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Scientists are developing increasingly sophisticated "virtual cells" – artificial intelligence models designed to simulate how living cells behave across multiple biological scales. Rather than focusing on a single type of data, the latest generation of models combines information on genes, proteins, cell structure and tissue organisation to better predict how cells respond to disease, medicines and environmental changes.
Researchers say this multiscale approach could provide a much more realistic picture of biology. By integrating different types of biological data, virtual cells may help scientists uncover how complex diseases develop, identify new drug targets and predict the effects of potential treatments before they are tested in the laboratory. Companies and research organisations including GenBio AI, the Arc Institute, Chan Zuckerberg Biohub, Xaira Therapeutics and Ginkgo Bioworks are among those working to advance the technology.
Although the technology is still in its early stages, experts believe virtual cells could dramatically speed up biomedical research by allowing many experiments to be carried out in silico before moving to animal studies or clinical trials. However, researchers caution that today's models remain limited and cannot yet fully capture the dynamic complexity of living cells, meaning laboratory experiments will continue to play a crucial role.
If the field continues to advance, AI-powered virtual cells could become an important tool for precision medicine, helping scientists understand disease mechanisms, develop personalised therapies and accelerate the discovery of new medicines.
