Impact of roll compactor scale on ribbon density

Implementation of mechanistic modeling and global sensitivity analysis (GSA) for design, optimization, and scale-up of a roller compaction process

The pharmaceutical industry has been shifting towards the application of mechanistic modeling to improve process robustness, enable scale-up, and reduce time to market. Modeling approaches have been well-developed for processes such as roller compaction, a continuous dry granulation process. Several mechanistic models/approaches have been documented with limited application to high drug-loaded formulations. In this study, the Johanson model was employed to optimize roller compaction processing and guide its scale-up for a high drug loaded formulation. The model was calibrated using a pilot-scale Minipactor and was validated for a commercial-scale Macropactor. Global sensitivity analysis (GSA) was implemented to determine the impact of process parameter variations (roll force, gap, speed) on a quality attribute [solid fraction (SF)]. The throughput method, which estimates SF values of ribbons using granule production rate, was also studied. The model predicted SF values for all 14 Macropactor batches within ± 0.04 SF. The throughput method estimated SF with ± 0.06 SF for 7 out of 11 batches. GSA confirmed that roll force had the largest impact on SF. This case study represents a process modeling approach to build quality into the products/processes and expands the use of mechanistic modeling during drug product development.

Laser Triangulation Based In-Line Elastic Recovery Measurement for the Determination of Ribbon Solid Fraction in Roll Compaction

Process Analytical Technology (PAT) plays a crucial role in the design of today's manufacturing lines as continuous manufacturing becomes more important. Until now PAT tools to measure the ribbon solid fraction (SFribbon) in-line are not commonly used in roll compaction. The aim of this study was therefore to establish a new approach as PAT for in-line ribbon solid fraction determination. Different placebo formulations with different binders and one formulation containing active pharmaceutical ingredient were investigated using in-line laser triangulation measurement to detect the ribbon thickness after compaction. With this the ribbon elastic recovery was determined in-line (ERin-line) while the ribbons are attached to the roll surface. It was found that the ratio (ERratio) between the total elastic recovery and ERin-line is formulation specific and not influenced by any process parameters. This enables ERratio as prediction tool for SFribbon, if the solid fraction at gap (SFgap) width is known. SFgap was determined with ribbon mass flow measurement or based on the Midoux model, a simplified Johanson model, gaining two prediction models for SFribbon. Both models showed good agreement of the predicted SFribbon and the measured one.

Systematic DOE Approach for Dry Granulation Study at Early Clinical Stage of Novel Drugs: An Industrial Case

In order to introduce a cost-effective strategy method for commercial scale dry granulation at the early clinical stage of drug product development, we developed dry granulation process using formulation without API, fitted and optimized the process parameters adopted Design of Experiment (DOE). Then, the process parameters were confirmed using one formulation containing active pharmaceutical ingredient (API). The results showed that the roller pressure had significant effect on particle ratio (retained up to #60 mesh screen), bulk density and tapped density. The roller gap had significant influence on particle ratio and specific energy. The particle ratio was significantly affected by the mill speed (second level). The tabletability of the powder decreased after dry granulation. The effect of magnesium stearate on the tabletability was significant. In the process validation study, the properties of the prepared granules met the requirements for each response studied in the DOE. The prepared tablets showed higher tensile strength, good content uniformity of filled capsules, and the dissolution profiles of which were consistent with that of clinical products. This drug product process development and research strategies could be used as a preliminary experiment for the dry granulation process in the early clinical stage.

Laser triangulation as a fast and reliable method for determining ribbon solid fraction; focus on accuracy, precision, and measurement time

Roller compaction and dry granulation represent well-established unit operations in the pharmaceutical industry. The ribbon solid fraction is classified as a critical quality attribute, that directly impacts final product quality and performance. The development and evaluation of novel methods measuring ribbon solid fraction represent a subject of current research, since novel analyses strategies need to be established for at-, on-, or in-line process monitoring to overcome limitations of end product testing and to set the course for continuous manufacturing. In this study, a novel analytical device, using the principle of laser triangulation, was investigated to asses its potential being used as at-line process analytical technology tool during a roller compaction process. To this end, the laser triangulation device was compared with X-ray micro-computed tomography and powder based volume displacement measurement techniques using different statistical evaluation methods. Special focus was given to accuracy, precision, and total measurement time. The laser triangulation device was confirmed as highly accurate and precise, enabling the shortest total measurement time compared to the other methods. The findings of this study support the idea of implementing the laser triangulation device as a novel at-line process analytical technology tool into a roller compaction process.

