Integrating Quantum Computing and Big Data Analytics for Accelerated Drug Discovery: A New Paradigm in Healthcare Innovation

The manipulation of atomic and molecular structures has been a topic of interest in recent years owing to the broad range of applications that its control entails. Researchers in areas such as macromolecular science are highly interested in protein folding problems, while direct drug discovery methods focus on strategies for designing ligands or modulators that target proteins of interest. In addition to targeting a specific protein, one of the principal objectives of work related to drug production is the modification of drugs in such a way that their performance profile is improved concerning that of other drugs. In this regard, the large amount of chemical data and their respective biological activities encoded in big data analytics will be a cornerstone in dealing with problems related to drug design. As a result of the many different data sources employed, strategies for the analysis of big data emerging from the world of research, especially the computer and health sciences are currently quite varied.