Computer Modeling and Simulation is an effective approach to reducing animal testing. This technology uses virtual models of biological systems to predict a drug’s mechanism of action, toxicity, and efficacy. It allows researchers to screen large numbers of compounds and conduct safety assessments early in the drug development process, significantly reducing the need for animal experiments. With advances in artificial intelligence (AI) and machine learning, the accuracy and reliability of computer models have improved, enabling more precise predictions of human responses to new drugs.

A specific example involves a pharmaceutical company that used computer modeling to evaluate the cardiotoxicity of drug candidates. By simulating the electrophysiological properties of human heart cells, they could predict adverse cardiac effects of various compounds. This approach enabled the early identification of high-risk drugs, thereby avoiding unnecessary animal testing. It also reduced the cost and time involved in drug development. Furthermore, the data obtained through computer simulations were used to design more effective clinical trials, increasing the likelihood of success in the later stages of drug development.