Process analytical technology in Downstream-Processing of Drug Substances – A review

Process Analytical Technology (PAT) has revolutionized pharmaceutical manufacturing by providing real-time monitoring and control capabilities throughout the production process. This review paper comprehensively examines the application of PAT methodologies specifically in the production of solid active pharmaceutical ingredients (APIs). Beginning with an overview of PAT principles and objectives, the paper explores the integration of advanced analytical techniques such as spectroscopy, imaging modalities and others into solid API substance production processes. Novel developments in in-line monitoring at academic level are also discussed. Emphasis is placed on the role of PAT in ensuring product quality, consistency, and compliance with regulatory requirements. Examples from existing literature illustrate the practical implementation of PAT in solid API substance production, including work-up, crystallization, filtration, and drying processes. The review addresses the quality and reliability of the measurement technologies, aspects of process implementation and handling, the integration of data treatment algorithms and current challenges. Overall, this review provides valuable insights into the transformative impact of PAT on enhancing pharmaceutical manufacturing processes for solid API substances.

Introduction

Recently, efforts to develop and implement advanced routes in pharmaceutical manufacturing has increased significantly. This includes both process engineering and control. Both require the availability of information about the state of the process and the materials, and therefore the acquisition of data in real-time. Especially for continuous manufacturing or the combination of drug substance and drug product processing in an end-to-end process, real-time data is needed to trigger control actions, before the next unit operation is reached. To achieve a higher level of control according to the FDA control strategy implementation options, real-time measurements are also required (Yu et al., 2014). These requirements can be met by implementing process analytical technology (PAT) (Afnan, 2004).

In the meantime, the term PAT has become an umbrella term that is generally used to describe process monitoring systems using various hardware and software components. The classic understanding of PAT is a hard sensor, that measures a (critical) quality attribute (CQA) of a raw material, an intermediate or a product. A hard sensor measures a QA of the processed material either directly (e.g., particle size via an image-based method) or via a correlation with the measured quantity (e.g., concentration via spectroscopy). In addition, (critical) process parameters (CPPs) (e.g., temperature profiles) or data provided by the equipment itself (e.g., flow rates) can provide information about the process and material state or can be correlated with CQAs (Read et al., 2010). As an alternative to hard sensors, soft sensors complement a PAT concept. A soft sensor is based on a process model, that uses available data as input, and predicts the attribute of interest.

The standard quality requirements for analytical methods defined by the International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use (ICH) (International Conference on Harmonization, 2005) are: accuracy, precision, specificity, limit of detection, limit of quantification, linearity and range. More details on these criteria can be found in (Sacher et al., 2022a). In addition, the expectations of the manufacturing sector focus on a robust and automatable design, long maintenance intervals, easy process integration, low complexity of the generated data and compliance with GMP and ATEX.

While PAT has been widely adopted in active pharmaceutical ingredient (API) synthesis (Simon et al., 2015) and secondary manufacturing (Laske et al., 2017), applications in downstream processing of the API are still rare, with the exception of crystallization (Malwade and Qu, 2018, Misra et al., 2015, Nagy et al., 2013, Yu et al., 2004, Zhao et al., 2023). The process routes linking primary and secondary manufacturing are diverse and consist of a wide range of unit operations. In this review we follow a typical process chain together with the corresponding CQAs as shown in Fig. 1. After the synthesis of the API, a workup may be performed to prepare the reaction output for the downstream process. This can include an initial separation or purification. In the following steps the API is crystallized, separated from the liquid phase and dried to achieve a powder. The most relevant CQAs for each process steps are also shown in Fig. 1.

The aim of this review is to provide a comprehensive overview of existing PAT methods and tools to monitor the CQAs of intermediates and products over the process chain from the workup to the dry drug substance. Developments and applications from academic and industrial level are considered.

Read more here

Peter Neugebauer, Manuel Zettl, Daniel Moser, Johannes Poms, Lisa Kuchler, Stephan Sacher, Process analytical technology in Downstream-Processing of Drug Substances– A review, International Journal of Pharmaceutics, Volume 661, 2024, 124412, ISSN 0378-5173, https://doi.org/10.1016/j.ijpharm.2024.124412.

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