Advances in Neural Networks for Pharmaceutical Applications

Abstract

Artificial neural networks (ANNs) are rapidly changing the landscape of the pharmaceutical industry. Their unique capabilities, including collective computing, adaptive learning, and fault tolerance, make them ideal for tackling complex challenges in drug discovery, analysis, and personalized medicine. This article summarizes the latest research progress in ANNs for pharmacy, highlighting breakthroughs in areas like QSAR modeling for drug design, pharmacokinetic prediction, and optimization of pharmaceutical preparations. With their immense potential to accelerate drug development, improve drug efficacy, and personalize healthcare, ANNs are poised to revolutionize the future of pharmaceuticals.