Process Analytical Technology Tools for Monitoring Pharmaceutical Unit Operations: A Control Strategy for Continuous Process Verification

Various frameworks and methods, such as quality by design (QbD), real time release test (RTRT), and continuous process verification (CPV), have been introduced to improve drug product quality in the pharmaceutical industry. The methods recognize that an appropriate combination of process controls and predefined material attributes and intermediate quality attributes (IQAs) during processing may provide greater assurance of product quality than end-product testing. The efficient analysis method to monitor the relationship between process and quality should be used. Process analytical technology (PAT) was introduced to analyze IQAs during the process of establishing regulatory specifications and facilitating continuous manufacturing improvement. Although PAT was introduced in the pharmaceutical industry in the early 21st century, new PAT tools have been introduced during the last 20 years. In this review, we present the recent pharmaceutical PAT tools and their application in pharmaceutical unit operations. Based on unit operations, the significant IQAs monitored by PAT are presented to establish a control strategy for CPV and real time release testing (RTRT). In addition, the equipment type used in unit operation, PAT tools, multivariate statistical tools, and mathematical preprocessing are introduced, along with relevant literature. This review suggests that various PAT tools are rapidly advancing, and various IQAs are efficiently and precisely monitored in the pharmaceutical industry. Therefore, PAT could be a fundamental tool for the present QbD and CPV to improve drug product quality.

A Multi-variate Mathematical Model for Simulating the Granule Size Distribution in Roller Compaction-Milling Process

Granule size distribution (GSD) is one of the critical quality attributes in the roller compaction (RC) process. Determination of GSD for newly developed pharmaceutical compounds with unknown ribbon breakage behaviors at the RC milling step requires a quantitative insight into process parameters and ribbon attributes. Despite its pivotal role in mapping the process operating conditions to achieve desired granule size, limited work has been presented in literature with a focus on RC-milling modeling. In this study, a multi-variate mathematical model is presented to simulate the full size-distribution of granulated ribbons as a function of ribbon mechanical properties. Experimental data with a lab-scale oscillating milling apparatus were generated using ribbons made of various powder compositions. Model parameters were determined by fitting it to experimental data sets. Parameters obtained from the first step were correlated to ribbon Young's modulus. The model was validated by predicting GSD of data that were excluded in model development step. Predictive capabilities of the developed model were further explored by simulating GSD profiles of a granulated pharmaceutical excipient obtained at three different conditions of a real-scale Gerteis RC system. While maintaining the milling operating conditions similar to the lab-scale apparatus (i.e., screen size and spacing, and low rotor speed), the proposed modeling approach successfully predicted the GSD of roller compacted MCC powder as the model compound. This model can be alternatively utilized in conjunction with an RC model in order to facilitate the process understanding to obtain granule attributes as part of Quality-by-Design paradigm.

Integrated Multi-stakeholder Systems Thinking Strategy: Decision-making with Biopharmaceutics Risk Assessment Roadmap (BioRAM) to Optimize Clinical Performance of Drug Products

Decision-making in drug development benefits from an integrated systems approach, where the stakeholders identify and address the critical questions for the system through carefully designed and performed studies. Biopharmaceutics Risk Assessment Roadmap (BioRAM) is such a systems approach for application of systems thinking to patient focused and timely decision-making, suitable for all stages of drug discovery and development. We described the BioRAM therapy-driven drug delivery framework, strategic roadmap, and integrated risk assessment instrument (BioRAM Scoring Grid) in previous publications (J Pharm Sci 103:3377-97, 2014; J Pharm Sci 105:3243-55, 2016). Integration of systems thinking with pharmaceutical development, manufacturing, and clinical sciences and health care is unique to BioRAM where the developed strategy identifies the system and enables risk characterization and balancing for the entire system. Successful decision-making process in BioRAM starts with the Blueprint (BP) meetings. Through shared understanding of the system, the program strategy is developed and captured in the program BP. Here, we provide three semi-hypothetical examples for illustrating risk-based decision-making in high and moderate risk settings. In the high-risk setting, which is a rare disease area, two completely alternate development approaches are considered (gene therapy and small molecule). The two moderate-risk examples represent varied knowledge levels and drivers for the programs. In one moderate-risk example, knowledge leveraging opportunities are drawn from the manufacturing knowledge and clinical performance of a similar drug substance. In the other example, knowledge on acute tolerance patterns for a similar mechanistic pathway is utilized for identifying markers to inform the drug release profile from the dosage form with the necessary "flexibility" for dosing. All examples illustrate implementation of the BioRAM strategy for leveraging knowledge and decision-making to optimize the clinical performance of drug products for patient benefit.

