Brahim Benyahia

End-to-End Continuous Manufacturing of Pharmaceuticals: Integrated Synthesis, Purification, and Final Dosage Formation†

A series of tubes: The continuous manufacture of a finished drug product starting from chemical intermediates is reported. The continuous pilot-scale plant used a novel route that incorporated many advantages of continuous-flow processes to produce active pharmaceutical ingredients and the drug product in one integrated system.

Multicriteria dynamic optimization of an emulsion copolymerization reactor

Abstract A multicriteria optimization approach based on an evolutionary algorithm has been developed to determine the optimal control policy for a fed-batch emulsion copolymerization reactor, particularly for styrene and butyl acrylate in the presence of n-C12 mercaptan as chain transfer agent. The process model was elaborated and validated experimentally in order to predict the global monomer conversion, the number and weight average molecular weights, the particle size distribution and the residual monomers mass fraction. The process objectives were to produce core–shell particles (hard core and smooth shell) with specific end-use properties and high productivity. This has been achieved by the maximization of the monomers overall conversion at the end of the process and the minimization of the error between the glass transition temperature and a designed profile subject to a set of operational constraints. The nondominated Pareto solutions obtained were ranked according to a decision making aid method based on a decision maker preferences and experience using multi-attribute utility theory. Finally, the best solution was implemented experimentally.

Dynamic optimization of semi-batch emulsion co-polymerization reactor for styrene/butyl acrylate in the presence of a chain transfer agent

Abstract We study dynamic optimization of a lab-scale semi-batch emulsion copolymerization reactor for styrene and butyl acrylate in the presence of n-dodecyl mercaptan as chain transfer agent (CTA). The previously developed mathematical model of the polymerization reactions is used to predict the glass transition temperature of produced polymer, the global monomer conversion, the number and weight average molecular weights, the particle size distribution, and the amount of residual monomers. This model is implemented within gPROMS environment for modeling and optimization. It is desired to compute optimal profiles of feed rate of pre-emulsioned monomers and CTA which optimize properties (quantitative as well as qualitative) of polymers produced during the reaction subject to operational conditions and constraints.

Applications of a plant-wide dynamic model of an integrated continuous pharmaceutical plant: Design of the recycle in the case of multiple impurities

Abstract One of the key advantages of continuous pharmaceutical manufacturing, besides enhanced control of mixing, reaction, and purification, is the potential for real-time recycling, which can reduce both production costs and environmental footprint. However, the design of an effective and robust plant-wide recycling loop may be very challenging because of the presence of various sources of impurities, such as raw materials as well as side and degradation reactions. The plant-wide dynamic model of an integrated end-to-end continuous pharmaceutical pilot plant is used to systematically to analyze the effect of the recycle on several key performance indicators. The continuous plant is assumed to operate for 60 days including start-up. This relatively short operational window makes the start-up, that may range from several days to a few weeks, one of the key considerations in the design, operation, and control of continuous pharmaceutical plants. The high significance of the start-up also suggests addressing plant-wide optimality in a different way compared to most conventional continuous industries, where the time required to reach steady state is typically below 10% of the operating time. The outlet stream of the first wash and filtration stage is being recycled, after a necessary purge step and solvent removal. The purge ratio and wash factors are considered as the most critical process parameters whose effect on start-up time and other key performance indicators is systematically addressed. Due to the high price of raw material, it may be tempting to maximize the recycle flowrate (reduce purge ratio). However, this may dramatically impact the rate of on-spec production and time to steady state. Nevertheless, the dynamic simulations provide a reliable and valuable tool to achieve a tradeoff among all performance consideration. It was demonstrated, based on dynamic simulations, that on-spec tablets can be produced during start-up, considering predefined acceptance levels of 7 impurities as the critical quality attributes (i.e., two isomers, one byproduct, one degradation product, two solvents, and one reaction intermediate). The plant wide simulations also showed the greenness potential of continuous manufacturing. The analysis of the plant wide environmental foot print under typical and optimal recycling scenarios demonstrated that the plant-wide E-factor may be lowered below 20, which is significantly lower than the values typically exhibited by most batch pharmaceutical processes (between 25 and 100).

Analysis of optimal operation of a fed-batch emulsion copolymerization reactor used for production of particles with core-shell morphology

Abstract In this paper dynamic optimization of a lab-scale semi-batch emulsion copolymerization reactor for styrene and butyl acrylate in the presence of a chain transfer agent (CTA) is studied. The mathematical model of the process, previously developed and experimentally validated, is used to predict the glass transition temperature of produced polymer, the number and weight average molecular weights, the monomers global conversion, the particle size distribution, and the amount of residual monomers. The model is implemented within gPROMS environment for modeling and optimization. It is desired to compute feed rate profiles of pre-emulsioned monomers, inhibitor and CTA that will allow the production of polymer particles with prescribed core–shell morphology with high productivity. The results obtained for different operating conditions and various additional product specifications are presented. The resulting feeding profiles are analyzed from the perspective of the nature of emulsion polymerization process and some interesting conclusions are drawn.

