Biosimulation: How Does Biosimulation Improve Drug Development?

Biosimulation uses computational models to predict biological responses, drug interactions, and disease progression. It allows pharmaceutical companies to simulate clinical scenarios before conducting physical trials, reducing costs and development time.

These models analyze pharmacokinetics (PK), pharmacodynamics (PD), toxicity, dosing strategies, and patient variability. By predicting outcomes early, researchers can optimize drug formulations, identify safety risks, and reduce the likelihood of trial failures.

Biosimulation is also valuable in precision medicine—helping tailor treatments for specific patient populations based on genetics or disease characteristics. In combination with AI and machine learning, biosimulation supports real-time decision-making and enhances the accuracy of predictive models.

Its growing role in virtual clinical trials is transforming research efficiency, making drug development more precise and patient-centered.