Google Research shows agents for automated biology labs: across three aptamer-design cycles, 33.5% and 42.1% of candidates were confirmed
Prepared by Sintelligent with the help of SI. Published in SI: . Updated: .
SI agents are closer to working independently in a lab, but the figures so far come from the company itself.
According to Google Research, the team presented three projects on wet labs: a VERID digital twin built on PyLabRobot that tracks lab state in 3D, runs virtual dry runs and checks equipment safety; aptamer design for myoglobin and α-thrombin, where over three closed-loop cycles (7-10 days each) the share of confirmed candidates was 33.5% and 42.1%; and an 8.6x speedup in structure prediction when designing protein binders, with single-digit nanomolar affinity to the protein FAP. The company describes safeguards: simulation before execution, biosecurity screening and human oversight of generated sequences.
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