Biosimulation is a scientific approach that uses computer-based models to simulate biological processes and predict how drugs interact with the human body. By combining data from biology, chemistry, mathematics, and pharmacology, biosimulation helps researchers understand disease mechanisms, optimize drug dosing, and predict treatment outcomes before clinical trials begin. This technology significantly reduces the time, cost, and risk associated with traditional trial-and-error drug development.
In pharmaceutical research, biosimulation supports decision-making across all stages—from early discovery to post-marketing surveillance. For example, it can simulate how a drug is absorbed, distributed, metabolized, and excreted, allowing scientists to identify potential safety issues early. Regulatory agencies increasingly recognize biosimulation as a valuable tool, especially for rare diseases where patient populations are limited.
Beyond drug development, biosimulation is also used in personalized medicine. By incorporating patient-specific data such as genetics or organ function, simulations can help tailor therapies to individual needs. As artificial intelligence and machine learning continue to advance, biosimulation models are becoming more accurate and predictive, making them a cornerstone of modern biomedical research and precision healthcare.