GOOGLE OPEN SOURCE ANTICANCER AI MODEL: SIMULATION OF 40000 DRUGS AND LOCKING IN POTENTIAL ANTICANCER DRUGS

The news of October 17thGoogleOn October 15, the Institute published a book announcing that it will work with Yale University to jointly publish a Cell2Sentence-Scale 27B model based on Gemma's short C2S-ScaleThe analysis of single cells helped to identify new potential cancer treatment options。

GOOGLE OPEN SOURCE ANTICANCER AI MODEL: SIMULATION OF 40000 DRUGS AND LOCKING IN POTENTIAL ANTICANCER DRUGS

1AI cites Boven as one of the major challenges in the case of cancer immunisation therapy is the “invisibility” of many tumors to the immune system, known as “cold” tumours. A key strategy is to force tumour cells to expose immuno-trigger signals by a process called antigen transmission, thus transforming them into “hot” tumours that can be attacked by the immune system。

Based on the Gemma series of Google Open Source, the research team built the C2S-Scale model with 27 billion parameters, giving it a difficult task: to find a “conditional amplifier” drug. The drug can only enhance the immune signal in a given “immuno-positive” environment, which, although low in interferant (a key immuno-sign protein) level, is not sufficient to induce a single antigen submission。

To achieve this goal, the research team designed a two-dimensional virtual screening process. They first entered two types of data into the model: a true patient sample (immuno-positive) containing the full tumour interactions with immunization, and an isolated cell system (immuno-immuno-sexual) data。

The model then simulated the effects of more than 4000 drugs in both situations and was asked to predict which drugs could enhance antigen transmission only in the first scenario. The model ' s predictions are very clear, and it has been found that the hormone CK2 inhibitor silmitasertib (CX-4945) produces significant situational effects。

THIS NEW AI-GENERATED HYPOTHESIS WAS THEN BROUGHT TO THE LAB FOR VALIDATION. THE RESULTS OF TESTING ON HUMAN NEUROENDOCRINE CELLS, WHICH WERE NEVER ENCOUNTERED BY RESEARCHERS DURING MODEL TRAINING, CONFIRMED THE MODEL ' S PREDICTIONS WITH ALARMING RESULTS。

The separate use of silmitasertib or low-dose interferant has had little effect, but when the two were used together, there was a synergy of antigen transmission levels in the cells, resulting in a significant increase of about 50%, which means that the tumor will be more easily identified and attacked by the immune system。

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