Computational modeling - a revolutionary tool in clinical research

Abstract

Computational modeling forms the virtual representation of real-world systems, phenomenon or process. Manipulating computer-based mathematical, graphical or algorithmic models of actual-world situations, products or surroundings adds richness to multiple fields. Disease predictive models, weather forecasting models, earthquake or car crash simulations are some examples of real life uses of computational modeling. Therefore, this method is utilized to gain a scientific insight into some real or hypothetical scenarios, monitor the impact of change in the scenarios, and facilitate decision-making. The article describes several kinds of computational models that highlight the pragmatic applications of computational modeling in medicine and biology. The research compares human-built model and AI model illustrating different problem-solving approaches. Yet, in spite of its benefits, there are a number of drawbacks. For example, the expense of operating a series of various simulations could be prohibitive or time could be required to review the results. Moreover, individuals' responses to the model may not be realistic or valid. Finally, this paper considers computational modeling as a revolutionary technology in biomedical engineering that enables to design a safe and effective drug.