A Virtual Plant for Integrated Continuous Manufacturing of a Carfilzomib Drug Substance Intermediate, Part 3: Manganese-Catalyzed Asymmetric Epoxidation, Crystallization, and Filtration

Crystallization of Bis(2-hydroxyethylene) Terephthalate as a Part of a Bottle-to-Bottle Recycling Concept for Poly(ethylene terephthalate)

The chemical recycling of poly(ethylene terephthalate) (PET) is very attractive as PET bottle waste provides an abundant clean material with low levels of additives. One of the most promising processes is glycolysis, which depolymerizes PET in the presence of ethylene glycol. For this process, it is necessary to think through the whole concept, from the waste material to the newly polymerized virgin polymer. Most research ends with determining the yield of bis(2-hydroxyethyl)terephthalate (BHET) after glycolysis. Some research includes antisolvent crystallization with water to separate BHET from ethylene glycol. However, the subsequent separation of water and ethylene glycol is an energy-intensive process. Therefore, this work aims to directly crystallize BHET from ethylene glycol. For this reason, the crystallization of BHET was investigated experimentally. Crystallization was simulated using gPROMS Formulated Products with the aim of estimating kinetic parameters and using these to optimize an industrial process. Kinetic parameters were determined by model validation, including primary and secondary nucleation and crystal growth. The best-fitting set of kinetic parameters was used to optimize BHET crystallization in batch and continuous modes by minimizing equipment costs. Impeller parameters were found to have a great influence on crystallization performance. Ultimately, the continuous and batch processes gave comparable results in terms of equipment cost, with the batch process giving larger crystals and higher yields but the continuous process requiring a smaller crystallizer.

Diversification of Pharmaceutical Manufacturing Processes: Taking the Plunge into the Non-PGM Catalyst Pool

Recent global events have led to the cost of platinum group metals (PGMs) reaching unprecedented heights. Many chemical companies are therefore starting to seriously consider and evaluate if and where they can substitute PGMs for non-PGMs in their catalytic processes. This review covers recent highly relevant applications of non-PGM catalysts in the modern pharmaceutical industry. By highlighting these selected successful examples of non-PGM-catalyzed processes from the literature, we hope to emphasize the enormous potential of non-PGM catalysis and inspire further development within this field to enable this technology to progress toward manufacturing processes. We also present some historical contexts and review the perceived advantages and challenges of implementing non-PGM catalysts in the pharmaceutical manufacturing environment.

Integrated Filtration and Washing Modeling: Optimization of Impurity Rejection for Filtration and Washing of Active Pharmaceutical Ingredients

A digital design tool that can transfer material property information between unit operations to predict the product attributes in integrated purification processes has been developed to facilitate end-to-end integrated pharmaceutical manufacturing. This work aims to combine filtration and washing operations frequently using active pharmaceutical ingredient (API) isolation. This is achieved by coupling predicted and experimental data produced during the upstream crystallization process. To reduce impurities in the isolated cake, a mechanistic model-based workflow was used to optimize an integrated filtration and washing process model. The Carman-Kozeny filtration model has been combined with a custom washing model that incorporates diffusion and axial dispersion mechanisms. The developed model and approach were applied to two systems, namely, mefenamic acid and paracetamol, which are representative compounds, and various crystallization and wash solvents and related impurities were used. The custom washing model provides a detailed evolution of species concentration during washing, simulating the washing curve with the three stages of the wash curve: constant rate, intermediate stage, and diffusion stage. A model validation approach was used to estimate cake properties (e.g., specific cake resistance, cake volume, cake composition after washing, and washing curve). A global systems analysis was conducted by using the calibrated model to explore the design space and aid in the setup of the optimization decision variables. Qualitative optimization was performed in order to reduce the concentration of impurities in the final cake after washing. The findings of this work were translated into a final model to simulate the optimal isolation conditions.

Digital design of an integrated purification system for continuous pharmaceutical manufacturing

In this work dynamic models of the continuous crystallization, filtration, deliquoring, washing, and drying steps are introduced, which are developed in the open-source pharmaceutical modeling tool PharmaPy. These models enable the simulation and digital design of an integrated continuous two-stage crystallization and filtration-drying carousel system. The carousel offers an intensified process that can manufacture products with tailored properties through optimal design and control. Results show that improved crystallization design enhances overall process efficiency by improving critical material attributes of the crystal slurry for downstream filtration and drying operations. The digital design of the integrated process achieves enhanced productivity while satisfying multiple design and product quality constraints. Additionally, the impact of model uncertainty on the optimal operating conditions is investigated. The findings demonstrate the systematic process development potential of PharmaPy, providing improved process understanding, design space identification, and optimized robust operation.

