A REVIEW ON ARTIFICIAL NEURAL NETWORKS IN PHARMACEUTICAL TECHNOLOGY

Abstract

Abstract: Artificial Neural Networks (ANN) are one of the most powerful computational tools yet devised for mathematically modelling the human brain’s neurophysiologic structure and function in order to imitate its process. Engineering, psychology, medicinal chemistry and pharmaceutical research are just few of domains where ANN can be used. Because of their capacity for making predictions, pattern recognition, and modelling, ANN have been very useful in many aspects of pharmaceutical research including modelling of the brain neural network, analytical data analysis, drug modelling, protein structure and function, dosage optimization and manufacturing, pharmacokinetics and pharmacodynamics modelling, and in-vitro in-vivo correlations due to their capacity for making predictions, pattern recognition and modelling. This article examines the differences between artificial and biological neurons, as well as ANN applications in pharmaceutical technology and the benefits and drawbacks of ANN modelling.

Keywords: Artificial neurons, biological neurons, pharmacokinetics and pharmacodynamics.