ArticleBiotechnology and bioengineering2026
Mathematical Modeling of Amoxicillin Synthesis in Batch and Semi-Batch Reactor: Application of Bayesian Statistics and Genetic Algorithm.
Article in Biotechnology and bioengineering, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Semipilot Scale Synthesis of Zeolite A from Kaolin Filler: Process Optimization with Boiler Steam, Mathematical Modeling, and CuACS omega · 2026Article
- Mathematical Modeling of Amoxicillin Synthesis in Batch and Semi-Batch Reactor: Application of Bayesian Statistics and Genetic Algorithm.Biotechnology and bioengineering · 2026Article
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This study investigates the enzymatic synthesis of amoxicillin, focusing on its kinetic properties and their influence on antibiotic production in a batch-operated enzymatic reactor. The reaction is catalyzed by penicillin G acylase (PGA, E.C.3.5.1.11), which is immobilized on glyoxyl-agarose. The reaction involves the p-hydroxyphenylglycyne methyl ester and 6-aminopenicillanic acid (6-APA) for amoxicillin formation. Under kinetic control, parallel hydrolytic pathways lead to product loss. Two kinetic models were evaluated: one based on Michaelis-Menten kinetics and another incorporating reaction and equilibrium constants for the process steps. Parameter estimation for the models was performed at different concentrations using two mathematical approaches: the Markov chain Monte Carlo (MCMC) method, rooted in Bayesian statistics and characterized as nondeterministic, and genetic algorithm, an evolutionary computation method incorporating crossover, mutation, and selection operators. The relative root mean squared error (rRMSE) was selected as the metric for evaluating the predictive performance of the models. MCMC presented the best results for low ester concentrations, with rRMSE values ranging from 1.48% to 6.10% for the Michaelis-Menten-based model. The mathematical model was validated using data from an enzymatic reactor operating in semi-batch mode, demonstrating a satisfactory capacity to predict the system's dynamic behavior under this operational condition.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.