Dynamic Modelling and Optimisation of the Batch Enzymatic Synthesis of Amoxicillin

Abstract

Amoxicillin belongs to the β-lactam family of antibiotics, a class of highly consumed pharmaceutical products used for the treatment of respiratory and urinary tract infections, and is listed as a World Health Organisation (WHO) "Essential Medicine". The demonstrated batch enzymatic synthesis of amoxicillin is composed of a desired synthesis and two undesired hydrolysis reactions of the main substrate (6-aminopenicillanic acid (6-APA)) and amoxicillin. Dynamic simulation and optimisation can be used to establish optimal control policies to attain target product specification objectives for bioprocesses. This work performed dynamic modelling, simulation and optimisation of the batch enzymatic synthesis of amoxicillin. First, kinetic parameter regression at different operating temperatures was performed, followed by Arrhenius parameter estimation to allow for non-isothermal modelling of the reaction network. Dynamic simulations were implemented to understand the behaviour of the design space, followed by the formulation and solution of a dynamic non-isothermal optimisation problem subject to various product specification constraints. Optimal reactor temperature (control) and species concentration (state) trajectories are presented for batch enzymatic amoxicillin synthesis.Processes 2019, 7, 318 2 of 17 worldwide [11]. The demonstrated enzymatic synthesis of amoxicillin paves the way for the elucidation of optimal design and operating parameters via modelling and optimisation [12,13].Dynamic modelling and optimisation of batch processes have been substantially implemented in the literature for a variety of bioprocesses, including fermentations [14,15], antibiotic synthesis [16,17] and many other applications, illustrating the utility and versatility of such methods in bioprocess design. Enzymatic synthesis, crystallisation and reactive crystallisation studies for β-lactam antibiotics have been implemented in the literature [16][17][18][19]. A demonstrated batch enzymatic synthesis of amoxicillin paves the way for theoretical studies [20]. Dynamic modelling and optimisation of the batch enzymatic synthesis of amoxicillin has yet to be implemented. Moreover, introducing temperature dependence into the model may allow for the optimisation of batch reactor temperature profiles to meet a specific production objective, which, to the best of our knowledge, has not been previously implemented.Processes 2019, 7, x FOR PEER REVIEW 2 of 17

Parameter estimation and estimability analysis in pharmaceutical models with uncertain inputs

“…Kuu et al 7 Primary drying of 5% mannitol and 5% povidone Batch Y Sadikoglu and Liapis 8 Drying stages in bulk solution freeze-drying of pharmaceuticals in trays Batch Y Togkalidou et al 9 Cooling crystallization of a drug compound Batch Y Hermanto et al 10 Crystallization of L-glutamic acid polymorphs Batch N Velardi et al 11 Freeze-drying of bovine serum albumin, sucrose, and mannitol Batch Y Mortier et al 12 Drying behavior of single pharmaceutical granules Continuous Y Barrasso et al 13 Manufacturing of microcrystalline cellulose and tablets Continuous N Barrasso et al 14 Twin screw granulation process Continuous Y Selisteanu et al 15 Monoclonal antibody production using mammalian cell culture process Batch Y Gagnon et al 16 Drying of pharmaceutical particles containing calcium carbonate Batch N Garcıa-Munoz et al 17 Direct compression process for pharmaceutical tablets Continuous N Garg et al 18 Antisolvent crystallization for production of dexlansoprazole Batch Y Montes et al 19 Hoescht process for the synthesis of ibuprofen Batch Y Wang et al 20 Chinese hamster ovary cell metabolism to produce antibody Fed-batch N Cuthbertson et al 21 Enzymatic synthesis of amoxicillin Batch Y Lee et al 22 Kinetics, evaporation, and crystallization in the manufacturing of active pharmaceutical ingredients (API) Batch, continuous Y Maloney et al 23 Carfilzomib drug substance intermediate manufacturing Batch, continuous N Schenk et al 24 Multistage solid-liquid pharmaceutical process for urea compound synthesis Fed-batch N Diab et al 25 Flow synthesis kinetics for an anticancer API called Lomustine Continuous Y Grimard et al 26 Hot-melt extrusion process for the manufacturing of itraconazole tablets…”

Challenges and Opportunities on Nonlinear State Estimation of Chemical and Biochemical Processes

“…The development of state estimators for bioprocesses is a challenging task owing to the increased complexity of such systems, mainly associated with their highly nonlinear and time-varying dynamics. Consequently, the adequate description of the dynamics of the enzyme kinetics, or the cells' growth and production rates, usually involves nonlinear process models with a large number of parameters (that may be time-dependent or not) [105,106]. Moreover, single models are often valid only in a limited period of time or range of operating conditions [13,52,107,108].…”

Dynamic Optimization of a Fed-Batch Nosiheptide Reactor

“…Human antibiotic production, particularly β-lactams (whose broad applications and importance in global healthcare make them high priority), has received a lot of attention in process systems engineering in the past decade; a summary of pertinent literature examples on modeling and optimization of antibiotic production is provided in Table 1. Application of artificial neural networks (ANNs) to model complex reaction scheme for penicillin G acylase (PGA)-catalyzed synthesis [12] Inclusion of additional experimental data to improve ANN in reference [12] [13] Maximization of API formation vs. different operating conditions in either methanol/ethylene glycol as reaction solvents [14] Sensitivity analysis on previous ANN study [12] [15] Modeling and simulation of continuous reactive crystallization in presence of substrates and impurities [16,17] Dynamic optimization of non-isothermal batch reactor [18] Ampicillin UTIs Pneumonia Gonorrhea Meningitis Abdominal infections Regression of nucleation and growth kinetics for pH crystallization model [19] Modeling and simulation of reactive crystallization in presence of substrates and impurities [20] Modeling and simulation of continuous reactive crystallization in presence of substrates and impurities [16,17] Multi-objective dynamic optimization of pH crystallization [21] Cephalexin UTIs…”