Continuous Extraction of 2-Chloroethyl isocyanate for 1-(2-chloroethyl)-3-cyclohexylurea Purification

This study details the development of simulation-aided design, development, and successful operation of a continuous liquid-liquid extraction platform made with 1.5 mm tubing for the extraction of 2-chloroethyl isocyanate, an important reagent in the synthesis of cancer drugs. Preliminary solvent screening was carried out with partition coefficient calculations to determine solvents of interest. Next, batch and flow extraction experiments of 2-chloroethyl isocyanate in 2-methyl tetrahydrofuran and water were conducted to estimate extraction parameters. Following parameter estimation, experimental and model values for KLa were determined in the range of 1.13×10-3 to 36.0×10-3 s-1. Simulations of the extraction of 2-chloroethyl isocyanate were found to agree with experimental data resulting in a maximum efficiency of 77% and percent extraction of 69% for the continuous platform. Finally, model selection and discrimination was implemented for design space generation with experimental and model determined KLa values to guide lab-scale operation.

Digital Design of Filtration and Washing of Active Pharmaceutical Ingredients via Mechanistic Modeling

To facilitate integrated end-to-end pharmaceutical manufacturing using digital design, a model capable of transferring material property information between operations to predict product attributes in integrated purification processes has been developed. The focus of the work reported here combines filtration and washing operations used in active pharmaceutical ingredient (API) purification and isolation to predict isolation performance without the need of extensive experimental work. A fixed Carman-Kozeny filtration model is integrated with several washing mechanisms (displacement, dilution, and axial dispersion). Two limiting cases are considered: case 1 where there is no change in the solid phase during isolation (no particle dissolution and/or growth), and case 2 where the liquid and solid phases are equilibrated over the course of isolation. In reality, all actual manufacturing conditions would be bracketed by these two limiting cases, so consideration of these two scenarios provides rigorous theoretical bounds for assessing isolation performance. This modeling approach aims to facilitate the selection of most appropriate models suitable for different isolation scenarios, without the requirement to use overly complex models for straightforward isolation processes. Mefenamic acid and paracetamol were selected as representative model compounds to assess a range of isolation scenarios. In each case, the objective of the models was to identify the purity of the product reached with a fixed wash ratio and minimize the changes to the crystalline particle attributes that occur during the isolation process. This was undertaken with the aim of identifying suitable criteria for the selection of appropriate filtration and washing models corresponding to relevant processing conditions, and ultimately developing guidelines for the digital design of filtration and washing processes.

Holistic Process Models: A Bayesian Predictive Ensemble Method for Single and Coupled Unit Operation Models

The coupling of individual models in terms of end-to-end calculations for unit operations in manufacturing processes is a challenging task. We present a probability distribution-based approach for the combined outcomes of parametric and non-parametric models. With this so-called Bayesian predictive ensemble, the statistical moments such as mean value and standard deviation can be accurately computed without any further approximation. It is shown that the ensemble of different model predictions leads to an uninformed prior distribution, which can be transformed into a predictive posterior distribution using Bayesian inference and numerical Markov Chain Monte Carlo calculations. We demonstrate the advantages of our method using several numerical examples. Our approach is not restricted to certain unit operations, and can also be used for the more robust interpretation and assessment of model predictions in general.

Impurity incorporation in solution crystallization: diagnosis, prevention, and control

This work highlights recent advances in the diagnosis, prevention, and control of impurity incorporation during solution crystallization.

Reactor design and selection for effective continuous manufacturing of pharmaceuticals

Pharmaceutical production remains one of the last industries that predominantly uses batch processes, which are inefficient and can cause drug shortages due to the long lead times or quality defects. Consequently, pharmaceutical companies are transitioning away from outdated batch lines, in large part motivated by the many advantages of continuous manufacturing (e.g., low cost, quality assurance, shortened lead time). As chemical reactions are fundamental to any drug production process, the selection of reactor and its design are critical to enhanced performance such as improved selectivity and yield. In this article, relevant theories, and models, as well as their required input data are summarized to assist the reader in these tasks, focusing on continuous reactions. Selected examples that describe the application of plug flow reactors (PFRs) and continuous-stirred tank reactors (CSTRs)-in-series within the pharmaceutical industry are provided. Process analytical technologies (PATs), which are important tools that provide real-time in-line continuous monitoring of reactions, are recommended to be considered during the reactor design process (e.g., port design for the PAT probe). Finally, other important points, such as density change caused by thermal expansion or solid precipitation, clogging/fouling, and scaling-up, are discussed.

Graphical abstract