I’ve been intrigued with this technology for some time from the standpoint of cell biology. When a healthy cell undergoes cancer transformation or metastasis, we are looking at a phase shift type of change where massive complexity comes into play. Cellular digital twins that incorporate the vast amount of data from technologies such as RNA-seq, multiphoton imaging, and proteomics can now be quite high-fidelity. Simulating such disease-related phenotypic changes may be incredibly useful for providing insights into the cell as a complex adaptive system, while also generating hypotheses for future experiments.
Beyond digital twins as they currently exist is the idea of AI world models, where the worlds are individual cells or a cell network. In that case, I could imagine a cell biologist using natural language to create an experimental initial condition and then simulate the time evolution of the world as an in silico experiment — how cool!
Although, as with all digital twins, we need to experimentally test in the real world. Trust, but verify.
Discoverers and Discoveries 