Speaker
Description
Drug design and discovery in the modern era necessitates rapid and co-optimization of multiple parameters. The quality and quantity of data for drug discovery should be more predictive and accurate for respective models. There should be a holistic approach to improvise the several parameters required in drug design and discovery. Drug design approaches have been categorized broadly as rational drug design, Computer aided drug design, structure-based drug design, ligand-based drug design, or quantitative structural activity relationship. Over the past 3 decades, many new technologies also emerged like property-based drug design, ligand based metrics, cheminformatics, molecular docking, artificial intelligence, and machine learning. Multiple parameter optimization may be done effectively if we have a proper strategy and holistic approach towards drug design. The approach could include probabilistic approach, rational approach, general principles, etc. but have their own limitations in various aspects. Some approaches may increase serendipity while others may have an inaccuracy in hypothesis. Therefore, the need of the hour is to combine and leverage different approaches in order to get the best result. Some examples of successful application of drug design approaches will be presented.