Exploring the Potential of Computer Simulation Models in Drug Testing and Biomedical Research: A Systematic Review

Rahul Mittal^1*Alan Ho²Harini Adivikolanu²Muskaan Sawhney²Joana R N Lemos¹Mannat Mittal²Khemraj Hirani¹

• ¹Division of Endocrinology, Diabetes and Metabolism, Department of Medicine, Leonard M. Miller School of Medicine, University of Miami, Miami, United States
• ²University of Miami Miller School of Medicine, Miami, United States

The growing limitations of animal models in drug testing and biomedical research, including ethical concerns, high costs, and poor translational relevance to human biology, have catalyzed interest in computational simulation models as transformative alternatives. These innovative models, encompassing in silico approaches, pharmacokinetic/pharmacodynamic frameworks, molecular simulations, and organ-on-chip technologies, offer unparalleled precision in replicating human physiological and pathological processes. By bridging critical gaps in predictive accuracy and translational relevance, computational simulation models present an opportunity to streamline drug development, reduce late-stage failures, and enhance personalized medicine. Moreover, their ability to reduce reliance on animal models aligns with global ethical initiatives advocating for humane and sustainable research practices. Despite their transformative potential, challenges such as standardization, scalability, and regulatory integration must be addressed. This systematic review highlights the significance of simulation models in reshaping biomedical research, suggesting their capacity to advance human health outcomes while addressing the ethical and scientific shortcomings of traditional methodologies.