In-depth analysis of the long-term processability of materials during continuous feeding

Continuous direct compression of a commercially batch-manufactured tablet formulation with two different processing lines

The transfer from batch-based to continuous tablet manufacturing increases the quality and efficiency of processes. Nonetheless, as in the development of a batch process, the continuous process design requires optimization studies to ensure a robust process. In this study, processing of a commercially batch-manufactured tablet product was tested with two continuous direct compression lines while keeping the original formulation composition and tablet quality requirements. Tableting runs were conducted with different values of process parameters. Changes in parameter settings were found to cause differences in tablet properties. Most of these quality properties could be controlled and maintained within the set limits effortlessly already at this stage of studies. However, the API content and content uniformity seemed to require more investigation. The observed content uniformity challenges were traced to individual tablets with a high amount of API. This was suspected to be caused by API micro-agglomerates since tablet weight variability did not explain the issue. This could be solved by adding a mill between two blenders in the process line. Overall, this case study produced promising results with both tested manufacturing lines since many tablet properties complied with the test result limits without optimization of process parameter settings.

Batch vs. continuous direct compression - a comparison of material processability and final tablet quality

In this study, an in-depth comparison was made between batch and continuous direct compression using similar compression set-ups. The overall material processability and final tablet quality were compared and evaluated. Correlations between material properties, process parameters and final tablet properties were made via multivariate data analyses. In total, 10 low-dosed (1% w/w) and 10 high-dosed (40% w/w) formulations were processed, using a total of 10 different fillers/filler combinations. The trials indicated that the impact of filler type, drug load or process settings was similar for batch and continuous direct compression. The main differentiator between batch and continuous was the flow dynamics in the operating system, where properties related to flow, compressibility and permeability played a crucial role. The less consistent flow throughout a batch process resulted in a significantly higher variability within the tablet press (σCF) and for the tablet quality responses (σMass, σTS). However, the better controlled blending procedure prior to batch processing was reflected in a more consistent API concentration variability. Overall, the comparison showed the benefits of selecting appropriate excipients and process settings to achieve a specific outcome, keeping in mind some key differentiators between both processes.

Cleaning of direct compression continuous manufacturing equipment through displacement of API residues by excipients

This feasibility study evaluates a cleaning process designed to avoid the use of detergents and reduce operator exposure to the active pharmaceutical ingredient (API). The continuous manufacturing equipment was cleaned using excipients to displace ibuprofen residues from the system. The cleaning process was performed using 3.0 kg of Prosolv® and 3.0 kg of Tablettose® 70. The impact of different volumetric feed rates of the cleaning excipient was assessed. The displacement of API and blend residues was evaluated with in-line near infrared (NIR) spectroscopy. Principal component analysis (PCA) was performed to evaluate the cleaning progress as the Prosolv® flowed through the feeder, mixer and stream sampler. In-place Raman spectra were acquired from the material sticking to detect the ibuprofen residues. The study showed that Prosolv® and Tablettose® can remove ibuprofen residues effectively from the hopper, feeder screw, mixer paddles, shaft and stream sampler. The Process Analytical Technology (PAT) system can be utilized to detect API displacement during the cleaning process. However, dismantling and manual cleaning was required to remove material sticking at the surfaces adjacent to the rotating feeder screws and mixer paddles.

Sample Size Requirements of a Pharmaceutical Material Library: A Case in Predicting Direct Compression Tablet Tensile Strength by Latent Variable Modeling

The material library is an emerging, new data-driven approach for developing pharmaceutical process models. How many materials or samples should be involved in a particular application scenario is unclear, and the impact of sample size on process modeling is worth discussing. In this work, the direct compression process was taken as the research object, and the effects of different sample sizes of material libraries on partial least squares (PLS) modeling in the prediction of tablet tensile strength were investigated. A primary material library comprising 45 materials was built. Then, material subsets containing 5 × i (i = 1, 2, 3, …, 8) materials were sampled from the primary material library. Each subset underwent sampling 1000 times to analyze variations in model fitting performance. Both hierarchical sampling and random sampling were employed and compared, with hierarchical sampling implemented with the help of the tabletability classification index d. For each subset, modeling data were organized, incorporating 18 physical properties and tableting pressure as the independent variables and tablet tensile strength as the dependent variable. A series of chemometric indicators was used to assess model performance and find important materials for model training. It was found that the minimum R2 and RMSE values reached their maximum, and the corresponding values were kept almost unchanged when the sample sizes varied from 20 to 45. When the sample size was smaller than 15, the hierarchical sampling method was more reliable in avoiding low-quality few-shot PLS models than the random sampling method. Two important materials were identified as useful for building an initial material library. Overall, this work demonstrated that as the number of materials increased, the model's reliability improved. It also highlighted the potential for effective few-shot modeling on a small material library by controlling its information richness.

On the influence of raw material attributes on process behaviour and product quality in a continuous WET granulation tableting line

Continuous manufacturing of oral solids is a complex process in which critical material attributes (CMAs), formulation and critical process parameters (CPPs) play a fundamental role. However, assessing their effect on the intermediate and final product's critical quality attributes (CQAs) remains challenging. The aim of this study was to tackle this shortcoming by evaluating the influence of raw material properties and formulation composition on the processability and quality of granules and tablets on a continuous manufacturing line. Powder-to-tablet manufacturing was performed using four formulations in various process settings. Pre-blends of different drug loadings (2.5 % w/w and 25% w/w) and two BCS classes (Class I and II) were continuously processed on an integrated process line ConsiGmaTM 25, including twin screw wet granulation, fluid bed drying, milling, sieving, in-line lubrication and tableting. The liquid-to-solid ratio and the granule drying time were varied to process granules under nominal, dry and wet conditions. It was shown that the BCS class and the drug dosage influenced the processability. Intermediate quality attributes, such as the loss on drying and the particle size distribution, directly correlated with the raw material's properties and process parameters. Process settings had a profound impact on the tablet's hardness, disintegration time, wettability and porosity.

Reviewing the Impact of Powder Cohesion on Continuous Direct Compression (CDC) Performance

The pharmaceutical industry is undergoing a paradigm shift towards continuous processing from batch, where continuous direct compression (CDC) is considered to offer the most straightforward implementation amongst powder processes due to the relatively low number of unit operations or handling steps. Due to the nature of continuous processing, the bulk properties of the formulation will require sufficient flowability and tabletability in order to be processed and transported effectively to and from each unit operation. Powder cohesion presents one of the greatest obstacles to the CDC process as it inhibits powder flow. As a result, there have been many studies investigating potential manners in which to overcome the effects of cohesion with, to date, little consideration of how these controls may affect downstream unit operations. The aim of this literature review is to explore and consolidate this literature, considering the impact of powder cohesion and cohesion control measures on the three-unit operations of the CDC process (feeding, mixing, and tabletting). This review will also cover the consequences of implementing such control measures whilst highlighting subject matter which could be of value for future research to better understand how to manage cohesive powders for CDC manufacture.

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.