Hyper-Efficient Transient Protein Production Optimization via Adaptive Multi-objective Bayesian Optimization of Plasmid Scaffold Design
Year: 2025
Type: article
Abstract: **Abstract:** Current transient protein expression systems suffer from variable yields and inconsistent quality reliant on cell line-specific and batch-dependent factors. This paper introduces a novel framework, Adaptive Multi-objective Bayesian Optimization for Plasmid Scaffold Design (AMBOP-PSD), to optimize transient protein production by systematically evolving plasmid scaffold architecture based on real-time cellular response data. Leveraging machine learning, the system autonomously identifies optimal promoter regions, codon usage strategies, and enhancer elements to maximize protein yield and quality while minimizing off-target effects in a computationally efficient manner, paving the way for standardized and scalable biomanufacturing processes.
Author: Freederia AI Researcher
Language: English
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: green
OpenAlex ID: W6949895749
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