Mapping key process parameters to the performance of a continuous dry powder blender in a continuous direct compression system

Palmer, John P.; Reynolds, Gavin K.; Tahir, Furqan; Yadav, Indrajeetsinh K.; Meehan, E. J.; Holman, James; Bajwa, Gurjit

doi:10.1016/j.powtec.2019.12.028

Cited by 35 publications

(29 citation statements)

References 32 publications

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“…With the increasing interest in continuous manufacturing for pharmaceutical dosage forms, continuous blending of powders is also gaining attention ( Bhalode and Ierapetritou, 2020 ; Gao et al, 2013 ; Pernenkil and Cooney, 2006 ). Most studies on continuous powder blending so far have been focused on varying process parameters and the resulting effects on blending performance ( Gao et al, 2011 ; Järvinen et al, 2013 ; Palmer et al, 2020 ; Roth et al, 2017 ; Van Snick et al, 2017 ; Vanarase and Muzzio, 2011 ). Furthermore, theoretical modeling and simulation of continuous powder blending has been a topic of increased interest in recent years ( Galbraith et al, 2018 ; Gyürkés et al, 2020 ; Toson et al, 2018 ).…”

Section: Introductionmentioning

confidence: 99%

Batch versus continuous blending of binary and ternary pharmaceutical powder mixtures

Jaspers¹,

Kulkarni²,

Tegel³

et al. 2022

International Journal of Pharmaceutics: X

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The material properties of excipients and active pharmaceutical ingredients (API's) are important parameters that affect blend uniformity of pharmaceutical powder formulations. With the current shift from batch to continuous manufacturing in the pharmaceutical industry, blending of excipients and API is converted to a continuous process. The relation between material properties and blend homogeneity, however, is generally based on batch-wise blending trials. Limited information is available on how material properties affect blending performance in a continuous process. Here, blending of API and excipients is studied in both a batch and a continuous process. Homogeneity of the resulting mixtures is analyzed, which reveals that the impact of material properties is very different in a continuous process. Where parameters such as particle size, density and flowability have significant impact on blending performance in a traditional batch process, continuous blending is more robust resulting in uniform blends for a large variety of blend compositions.

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Section: Introductionmentioning

confidence: 99%

Batch versus continuous blending of binary and ternary pharmaceutical powder mixtures

Jaspers¹,

Kulkarni²,

Tegel³

et al. 2022

International Journal of Pharmaceutics: X

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“…If the feeding rate of one ingredient varies from the set point for even a short period of time, or if there is a spike in material due to accumulation in any part of the system, the resulting variability in concentration could produce out of specification material downstream (Weinekötter and Reh, 1995). Blenders are incorporated in the continuous manufacturing line and can offset some degree of feed variability (Palmer et al, 2020), but when the process shifts from acceptable ranges it results in material rejection via the control system, impacting the overall yield or causing the continuous process to stop for correction. Many studies of LIW feeders have not sufficiently evaluated the impact of feeder refills to the overall feasibility of feeding.…”

Section: Introductionmentioning

confidence: 99%

Loss-in-weight feeding, powder flow and electrostatic evaluation for direct compression hydroxypropyl methylcellulose (HPMC) to support continuous manufacturing

Allenspach

Timmins

Lumay

et al. 2021

International Journal of Pharmaceutics

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Minimizing variability in the feeding process is important for continuous manufacturing since materials are fed individually and can impact the final product. This study demonstrates the importance of measuring powder properties and highlights the need to characterize the feeding performance both offline with multiple refills and in the intended configuration for the continuous manufacturing equipment. The standard grade hydroxypropyl methylcellulose (HPMC) had material buildup on the loss-in-weight feeder barrel from triboelectric charging and resulted in more mass flow excursions and failed refills which were not observed with the direct compression grades. The location of the electrostatic buildup changed when the feeder was connected to a hopper instead of feeding offline into a collection bucket. Overall, the direct compression HPMC exhibited better flow which resulted in more accurate loss-in-weight feeding with less excursions from the target mass flow and all refills were completed in the first attempt. The improvements with the direct compression HPMC would be beneficial when running any continuous process (wet granulation, roller compaction, or direct compression) or other processes where loss-in-weight feeding is utilized, such as melt extrusion or twin screw granulation.

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“…Similar to the method in [31], the API concentration in the blended powder was determined using an inline SentroPAT FO NIR (near-infra-red) spectrometer with InGaAs photodiode array detector in the 1100-2200 nm range equipped with a diffuse reflectance fiber optic probe (Sentronic GmbH). The NIR calibration consisted of 337 samples spanning approximately 80-150% of the target API concentration, with minimized correlation between any two components.…”

Section: Methodsmentioning

confidence: 99%

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

et al. 2022

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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.

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Mapping key process parameters to the performance of a continuous dry powder blender in a continuous direct compression system

Cited by 35 publications

References 32 publications

Batch versus continuous blending of binary and ternary pharmaceutical powder mixtures

Batch versus continuous blending of binary and ternary pharmaceutical powder mixtures

Loss-in-weight feeding, powder flow and electrostatic evaluation for direct compression hydroxypropyl methylcellulose (HPMC) to support continuous manufacturing

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

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