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Embodied Artificial Intelligence Must Learn Laboratory Constraints before It Can Autonomously Conduct Pharmaceutical Experiments

Year: 2025

Type: article

Abstract: Artificial intelligence is increasingly connected to automated synthesis, analytical instrumentation, experiment planning, and closed-loop scientific discovery. However, computational competence does not by itself establish the capacity to conduct pharmaceutical experiments. Laboratory work is embodied: every action is conditioned by equipment availability, material identity, container state, spatial reachability, procedural dependencies, timing requirements, contamination controls, hazard bound

Source: Pharmacophore

DOI: 10.51847/ajmb8aq7zf

Authors: Marco De Luca, Giulia Ferraro, Antonio Russo, Elena Rossi

Institution: University of Naples Federico II

Topic: Machine Learning in Materials Science

Subfield: Materials Chemistry

Field: Materials Science

Domain: Physical Sciences

Open Access status: hybrid

OpenAlex ID: W7202077589

FWCI:

Cites: 30

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