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

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Abstract

Purpose

The objective of this study was to implement computational fluid dynamics (CFD) simulations and aerosol characterization experiments to determine best-case spray drying conditions of a tobramycin excipient enhanced growth (Tobi-EEG) formulation for use in a pediatric air-jet dry powder inhaler (DPI).

Methods

An iterative approach was implemented in which sets of spray drying conditions were explored using CFD simulations followed by lead candidate selection, powder production and in vitro aerosol testing. CFD simulations of a small-particle spray dryer were performed to capture droplet drying parameters and surface-averaged temperature and relative humidity (RH) conditions in the powder collection region. In vitro aerosol testing was performed for the selected powders using the pediatric air-jet DPI, cascade impaction, and aerosol transport through a pediatric mouth-throat (MT) model to a tracheal filter.

Results

Based on comparisons of CFD simulations and in vitro powder performance, recommended drying conditions for small-particle powders with electrostatic collection include: (i) reducing the CFD-predicted drying parameters of κavg and κmax to values below 3 μm2/ms and 114 μm2/ms, respectively; (ii) maintaining the Collector Surface RH within an elevated range, which for the Tobi-EEG formulation with l-leucine was 20–30 %RH; and (iii) ensuring that particles reaching the collector were fully dried, based on a mass fraction of solute CFD parameter.

Conclusions

Based on the newly recommended spray dryer conditions for small particle aerosols, delivery performance of the lead Tobi-EEG formulation was improved resulting in >60% of the DPI loaded dose passing through the pediatric MT model.

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Abbreviations

3D:

Three dimensional

AS:

Albuterol sulfate

CFD:

Computational fluid dynamics

CoV:

Coefficient of variation

DPI:

Dry powder inhaler

DVS:

Dynamic vapor sorption

ED:

Emitted dose

EEG:

Excipient enhanced growth

FPF:

Fine particle fraction

HP:

High performance

HPLC:

High performance liquid chromatography

ISR:

Time integral of saturation ratio

LC-MS:

Liquid chromatography-mass spectrometry

LPM:

Liters per minute

LRN:

Low Reynolds number

MMAD:

Mass median aerodynamic diameter

MN:

Mannitol

MP:

Mouthpiece

MT:

Mouth-throat

NGI:

Next Generation Impactor

ODE:

Ordinary differential equation

PDE:

Partial differential equation

RH:

Relative humidity

RMM:

Rapid mixing model

SD:

Standard deviation

SR:

Saturation ratio

T:

Temperature

Tobi:

Tobramycin

USP:

United States Pharmacopeia

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ACKNOWLEDGMENTS AND DISCLOSURES

Research reported in this publication was supported by the Eunice Kennedy Shriver National Institute of Child Health & Human Development of the National Institutes of Health under Award Number R01HD087339 and by the National Heart, Lung and Blood Institute of the National Institutes of Health under Award Number R01HL139673. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. Virginia Commonwealth University is currently pursuing patent protection of devices and methods described in this study, which if licensed and commercialized, may provide a future financial interest to the authors.

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Authors and Affiliations

  1. Department of Mechanical and Nuclear Engineering, Virginia Commonwealth University, 401 West Main Street, P.O. Box 843015, Richmond, Virginia, 23284-3015, USA

    Worth Longest & Dale Farkas

  2. Department of Pharmaceutics, Virginia Commonwealth University, 410 North 12th Street, P.O. Box 980533, Richmond, Virginia, 23298-0533, USA

    Worth Longest, Amr Hassan & Michael Hindle

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  1. Worth Longest
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Longest, W., Hassan, A., Farkas, D. et al. Computational Fluid Dynamics (CFD) Guided Spray Drying Recommendations for Improved Aerosol Performance of a Small-Particle Antibiotic Formulation. Pharm Res 39, 295–316 (2022). https://doi.org/10.1007/s11095-022-03180-7

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