Review Article
Volume 10 Issue 9 - 2022
Basics of Machine Learning in Drug Discovery: A Bird’s Eye Perspective
Rekha Choudhary1, Pranali Yelchatwar1, Vinayak Walhekar1, Ashwini Patil1, Dileep Kumar1, Amol Muthal2, Macha Baswaraju3, Garige Anil kumar3, Chandrakant Bagul4* and Ravindra Kulkarni1*

1Department of Pharmaceutical Chemistry, BVDU’S Poona College of Pharmacy, Erandwane Pune, Maharashtra, India.

2Department of Pharmacology, BVDU’S Poona College of Pharmacy, Erandwane Pune, Maharashtra, India

3Department of Pharmaceutical Chemistry, Jayamukhi Institute of Pharmaceutical Sciences, Narsampet, Warangal, Telangana, India

4Department of Pharmaceutical Chemistry, Amrita School of Pharmacy Amrita Vishwa Vidyapeetham, AIMS Health Sciences Campus, Kochi

*Corresponding Author: Chandrakant Bagul, Department of Pharmaceutical Chemistry, Amrita School of Pharmacy Amrita Vishwa Vidyapeetham, AIMS Health Sciences Campus, Kochi.
Received: May 02, 2022; Published: August 31, 2022


Artificial Intelligence is an algorithm based computational approach to find solution from existing data. It has wider applications in different areas like medicine, agriculture, etc., and pharmaceutical field is not out of its ambit. Machine learning (ML) that is a subset of artificial intelligence, plays a crucial role in drug discovery and development by employing a massive quantum of structured and semi-structured data so that a ML model can create accurate outputs or provide predictions based on the data under analysis. It is a technical approach in which the machines are trained to process a significant amount of data. Two main categories of ML are supervised and unsupervised learning which are the platforms for the data processing. ML uses historical data which is responsible to generate algorithms for its working to produce the output. This can be accomplished in the ligand-based and structure-based approaches of drug design that helps to anticipate the hit and lead molecules for the drug discovery process.


Keywords: Artificial Intelligence; Machine Learning; Supervised Learning; Unsupervised Learning; Algorithms


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Citation: Ravindra Kulkarni., et al. “Basics of Machine Learning in Drug Discovery: A Bird’s Eye Perspective”. EC Pharmacology and Toxicology 10.9 (2022): 21-45.

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