Abstract
The objectives of this study were to expand and implement a Computational Fluid Dynamics (CFD)-Dissolution, Absorption and Clearance (DAC)-Pharmacokinetics (PK) multi-physics modeling framework for simulating the transport of suspension-based nasal corticosteroid sprays. The mean CFD-predicted peak plasma concentration (Cmax) and area under the curve (AUC) of the plasma concentration-time profile, based on three representative nasal airway models (capturing low, medium and high posterior spray deposition), were within one standard deviation of available in vivo PK data for a representative corticosteroid drug (triamcinolone acetonide). The relative differences in mean Cmax between predictions and in vivo data for low dose (110 µg) and high dose (220 µg) cases were 27.8% and 10.1%, respectively. The models confirmed the dose-dependent dissolution-limited behavior of nasally delivered triamcinolone acetonide observed in available in vivo data. The total uptake from the nasal cavity decreased from 68.3% to 51.3% for the medium deposition model as dose was increased from 110 to 220 µg due to concentration-limited dissolution. The modeling framework is envisioned to facilitate faster development and testing of generic locally acting suspension nasal spray products due to its ability to predict the impact of differences in spray characteristics and patient use parameters on systemic PK.
Keywords
Computational fluid dynamics (CFD)
Dissolution
Mucociliary clearance
Nasal spray
Pharmacokinetics modeling
Triamcinolone acetonide
MeSH 主题词
Humans
Triamcinolone Acetonide/pharmacokinetics,administration & dosage
Nasal Sprays
Suspensions
Models, Biological
Administration, Intranasal
Adult
Hydrodynamics
Computer Simulation
Area Under Curve
Solubility
Male
化学物质
Triamcinolone Acetonide
Nasal Sprays
Suspensions
作者与单位
共 9 位作者,点击展开单位 / ORCID
Dutta Rabijit
Department of Mechanical and Nuclear Engineering, Virginia Commonwealth University, Richmond, VA, USA.
V Kolanjiyil Arun
Department of Mechanical and Nuclear Engineering, Virginia Commonwealth University, Richmond, VA, USA.
Walenga Ross L
Division of Quantitative Methods and Modeling, Office of Research and Standards, Office of Generic Drugs, Center for Drug Evaluation and Research, U.S. Food and Drug Administration, Silver Spring, MD, USA.
Chopski Steven G
Division of Quantitative Methods and Modeling, Office of Research and Standards, Office of Generic Drugs, Center for Drug Evaluation and Research, U.S. Food and Drug Administration, Silver Spring, MD, USA.
Kaviratna Anubhav
Division of Therapeutic Performance I, Office of Research and Standards, Office of Generic Drugs, Center for Drug Evaluation and Research, U.S. Food and Drug Administration, Silver Spring, MD, USA.
Mohan Abhinav R
Division of Therapeutic Performance I, Office of Research and Standards, Office of Generic Drugs, Center for Drug Evaluation and Research, U.S. Food and Drug Administration, Silver Spring, MD, USA.
Newman Bryan
Division of Therapeutic Performance I, Office of Research and Standards, Office of Generic Drugs, Center for Drug Evaluation and Research, U.S. Food and Drug Administration, Silver Spring, MD, USA.
Golshahi Laleh
Department of Mechanical and Nuclear Engineering, Virginia Commonwealth University, Richmond, VA, USA.
Longest Worth
Department of Mechanical and Nuclear Engineering, Virginia Commonwealth University, Richmond, VA, USA; Department of Pharmaceutics, Virginia Commonwealth University, Richmond, VA, USA. Electronic address:
[email protected].