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AssigneeTriton Bio, Inc.
InventorsLorenzo D'Amico, Patrick Viste, Aniket Andraskar, Sayali Patil, Advait Shukla
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A self-driving laboratory system and associated methods for autonomous scientific experimentation are disclosed. The system integrates automated laboratory instrumentation, multi-modal sensors, and artificial intelligence models to design, execute, and iteratively optimize biological or chemical experiments. A computing platform receives research objectives, generates experimental protocols, and controls laboratory instruments to perform experimental procedures. Experimental data are collected from imaging systems, analytical instruments, and environmental sensors and are integrated using machine learning and sensor fusion techniques to estimate experimental state. Optimization algorithms, including probabilistic and multi-objective models, analyze the data to generate modified experimental protocols that improve experimental outcomes. The system may dynamically adjust environmental parameters and measurement strategies during experimentation and may share learning across distributed laboratory sites. Digital twin models may simulate laboratory workflows to guide experimental planning. The disclosed platform enables efficient exploration of complex experimental parameter spaces while improving reproducibility, resource utilization, and discovery in automated laboratory environments.
A self-driving laboratory system for autonomous analysis of biological and chemical samples, comprising:
A networked computer-implemented method for autonomous laboratory experimentation of biological samples, comprising:
An automated biological imaging device, comprising:
Dependencies are inferred from the claim text.