Vivodyne, a biotech startup, says its HIVE modular robotic labs can grow 20 human tissue types and autonomously dose and monitor them to produce causal biological data that current AI drug‑discovery models lack. The company argues that existing AI models rely on animal testing and static snapshots of single cells or proteins rather than living tissue.

According to CEO Andrei Georgescu, the lack of human testing means AI models will only be able to cure cancer in mice, a claim he says is becoming cliché.

AI‑designed drugs have entered human trials, with one reaching Phase III, but the industry reports that 90% of drugs that succeed in animal testing fail to obtain regulatory approval in humans.

Vivodyne says its tissues show high predictive accuracy: liver cells match human toxicity tests in 94% of cases, airway tissue behaves like real human tissue in 96% of trials, and bone marrow predicts response to 20 chemotherapy drugs with 100% concordance.

The company, which has raised just under $80 million, opened a facility it calls the world’s largest human data center near San Francisco, reporting twice the throughput of all U.S. animal trials.

Georgescu says the labs are intended to generate the causal data needed to train AI models on human biology, a capability he says is essential for future combination therapies that target multiple pathways. A recent Nature Methods study found that training generative AI on static cellular snapshots does not capture how cell states arise from one another.