Elixir for Medicine

Authors

  • Thiyagarajan. B  Department of Computer science and Engineering, Sri Manakula Vinayagar Engineering College, Pondicherry, Tamil Nadu, India
  • Jamuna. I  Department of Computer science and Engineering, Sri Manakula Vinayagar Engineering College, Pondicherry, Tamil Nadu, India
  • Keerthana. G  Department of Computer science and Engineering, Sri Manakula Vinayagar Engineering College, Pondicherry, Tamil Nadu, India
  • Krithika. B  Department of Computer science and Engineering, Sri Manakula Vinayagar Engineering College, Pondicherry, Tamil Nadu, India

DOI:

https://doi.org//10.32628/CSEIT1952213

Keywords:

Artificial Intelligence, Machine Learning, Deep Learning, Generative Adversarial Networks.

Abstract

The Drug formulation is a proactive part of research in the existing Biomedical Industry is highly money consuming and the general pipeline involved in terms of time is huge that it takes around 10-12 years. People generally get typically skeptical as the time progresses. This is an essential need that needs to be addressed. The process of getting a drug from Initial Discovery to market can take years or decades. Experiments, clinical studies, and clinical trials are necessary.90% of all clinical trials in humans fail even after the molecule compounds have been successfully tested in animals.

References

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IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology

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Published

2019-04-30

Issue

Volume 5, Issue 2, March-April-2019

Section

Research Articles

License

Copyright (c) IJSRCSEIT

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
Thiyagarajan. B, Jamuna. I, Keerthana. G, Krithika. B, " Elixir for Medicine, IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 5, Issue 2, pp.911-914, March-April-2019. Available at doi : https://doi.org/10.32628/CSEIT1952213