(349b) Dynamic Modelling, Simulation and Optimisation of Batch Enzymatic Amoxicillin Production | AIChE

(349b) Dynamic Modelling, Simulation and Optimisation of Batch Enzymatic Amoxicillin Production


Diab, S. - Presenter, University of Edinburgh
Rodman, A. D., University of Edinburgh
Cuthbertson, A. B., University of Edinburgh
Gerogiorgis, D., University of Edinburgh

Antibiotics are societally essential pharmaceutical products, making previously untreatable illnesses such as pneumonia and tuberculosis curable, thus revolutionising modern medicine.1 Access to essential medicines in low- to middle-income countries as well as antibiotic shortages in developed countries remain an important issue.2,3 The complex molecular structures of antibiotics imply that they are generally expensive due to the multistep, materially-intensive syntheses required to make such molecules. Designing cost-effective antibiotic manufacturing routes is imperative.

The family of β-lactam antibiotics are some of the most important pharmaceutical products, with cephalosporins and semi-synthetic penicillins corresponding to approximately 65% of global production of antibiotics.4 Amoxicillin is one β-lactam antibiotic used to treat respiratory and urinary tract infections and meningitis and listed as a World Health Organisation (WHO) essential medicine. The batch enzymatic synthesis of amoxicillin involves a kinetically controlled network of series-parallel reactions of desired amoxicillin synthesis and undesired hydrolysis of both amoxicillin and the substrate.5 The demonstrated enzymatic synthesis of amoxicillin and kinetic model in the literature paves allows elucidation of optimal design and operating parameters via modelling and optimisation.6

While studies into modelling and simulation of synthesis and crystallisation of β-lactam antibiotics have been recently demonstrated,7 dynamic modelling and optimisation of the described batch enzymatic synthesis of amoxicillin has yet to be implemented. Specifically, establishing optimal temperature control profiles for the batch reactor to meet a specific production objective for amoxicillin synthesis will allow for elucidation of optimal heating policies and possible reduction of total batch run times.8

This work implements dynamic modelling and optimisation of the batch enzymatic synthesis of amoxicillin.5 First, the enzymatic synthesis pathway is presented with the kinetic model. Temperature dependence of kinetic parameters is introduced by regression of Arrhenius constants from experimental data, followed by isothermal simulation for design space investigation. A constrained dynamic optimisation problem is then described to minimise the consumption of key substrate subject to different constraints on product amoxicillin concentrations, comparing resulting optimal temperature profiles.


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(6) Diab, S.; McQuade, D.T.; Gupton, B.F.; Gerogiorgis, D.I. Process design and optimisation for the continuous manufacturing of nevirapine, an active pharmaceutical ingredient for H.I.V. treatment. Org. Process Res. Dev. 2019, 23(3), 320–333.

(7) McDonald, M.A.; Bommarius, A.S.; Rousseau, R.W.; Grover, M.A. Continuous reactive crystallization of β-lactam antibiotics catalyzed by penicillin G acylase. Part I: Model development. Comput. Chem. Eng. 2019, 123, 331–343.

(8) Rodman, A.D.; Gerogiorgis, D.I. An investigation of initialisation strategies for dynamic temperature optimisation in beer fermentation. Comput. Chem. Eng. 2019, 124, 43–61.