Development and Scale-Up of a Continuous Reaction for Production of an Active Pharmaceutical Ingredient Intermediate

A Brief Introduction to Chemical Reaction Optimization

From the start of a synthetic chemist's training, experiments are conducted based on recipes from textbooks and manuscripts that achieve clean reaction outcomes, allowing the scientist to develop practical skills and some chemical intuition. This procedure is often kept long into a researcher's career, as new recipes are developed based on similar reaction protocols, and intuition-guided deviations are conducted through learning from failed experiments. However, when attempting to understand chemical systems of interest, it has been shown that model-based, algorithm-based, and miniaturized high-throughput techniques outperform human chemical intuition and achieve reaction optimization in a much more time- and material-efficient manner; this is covered in detail in this paper. As many synthetic chemists are not exposed to these techniques in undergraduate teaching, this leads to a disproportionate number of scientists that wish to optimize their reactions but are unable to use these methodologies or are simply unaware of their existence. This review highlights the basics, and the cutting-edge, of modern chemical reaction optimization as well as its relation to process scale-up and can thereby serve as a reference for inspired scientists for each of these techniques, detailing several of their respective applications.

Automated optimization under dynamic flow conditions

The combination of feedback optimization with dynamic operations leads to enhanced data-rich experimentation in flow.

The application of modern reactions in large-scale synthesis

In the past decade, the field of organic synthesis has witnessed tremendous advancements in the areas of photoredox catalysis, electrochemistry, C-H activation, reductive coupling and flow chemistry. While these methods and technologies offer many strategic advantages in streamlining syntheses, their application on the process scale is complicated by several factors. In this Review, we discuss the challenges that arise when these reaction classes and/or flow chemistry technology are taken from a research laboratory operating at the milligram scale to a reactor capable of producing kilograms of product. We discuss how these challenges have been overcome through chemical and engineering solutions. Specifically, this Review will highlight key examples that have led to the production of multi-hundred-gram to kilogram quantities of active pharmaceutical ingredients or their intermediates and will provide insight on the scaling-up process to those developing new technologies and reactions.

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

Multidimensional dynamic experiments for data-rich process development of reactions in flow

The use of multidimensional dynamic flow experiments for reaction profiling and generation of an empirical surface response model for a Knoevenagel condensation reaction is described.