is not funded by any agency.
1. Introduction
In the current scenario, India's health department faces a double challenge. The first one is that they have to wrestle with diseases such as diarrhea, and lower respiratory infections(Asthma, Pneumonia, etc.) and another one is they have to tackle non-communicable conditions like cancer, and diabetes. There is no permanent medicine and treatment for these diseases available. For any disease, medicine takes a long time to manufacture and takes enough resources. Using a machine learning Author team builds a model which helps to manufacture or test the Bioactivity of drugs easily.