Implementation of a fully integrated continuous manufacturing line for direct compression and coating at a commercial pharmaceutical facility - Part 1: Operational considerations and control strategy.

We implement a fully integrated continuous manufacturing (CM) line for direct compression and coating of a pharmaceutical oral solid dosage form in a commercial production facility. In this first paper of a two-part series, we describe process design and operational choices made to introduce CM using infrastructure originally intended for batch operations. Consistent with lean manufacturing principles, we select equipment, facilities, and novel process analytical technologies that meet production agility goals alongside an existing batch process. Choices address process risks, are aligned with existing quality systems, yet allow exploration of CM agility benefits in commercial operations. We outline how operating procedures, control schemes, and release criteria from the historical batch process are adapted for CM with modified lot and yield definitions based on patient demand. We devise a hierarchy of complementary controls including real-time process interrogation, predictive residence time distribution models of tablet concentration, real-time product release testing using automated tablet NIR spectroscopy, active rejection and diversion, and throughput-based sampling. Results from lots produced under normal operational conditions confirm our CM process provides assurance of product quality. Qualification strategies to achieve lot size flexibility aims are also described. Finally, we consider CM extensions to formulations with differing risk profiles. Further analysis of results for lots produced under normal operational conditions is provided in part 2 (Rosas et al., 2023).

Implementation of a fully integrated CM direct compression and coating process at a commercial pharmaceutical facility - Part 2: PAT and RTD results for normal operational conditions batches.

This is the second of two articles detailing the continuous manufacturing (CM) development and implementation activities for an marketed product which have been realized in novel, qualified equipment, using validated control strategy elements to enable manufacture of batches under current good manufacturing practices (cGMP) and compliant with data integrity principles. Here, the application of process analytical technologies (PAT) and automation tools on batches produced under normal operational conditions is reviewed. The results from residence time distribution (RTD) models for predicting API concentration, in-line near infrared (NIR) testing of blend uniformity (BU) and at-line NIR spectroscopy analysis of core tablet concentration and tablet identity for real-time release testing (RTRT) are discussed. The influences of process equipment and design choices on NIR and RTD model variability, as well as the use of the PAT tools for monitoring the evolving properties understanding of CM process development, such as overcoming flow instabilities, is described. Results demonstrate that the RTD and NIR models developed and validated are robust to operating conditions and are critical for assuring steady state control of the continuous manufacturing process. Finally, the NIR and RTD model lifecycle, including procedures for necessary and normal model upgrades in a cGMP production environment, are presented.

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

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.