Using a GPT-5-driven autonomous lab to optimize the cost and titer of cell-free protein synthesis

Abstract excerpt

We used an autonomous lab, comprising a large language model (LLM) and a fully automated cloud laboratory, to optimize the cost efficiency of cell-free protein synthesis (CFPS). By conducting iterative optimization, the LLM-driven autonomous lab was able to achieve a 40% reduction in the specific cost ($/g protein) of CFPS relative to the state of the art (SOTA). This cost reduction was accompanied by a 27% increa...

Topics

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• Monoclonal and Polyclonal Antibodies Research
• Protein purification and stability
• Viral Infectious Diseases and Gene Expression in Insects

Identifiers and source

Literature Corpus work

07109788-9751-54ec-b669-dafb046c4019

DOI

10.64898/2026.02.05.703998