Development and Use of a Residence Time Distribution (RTD) Model Control Strategy for a Continuous Manufacturing Drug Product Pharmaceutical Process.

Samantha Hurley,Manuel Sebastian Escotet-Espinoza,Matthew Flamm,Anthony Tantuccio,Matthew Metzger

doi:10.3390/pharmaceutics14020355

Samantha Hurley, Manuel Sebastian Escotet-Espinoza + Show 3 more

Open Access

https://doi.org/10.3390/pharmaceutics14020355

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Journal: Pharmaceutics	Publication Date: Feb 3, 2022
Citations: 10	License type: CC BY 4.0

Affiliation: United States Military Academy

Abstract

Residence-time-distribution (RTD)-based models are key to understanding the mixing dynamics of continuous manufacturing systems. Such models can allow for material traceability throughout the process and can provide the ability for removal of non-conforming material from the finished product. These models have been implemented in continuous pharmaceutical manufacturing mainly for monitoring purposes, not as an integral part of the control strategy and in-process specifications. This paper discusses the steps taken to develop an RTD model design space and how the model was statistically incorporated into the product’s control strategy. To develop the model, experiments were conducted at a range of blender impeller speeds and total system mass flow rates. RTD parameters were optimized for each condition tested using a tank-in-series-type model with a delay. Using the experimental RTD parameters, an equation was derived relating the mean residence time to the operating conditions (i.e., blender impeller speed and mass flow rate). The RTD parameters were used in combination with real-time upstream process data to predict downstream API concentration, where these predictions allowed validation across the entire operating range of the process by comparison to measured tablet assay. The standard in-process control limits for the product were statistically tightened using the validation acceptance criteria. Ultimately, this model and strategy were accepted by regulatory authorities.

Highlights

Traditional industrial processing, such as petrochemical, steel, and high-volume food manufacturing, is performed using continuous processes
Continuous processes are a shift from the original batch processes, which mainly occurred in order to reap the many benefits of continuous manufacturing [1–3]
Continuous drug substance and product manufacturing has been sparked by the FDA. As they continually express their support for the development and implementation of continuous manufacturing for drug product processing [9–11]

Summary

Introduction

Traditional industrial processing, such as petrochemical, steel, and high-volume food manufacturing, is performed using continuous processes. Continuous processes are a shift from the original batch processes, which mainly occurred in order to reap the many benefits of continuous manufacturing [1–3]. Benefits of continuous processes include reduced cost and processing time and improved ability to implement time-independent control strategies [4,5]. This shift has only started to occur within the last few years due to many regulatory constraints and a relatively risk-averse culture. The push for the change in the pharmaceutical industry is due to the potential improvements to product flow in supply chains, such as leveraging fast cycle times and flexible batch sizes, and to a reduction in lead times and inventory levels [6–8].

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