Google's Gemma AI model helps discover new potential cancer therapy pathway
Here is the research paper: https://www.biorxiv.org/content/10.1101/2025.04.14.648850v3
Cell2Sentence-Scale, or C2S-Scale, it’s a 27-billion parameter AI model built on Google's Gemma family that was designed to understand the language of individual cells.
The big problem in cancer treatment is that many tumors are 'cold,' meaning they are invisible to your immune system, so your body cannot fight them.
Scientists have been trying for years to figure out how to make these tumors 'hot' so the immune system can see and attack them.
Google gave C2S-Scale a nearly impossible task: find a drug that boosts the immune signal only when a specific immune protein called interferon is already present, but at levels too low to work on its own.
This required conditional reasoning that smaller AI models could not do.
The AI simulated over 4,000 drugs across two different immune contexts, real patient tumours vs lab grown tumors, and it identified a drug called silmitasertib, predicting it would amplify antigen presentation, making tumors visible, but only in the right immune environment.
This was a completely novel hypothesis; no prior research had ever linked silmitasertib to enhancing antigen presentation.
The AI was not repeating known facts; it was generating a brand-new idea.
But a prediction means nothing without proof, so researchers took this hypothesis to the lab and tested it on human neuroendocrine cells that the AI had never seen during training.
These were the results... The drug alone did nothing, low-dose interferon alone had a modest effect, but combining interferon with silmitasertib produced a 50% increase in antigen presentation, exactly as the AI predicted.
This is not just incremental progress; this is AI generating entirely new biological knowledge and having it confirmed in living cells.
Teams at Yale are now exploring this mechanism further and testing additional AI-generated predictions.
If this holds up in clinical trials, we could be looking at a whole new class of combination therapies for cancer.
Here is Google's blog about this research to learn more: https://blog.google/technology/ai/google-gemma-ai-cancer-therapy-discovery/
Cell2Sentence-Scale, or C2S-Scale, it’s a 27-billion parameter AI model built on Google's Gemma family that was designed to understand the language of individual cells.
The big problem in cancer treatment is that many tumors are 'cold,' meaning they are invisible to your immune system, so your body cannot fight them.
Scientists have been trying for years to figure out how to make these tumors 'hot' so the immune system can see and attack them.
Google gave C2S-Scale a nearly impossible task: find a drug that boosts the immune signal only when a specific immune protein called interferon is already present, but at levels too low to work on its own.
This required conditional reasoning that smaller AI models could not do.
The AI simulated over 4,000 drugs across two different immune contexts, real patient tumours vs lab grown tumors, and it identified a drug called silmitasertib, predicting it would amplify antigen presentation, making tumors visible, but only in the right immune environment.
This was a completely novel hypothesis; no prior research had ever linked silmitasertib to enhancing antigen presentation.
The AI was not repeating known facts; it was generating a brand-new idea.
But a prediction means nothing without proof, so researchers took this hypothesis to the lab and tested it on human neuroendocrine cells that the AI had never seen during training.
These were the results... The drug alone did nothing, low-dose interferon alone had a modest effect, but combining interferon with silmitasertib produced a 50% increase in antigen presentation, exactly as the AI predicted.
This is not just incremental progress; this is AI generating entirely new biological knowledge and having it confirmed in living cells.
Teams at Yale are now exploring this mechanism further and testing additional AI-generated predictions.
If this holds up in clinical trials, we could be looking at a whole new class of combination therapies for cancer.
Here is Google's blog about this research to learn more: https://blog.google/technology/ai/google-gemma-ai-cancer-therapy-discovery/
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By Leon Petrou
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