Bioinformatics Tools for Pharmaceutical Drug Product Development

2Artificial Intelligence and Machine Learning-Based New Drug Discovery Process with Molecular Modelling

Isha Rani¹, Kavita Munjal², Rajeev K. Singla^3,4 and Rupesh K. Gautam⁵*

¹Spurthy College of Pharmacy, Marasur Gate, Bengaluru, Karnataka, India

²MM College of Pharmacy, MM (Deemed to be) University-Mullana, Ambala, Haryana, India

³Institutes for Systems Genetics, Frontiers Science Center for Disease-Related Molecular Network, West China Hospital, Sichuan University, Chengdu, China

⁴iGlobal Research and Publishing Foundation, New Delhi, India

⁵Department of Pharmacology, Indore Institute of Pharmacy, IIST Campus, Rau, Indore (M.P.), India

Abstract

Drug development is a time-consuming, expensive and extremely risky procedure. Up to 90% of drug concepts are discarded due to challenges such as safety, efficacy and toxicity resulting in significant losses for the investor. The use of artificial intelligence (AI), namely machine learning and deep learning algorithms, to improve the drug discovery process is one technique that has arisen in recent years. AI has been effectively used in drug discovery and design. This chapter includes these machine learning approaches in depth, as well as their applications in medicinal chemistry. The current state-of-the-art of AI supported pharmaceutical discovery is discussed, including applications in structure and ligand-based virtual screening, de novo drug design, drug repurposing, and factors related, after introducing the basic principles, ...