Development and beyond: Strategy for long-term maintenance of an online laser diffraction particle size method in a spray drying manufacturing process

Medendorp, Joseph; Bric, John; Connelly, Greg; Tolton, Kelly; Warman, Martin

doi:10.1016/j.jpba.2015.04.019

Cited by 12 publications

(6 citation statements)

References 10 publications

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“…The consistency between the inline measurement obtained from the PAT and the offline release testing was verified first. As reported by Medendorp et al, the two methods, i.e., offline and inline laser diffraction, result in different dv50 estimations, but the two are linearly correlated. The inline measurement normally underestimates the large particles, resulting in a lower dv50.…”

Section: Resultsmentioning

confidence: 72%

Data-Driven Modeling of the Spray Drying Process. Process Monitoring and Prediction of the Particle Size in Pharmaceutical Production

Muñoz López,

Peeters,

Van Impe

2024

ACS Omega

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Spray drying is used in the pharmaceutical industry for particle engineering of amorphous solid dispersions (ASDs). The particle size of the spray-dried (SD) powders is one of their key attributes due to its impact on the downstream processes and the drug product's functional properties. Offline and inline laser diffraction methods can be used to estimate the product's particle size; however, the final release of these ASDs is based on offline instruments. This paper presents a novel data-driven modeling approach for predicting the particle size of SD products. The modelbased characterization of the process and the product's particle size, as a critical quality attribute, follows the quality by design principles. The resulting model can be used for online process monitoring, reducing the risks of out-of-specifications products and supporting their real-time release. A Tucker3 model is trained to capture and factorize the deterministic variability of the process. Subsequently, a partial least-squares regression model is calibrated to model the impact that variability in the input material properties, the process parameters, and the spray nozzle have on the products' particle size. This strategy has been calibrated and validated using large scale production data for two intermediate drug products under high sparsity of particle size data. Despite the challenges, high accuracy was obtained in predicting the median particle size (dv50) for release. The 99% confidence interval results in an error of maximum 2.5 μm, which is less than 10% of the allowed range of variation.

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Section: Resultsmentioning

confidence: 72%

Data-Driven Modeling of the Spray Drying Process. Process Monitoring and Prediction of the Particle Size in Pharmaceutical Production

Muñoz López,

Peeters,

Van Impe

2024

ACS Omega

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“…The Insitec system has been applied as a PAT tool for spray-drying in several studies [69]. For example, alongterm maintenance strategy with an online laser diffraction probe (Malvern Insitec) was compared to an offline method (Malvern Mastersizer) for the analysis of spray-drying [70]. This showed that spray-drying can produce reproducible particle size distributions and is effective for targeted particle engineering.…”

Section: Laser Diffractionmentioning

confidence: 99%

Process Analytical Technology for the Production of Parenteral Lipid Emulsions According to Good Manufacturing Practices

Grumbach

Czermak

2022

Processes

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The good manufacturing practices (GMP) and process analytical technology (PAT) initiatives of the US Food and Drug Administration, in conjunction with International Council for Harmonisation (ICH) quality guidelines Q8, Q9, and Q10, ensure that manufacturing processes for parenteral formulations meet the requirements of increasingly strict regulations. This involves the selection of suitable process analytics for process integration and aseptic processing. In this article, we discuss the PAT requirements for the GMP-compliant manufacturing of parenteral lipid emulsions, which can be used for clinical nutrition or for the delivery of lipophilic active ingredients. There are risks associated with the manufacturing processes, including the potential for unstable emulsions and the formation of large droplets that can induce embolisms in the patient. Parenteral emulsions are currently monitored offline using a statistical approach. Inline analytics, supplemented by measurements of zeta potential, could minimize the above risks. Laser scanning technology, ultrasound attenuation spectroscopy, and photo-optical sensors combined with image analysis may prove to be useful PAT methods. In the future, these technologies could lead to better process understanding and control, thus improving production efficiency.

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“…Even if LD has been commonly used as offline characterization technique, its implementation as PAT has been uncommon , and mainly used for dry powders . Handling of crystal suspensions, especially in an automated fashion, is the principal challenge in developing an LD system as PAT because such system requires suitable pumps, valves, dilution systems, and flow cells.…”

Section: Introductionmentioning

confidence: 99%

Automated Continuous Crystallization Platform with Real-Time Particle Size Analysis via Laser Diffraction

Pal,

Pankajakshan,

Besenhard

et al. 2024

Org. Process Res. Dev.

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The fourth industrial revolution is gaining momentum in the pharmaceutical industry. However, particulate processes and suspension handling remain big challenges for automation and the implementation of real-time particle size analysis. Moreover, the development of antisolvent crystallization processes is often limited by the associated time-intensive experimental screenings. This work demonstrates a fully automated modular crystallization platform that overcomes these bottlenecks. The system combines automated crystallization, sample preparation, and immediate crystal size analysis via online laser diffraction (LD) and provides a technology for rapidly screening crystallization process parameters and crystallizer design spaces with minimal experimental effort. During the LD measurements, to avoid multiple scattering events, crystal suspension samples are diluted automatically. Multiple software tools, i.e., LabVIEW, Python, and PharmaMV, and logic algorithms are integrated in the platform to facilitate automated control of all the sensors and equipment, enabling fully automated operation. A customized graphical user interface is provided to operate the crystallization platform automatically and to visualize the measured crystal size and the crystal size distribution of the suspension. Antisolvent crystallization of ibuprofen, with ethanol as solvent and water with Soluplus (an additive) as antisolvent, is used as a case study. The platform is demonstrated for antisolvent crystallization of small ibuprofen crystals in a confined impinging jet crystallizer, performing automated preplanned user-defined experiments with online LD analysis.

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Development and beyond: Strategy for long-term maintenance of an online laser diffraction particle size method in a spray drying manufacturing process

Cited by 12 publications

References 10 publications

Data-Driven Modeling of the Spray Drying Process. Process Monitoring and Prediction of the Particle Size in Pharmaceutical Production

Data-Driven Modeling of the Spray Drying Process. Process Monitoring and Prediction of the Particle Size in Pharmaceutical Production

Process Analytical Technology for the Production of Parenteral Lipid Emulsions According to Good Manufacturing Practices

Automated Continuous Crystallization Platform with Real-Time Particle Size Analysis via Laser Diffraction

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