Model-Based Scale-Up Methodologies for Pharmaceutical Granulation

In the pharmaceutical industry, it is a major challenge to maintain consistent quality of drug products when the batch scale of a process is changed from a laboratory scale to a pilot or commercial scale. Generally, a pharmaceutical manufacturing process involves various unit operations, such as blending, granulation, milling, tableting and coating and the process parameters of a unit operation have significant effects on the quality of the drug product. Depending on the change in batch scale, various process parameters should be strategically controlled to ensure consistent quality attributes of a drug product. In particular, the granulation may be significantly influenced by scale variation as a result of changes in various process parameters and equipment geometry. In this study, model-based scale-up methodologies for pharmaceutical granulation are presented, along with data from various related reports. The first is an engineering-based modeling method that uses dimensionless numbers based on process similarity. The second is a process analytical technology-based modeling method that maintains the desired quality attributes through flexible adjustment of process parameters by monitoring the quality attributes of process products in real time. The third is a physics-based modeling method that involves a process simulation that understands and predicts drug quality through calculation of the behavior of the process using physics related to the process. The applications of these three scale-up methods are summarized according to granulation mechanisms, such as wet granulation and dry granulation. This review shows that these model-based scale-up methodologies provide a systematic process strategy that can ensure the quality of drug products in the pharmaceutical industry.

Sensor Network Robustness Using Model-Based Data Reconciliation for Continuous Tablet Manufacturing

Advances in continuous manufacturing in the pharmaceutical industry necessitate reliable process monitoring systems that are capable of handling measurement errors inherent in all sensor technologies and detecting measurement outliers to ensure operational reliability. The purpose of this work was to demonstrate data reconciliation (DR) and gross error detection methods as real-time process management tools to accomplish robust process monitoring. DR mitigates the effects of random measurement errors, while gross error detection identifies nonrandom sensor malfunctions. DR is an established methodology in other industries (i.e., oil and gas) and was recently investigated for use in drug product continuous manufacturing. This work demonstrates the development and implementation of model-based steady-state data reconciliation on 2 different end-to-end continuous tableting lines: direct compression and dry granulation. These tableting lines involve different equipment and sensor configurations, with sensor network redundancy achieved using equipment-embedded sensors and in-line process analytical technology tools for the critical process parameters and critical quality attributes. The nonlinearity of the process poses additional challenges to solve the steady-state data reconciliation optimization problem in real time. At-line and off-line measurements were used to validate the framework results.

Impact of roll compaction design, process parameters, and material deformation behaviour on ribbon relative density

Ribbons from microcrystalline cellulose (MCC), mannitol, and their 50:50% mixture were produced using the roll compactors AlexanderWerk BT120, Hosokawa Alpine Pharmapaktor C250, L.B. Bohle BRC 25, and Gerteis Mini-Pactor in the frame of multilevel full factorial experimental plans. The specific compaction force (SCF)/hydraulic pressure (HP), gap width (GW), roll speed, and fraction of MCC were analyzed as quantitative factors, whereas the roll surface and sealing system were examined as qualitative factors. Ribbon relative density was investigated as response of the models. The SCF/HP is found to be the most significant factor in each model. A significant inverse effect of the GW is obtained in the models of AlexanderWerk BT120, Pharmapaktor C250, and BRC 25 roll compactors, using smooth rolls. The principle of the establishment of a conversion factor (c_f) is introduced based on the obtained data sets of AlexanderWerk BT120 and Mini-Pactor. This can facilitate the transfer of a roll compaction process between different types of roll compactors.