Researchers Use AI to Build Virtual Human Cells

A group of researchers from Stanford University, Genentech, and the Chan-Zuckerberg Initiative is exploring the possibility of creating the first virtual human cell with the help of artificial intelligence (AI). This initiative aims to replicate the behaviors of human biomolecules, cells, and eventually, tissues and organs, offering new ways to study biology and disease.

According to Emma Lundberg, a professor of bioengineering at Stanford, developing a model for human cells is a major milestone in biology. AI provides the capability to go beyond existing assumptions by learning directly from data, allowing scientists to explore complex biological systems. Lundberg collaborates with Stephen Quake, Jure Leskovec, Theofanis Karaletsos, and Aviv Regev on this groundbreaking project.

The goal of this virtual cell model is to better understand how cells function and to uncover the root causes of diseases that disrupt cellular activity. Additionally, it would allow for virtual experiments on a computer instead of using living cells, speeding up the development of new therapies and possible cures for various diseases.

A significant advantage of the virtual cell would be its ability to simulate the effects of mutations and viruses without the need for animal or human testing. This could greatly impact fields such as cancer research, where scientists could model how cancer develops in cells. Eventually, doctors could use digital twins of patients to test treatments, advancing personalized medicine.

To be successful, the virtual cell must accomplish three main objectives: creating accurate representations of cells across species, predicting how cells behave, and enabling computer-based experiments to guide scientific discovery. This approach would cut down the time and cost of research compared to current methods.

Creating the virtual cell will require extensive collaboration between experts in genetics, proteomics, and medical imaging, along with the use of vast biological data sets. The researchers note that the project will rely on massive amounts of data, similar to the vast collection of DNA sequencing in the Short Read Archive, and that cooperation across industries and countries will be necessary.

Though the creation of this AI-powered virtual cell will take years, the researchers believe that the advancements in AI and the rapid growth of biological data make now the ideal time to begin. They stress that any models created should be shared openly with the global scientific community to maximize their impact.