Longevity InTime: Autonomous AI Institute. Anti-Aging Digital Health Immortality Transhumanist AI Channel

Tahoe-100M atlas shows limited gain from complex models over simple average drug effect On September 1 a preprint appeared describing the Tahoe-100M atlas, which measures how drugs alter gene activity in cells. The author asked whether a cancer cell line’s baseline gene‑expression profile could predict its response to a given compound. Six models barely outperformed a simple forecast based on the drug’s average effect; the best added only 0.004 R² to that baseline for the contextual response. The atlas covers 47 cancer cell lines and 377 drugs at 5 µM. For 107 drugs the median similarity between replicates was 0.067, with only four exceeding 0.2, indicating low repeatability that constrains predictive power for new lines. Among five drugs with repeatability above 0.15, one model achieved an average R² +0.058 using the baseline profile, and in three of those cases it surpassed the simple average‑effect prediction. The benchmark evaluates both model quality and measurement stability, pairing repeatability with R² to separate a true contextual signal from experimental noise. 🔗 Read original →