Artificial Intelligence and Machine Learning in Drug Design and Development

13AI Models for Biopharmaceutical Property Prediction

Bancha Yingngam

Department of Pharmaceutical Chemistry and Technology, Faculty of Pharmaceutical Sciences, Ubon Ratchathani University, Ubon Ratchathani, Thailand

Abstract

Accurate and reliable prediction of drug properties is crucial in the biopharmaceutical industry because they directly impact drug efficacy and safety. However, the traditional experimental methods used to determine these properties are often expensive, time-consuming, and impractical, hindering efficient drug discovery and development. In recent years, machine learning (ML) and artificial intelligence (AI) techniques have gained popularity for predicting biopharmaceutical properties. This chapter aims to provide a comprehensive overview of AI models in biopharmaceutical property prediction. It covers key areas such as the critical importance of accurate prediction, traditional challenges, introduction to AI models, their underlying principles, advantages, challenges, recent advances, and future directions. The chapter consolidates the latest advancements in AI models tailored for predicting biopharmaceutical properties and explores alternative approaches, integrates AI techniques, and offers a focused and comprehensive overview. It discusses recent advances in ML and AI models, including deep learning and ensemble models, and their potential applications in drug discovery and development. Additionally, it addresses future directions and challenges in ...