Computational Fluid Dynamics (CFD) Simulations of Spray Drying: Linking Drying Parameters with Experimental Aerosolization Performance

Overview

Journal Pharm Res

Specialties Pharmacology
Pharmacy

Date 2020 May 23

PMID 32440940

Citations 9

Authors

P Worth Longest

Dale Farkas

Amr Hassan

Michael Hindle

Affiliations

Soon will be listed here.

Abstract

Purpose: The purpose of this study was to develop a new computational fluid dynamics (CFD)-based model of the complex transport and droplet drying kinetics within a laboratory-scale spray dryer, and relate CFD-predicted drying parameters to powder aerosolization metrics from a reference dry powder inhaler (DPI).

Methods: A CFD model of the Buchi Nano Spray Dryer B-90 was developed that captured spray dryer conditions from a previous experimental study producing excipient enhanced growth powders with L-leucine as a dispersion enhancer. The CFD model accounted for two-way heat and mass transfer coupling between the phases and turbulent flow created by acoustic streaming from the mesh nebulizer. CFD-based drying parameters were averaged across all droplets in each spray dryer case and included droplet time-averaged drying rate (κ), maximum instantaneous drying rate (κ) and precipitation window.

Results: CFD results highlighted a chaotic drying environment in which time-averaged droplet drying rates (κ) for each spray dryer case had high variability with coefficients of variation in the range of 60-70%. Maximum instantaneous droplet drying rates (κ) were discovered that were two orders of magnitude above time-averaged drying rates. Comparing CFD-predicted drying parameters with experimentally determined mass median aerodynamic diameters (MMAD) and emitted doses (ED) from a reference DPI produced strong linear correlations with coefficients of determination as high as R = 0.98.

Conclusions: For the spray dryer system and conditions considered, reducing the CFD-predicted maximum drying rate experienced by droplets improved the aerosolization performance (both MMAD and ED) when the powders were aerosolized with a reference DPI.

Citing Articles

Effects of different mesh nebulizer sources on the dispersion of powder formulations produced with a new small-particle spray dryer.

Aladwani G, Momin M, Spence B, Farkas D, Bonasera S, Hassan A Int J Pharm. 2023; 642:123138.

PMID: 37307962 PMC: 10527815. DOI: 10.1016/j.ijpharm.2023.123138.

Near Elimination of In Vitro Predicted Extrathoracic Aerosol Deposition in Children Using a Spray-Dried Antibiotic Formulation and Pediatric Air-Jet DPI.

Farkas D, Thomas M, Hassan A, Bonasera S, Hindle M, Longest W Pharm Res. 2022; 40(5):1193-1207.

PMID: 35761163 PMC: 10616820. DOI: 10.1007/s11095-022-03316-9.

Particle Engineering by Nano Spray Drying: Optimization of Process Parameters with Hydroethanolic versus Aqueous Solutions.

Almansour K, Ali R, Alheibshy F, Almutairi T, Alshammari R, Alhajj N Pharmaceutics. 2022; 14(4).

PMID: 35456634 PMC: 9031873. DOI: 10.3390/pharmaceutics14040800.

Computational Fluid Dynamics (CFD) Guided Spray Drying Recommendations for Improved Aerosol Performance of a Small-Particle Antibiotic Formulation.

Longest W, Hassan A, Farkas D, Hindle M Pharm Res. 2022; 39(2):295-316.

PMID: 35147870 PMC: 8958016. DOI: 10.1007/s11095-022-03180-7.

Integrating Elastic Tensor and PC-SAFT Modeling with Systems-Based Pharma 4.0 Simulation, to Predict Process Operations and Product Specifications of Ternary Nanocrystalline Suspensions.

Ouranidis A, Davidopoulou C, Kachrimanis K Pharmaceutics. 2021; 13(11).

PMID: 34834186 PMC: 8623873. DOI: 10.3390/pharmaceutics13111771.

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