Shelly Fan in Singularity Hub:
Tailoring cancer treatments is a science and an art. The same type of tumor can behave very differently from one person to the next, and a drug that works for one patient may fail in another. The uncertainty stacks up when multiple drugs enter the mix. Trial and error is often unavoidable. Meanwhile, cancers keep growing and compounding side effects can plague already beleaguered bodies.
Researchers have long sought to speed up the process of tailoring treatments to patients, and AI might lend a hand. This month, a Chinese team developed an AI-based virtual cell for triple-negative breast cancer—a challenging form of the disease that often evades standard treatments—to predict how individuals will respond to different drugs. Rather than reconstructing every detail of a cell’s inner workings, the virtual cell focused on just proteins. Trained on a massive, curated dataset tracking protein changes before and after drug treatments, the model outperformed existing drug-tailoring approaches and discovered new combinations that could work even better.
More here.
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