AIMC Topic: Dry Powder Inhalers

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Machine learning-based prediction of aerodynamic performance in arformoterol-lactose dry powder inhaler formulations using surface roughness features.

International journal of pharmaceutics
Dry powder inhalers (DPIs) are widely used for pulmonary drug delivery, and their aerodynamic performance is highly dependent on particle surface morphology. This paper presents a machine learning-based framework to quantitatively predict DPI aerodyn...

Factors Influencing the Dispersibility of Glycopyrronium Bromide and Indacaterol Maleate - Combined In Vitro and In Silico Study.

AAPS PharmSciTech
The development of dry powder inhalers (DPIs) for pulmonary drug delivery is complex, requiring optimization of variable factors to ensure effective lung deposition. This study investigates the factors influencing the dispersibility of glycopyrronium...

Development and application of an AI-empowered acoustic monitoring system for misuse detection in dry powder inhalers.

International journal of pharmaceutics
Misuse and poor inhalation techniques remain persistent issues in pulmonary drug delivery via dry powder inhalation. While acoustic-based monitoring has been a feasible strategy, existing approaches often depend on smartphones for signal collection, ...

Recent advances in dry powder inhalation formulations prepared by co-spray drying technology: a comprehensive review.

International journal of pharmaceutics
Co-spray drying technology represents an increasingly important approach in preparing dry powder inhalation (DPI) formulations. Compared to conventional spray drying, co-spray drying typically yields particles characterized by improved aerosol perfor...

In vitro and in vivo performance modelling and optimisation of different dry powder inhalers: A complementary study of neural networks, genetic algorithms and decision trees.

International journal of clinical practice
INTRODUCTION: Aerosol delivery from DPIs could be affected by different factors. This study aimed to evaluate and predict the effects of different factors on drug delivery from DPIs.

Development of an Inline Dry Powder Inhaler That Requires Low Air Volume.

Journal of aerosol medicine and pulmonary drug delivery
BACKGROUND: Inline dry powder inhalers (DPIs) are actuated by an external air source and have distinct advantages for delivering aerosols to infants and children, and to individuals with compromised lung function or who require ventilator support. Ho...

Predicting the Fine Particle Fraction of Dry Powder Inhalers Using Artificial Neural Networks.

Journal of pharmaceutical sciences
Dry powder inhalers are increasingly popular for delivering drugs to the lungs for the treatment of respiratory diseases, but are complex products with multivariate performance determinants. Heuristic product development guided by in vitro aerosol pe...

Predictive machine learning algorithm for COPD exacerbations using a digital inhaler with integrated sensors.

BMJ open respiratory research
PURPOSE: By using data obtained with digital inhalers, machine learning models have the potential to detect early signs of deterioration and predict impending exacerbations of chronic obstructive pulmonary disease (COPD) for individual patients. This...