Multicriteria dynamic optimization of an emulsion copolymerization reactor [conference paper]

A multicriteria optimization procedure based on an evolutionary algorithm has been developed to determine the optimal control policies for a fed-batch emulsion copolymerization reactor, particularly for styrene and butyl acrylate in the presence of n-C12 mercaptan as chain transfer agent (CTA). The process model was elaborated and validated experimentally in order to predict the global monomer conversion, the number and weight average molecular weights, the particle size distribution and the residual monomers mass fraction. The process objectives were to produce core-shell particles (hard core and smooth shell) with specific end use properties and high productivity. This has been achieved by the maximization of the conversion at the end of the process and the minimization of the error between the glass transition temperature and a designed profile subject to a set of operational constraints. The nondominated Pareto solutions obtained were ranked according to a decision aid strategy based on a decision maker preferences and experience using multiple attribute utility theory (MAUT). Finally, the best solution was implemented experimentally.

A Global State Feedback Linearization and Decoupling MPC of a MIMO Continuous MSMPR Cooling Crystallization Process

Abstract Continuous manufacturing of pharmaceuticals requires effective control strategies to meet the tightly regulated critical product quality attributes, which has triggered a wide interest in model predictive control (MPC) techniques. This study applies a linear form of MPC to a nonlinear seeded continuous MSMPR crystallization process of acetaminophen in water, by using a global linearization technique; input-output statefeedback linearization (SFL). The two novelties are the application of MPC with SFL to continuous crystallization for SISO and MIMO systems; and the handling of the constraints as part of the SFL framework. For a single-input single-output system (SISO), MPC with SFL is applied to achieve a supersaturation reference trajectory by manipulating the coolant temperature subject to bounds and constraints. Additionally a multiple-input multiple-output (MIMO) case is presented using MPC with SFL and decoupling (SFLD). The supersaturation control from SISO was implemented in conjunction with crystal mean size control by manipulating the seed loading rate within bounds. The SISO configuration managed to control the crystallization process to within 1% of a prescribed set-point value within 2 residence times. In contrast, the MIMO controller was only able to stay within 4% of the set-point after 10 residence times, likely due to the highly coupled effects of the inputs on the outputs, which are lost in part due to the SFLD.

Local vs Global Estimability Analysis of Population Balance Models for Crystallization Processes

Abstract Estimability and sensitivity analysis has been applied to a one-dimensional population balance model (PBM) that describes the dynamic evolution of the critical quality attributes (CQAs) for a batch cooling crystallization process in order to assess the estimability potential of the identified parameters. Hybrid non-convex optimization model-based approaches have been utilized for the identification of the crystallization kinetics. The results were validated by using experimental online and offline process analytical tools (PAT) for the determination of the evolution of mean crystal size and the solution concentration. Then the optimum subset of parameters was determined based on two different approaches: (1) a sequential orthogonalization of the sensitivity matrix and (2) a variance-based global sensitivity analysis approach. The estimability analysis revealed that due to the low information content of the data and correlation between the parameters, only 4 parameters out of 13 are identifiable, ascertaining that the model is over-parameterized. By applying this methodology the most influential and least correlated parameters could be identified more reliably, providing enhanced prediction capabilities of the overall dynamics of the studied crystallization process.

Multi-objective Optimization of Small-size Wastewater Treatment Plants Operation

This paper deals with the multi-objective optimal control of a small-size wastewater treatment plant, where the excess sludge produced is incinerated for electricity production. The trade-offs between the treatment quality and operating costs are characterized. Emphasis is put on a proper formulation of the problem so as to get physically relevant solutions. Sludge incineration is shown to be quite profitable energetically, especially when a high nitrogen discharge is tolerated.

Optimized Production of Multilayered Monodisperse Polymer Nanoparticles.

Abstract A dynamic optimization frame work is used to produce in a controlled way multilayered latex nanoparticles. The key feature of the method is to track a glass transition temperature profile, which is designed to produce polymer layers with the targeted properties. Several constraints are considered to achieve better control and produce nanoparticles with a specified particle diameter and layers’ thicknesses. To enhance the control of the different layers,two separate monomer feeds are considered under starving conditions throughout the fed-batch stages. The emulsion copolymerization of styrene and butyl acrylate in the presence of n-C12 mercaptan, as chain transfer agent (CTA), is illustrated here as a case study. The optimal feed profiles of the pre-emulsioned monomers are obtained using a genetic algorithm.