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There are a lot of modalities being integrated, things like spatial/temporal, ADT/protein, etc. Integrating all of this data is a computational challenge, and of course there are lots of methods for analyzing it that vary in computational demands. It's not simulation, but still a lot of processing.

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So you're taking all wet bench data and analyzing or integrating it rather than modeling? That's interesting!

Are there any possibilities that you see from your experience in using modeling or other in silico methods to reduce time in the lab, find new leads in drug development, or otherwise enhance research capabilities?

Yes, essentially, though you may create models of interactions etc., but the main idea is to extract information from various aspects of the cell.

As far as in silico, I think absolutely there are probably opportunities here. Generative models might be useful for some type of counterfactual (automated) reasoning with respect to disease course/treatment. I think we're in the relatively early days of collecting high resolution cellular data, so I think in silico approaches like this will be more and more relevant.

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