System Theoretic Methods in Drug Discovery and Vaccine Formulation: Review and Perspectives

The methods utilized in drug discovery pipeline routinely combines machine learning and deep learning algorithms to enhance the outputs. The generation of drug target, through virtual screening and computational analysis of databases used for target discovery, has increased the reliability of the machine learning and deep learning incorporated techniques. Recent technological advances in human immunology have provided improved tools that allow a better understanding of the biological and molecular mechanisms leading to a protective human immune response to pathogens, inspiring new strategies for vaccine design. Immunoinformatics approaches are more beneficial, and thus the demand for modern technologies such as reverse vaccinology, structural vaccinology, and system approaches, are utilized in developing potential vaccine candidates. Here, we summarize the system theoretic methods which provide insights into developed approaches and their applications in rational drug discovery and vaccine formulations. The approaches ranged in review yields to accurate predictions and insights.