Evaluation of Preliminary Bronchodilation Effect on Aerosol Delivery from a Dry Powder Inhaler for Patients with Chronic Obstructive Pulmonary Disease with Suboptimal Peak Inspiratory Flow Rate

Abstract

Background

Suboptimal peak inspiratory flow rates (PIFR) are common in patients with chronic obstructive pulmonary disease (COPD), hindering effective medication dispersion and aerosol delivery. This study aimed to assess whether administering a preliminary bronchodilator dose via a pressurized metered-dose inhaler (pMDI) improves aerosol drug delivery via dry powder inhaler (DPI) in patients with COPD with suboptimal PIFR (< 60 L/min), compared with those with optimal PIFR (≥ 60 L/min).

Methods

Overall, 24 patients with COPD were evaluated. PIFR was measured using the In-Check Dial^© G16, dividing patients into optimal and suboptimal groups. All patients received a 200 µg dose of salbutamol via Diskus^® DPI. Patients with COPD with suboptimal PIFR received two puffs (100 µg each) preceded by a preliminary salbutamol dose administered via pMDI^®. Urine salbutamol levels (USAL30) and salbutamol that was eluted from filters (SALF) were measured after 30 min to assess lung deposition through high-performance liquid chromatography (HPLC).

Results

Patients with COPD with suboptimal PIFR without a preliminary dose had significantly lower USAL30 than the optimal group (4.99% versus 6.18%, p = 0.013). A preliminary dose improved USAL30 in the suboptimal group but did not reach statistical significance (5.45% versus 4.99%, p = 0.071).

Conclusions

A significant difference in aerosol drug delivery was observed between optimal and suboptimal groups without a preliminary dose, suggesting that inhaler selection in patients with COPD may need to be individualized on the basis of inspiratory flow capability. Administering a preliminary dose of pMDI^® before using a DPI minimally affects the suboptimal inhalation through DPI.

Key Points

Patients with COPD with suboptimal PIFR had significantly lower lung deposition of salbutamol compared with patients with COPD with optimal PIFR.

Administering a preliminary bronchodilator dose using a pMDI improved salbutamol deposition in patients with COPD with suboptimal PIFR.

Ex vivo testing showed no significant differences in salbutamol recovery from the filters between the groups.

Individualizing inhaler selection on the basis of the patient’s peak inspiratory flow rate is crucial for effective aerosol drug delivery.

The study utilized a novel approach of combining DPI and pMDI to compensate for suboptimal inhalation through DPI.

Introduction

Recently, the use of dry powder inhalers (DPIs) for treating chronic respiratory diseases has expanded significantly. DPIs have numerous advantages over pressurized metered-dosage inhalers (pMDIs), which could explain this [1]. Unlike pMDI, which needs coordination, DPIs are breath-actuated and use the patient’s respiration to deliver the medication deep into the lungs [2]. DPIs are safer than pMDIs owing to their lack of propellants, low risk of chemical contamination, and lack of a chilly sensation caused by inhaling the aerosol [3, 4]. DPIs, however, come in a variety of dosage forms with different inhalation techniques [5]. An uncontrolled patient’s condition can arise from improper use of DPIs [1]. Moreover, DPIs vary in their internal resistance to airflow, from low to high [6]. Patients must therefore inhale deeply and firmly to receive the recommended dose from the DPI [6]. This type of inhalation, which has a high initial acceleration rate, is effective for releasing aerosol particles [7].

Most patients can typically reach an inhaling flow of 30 L/min throughout a DPI, which in certain DPIs is adequate to deliver a portion of the dose [8]. Yet, DPIs need a peak inspiratory flow rate (PIFR) to conquer the device’s unique internal resistance and disperse the medication powder properly. The capacity to sustain an optimal PIFR is a significant necessity for effective DPI use [9]. Each inhaler device must have a certain PIFR to prevent early deposition of the effective dose and enable deep medication delivery into the lungs. It has been recently suggested that when selecting an inhaler device on a prescription, the patient’s capacity to produce a sufficient PIFR should be taken into account [6, 10]. It was thought that the key to a successful inhalation therapy was optimal PIFR. Depending on the inhaler-device resistance, there are notable differences [11–13]. As a result, depending on whether their PIFR matches or deviates from the matching inhaler-device resistance, patients are either optimal or suboptimal for each inhaler device [14]. The phrase “inhaler discordance” (PIFR mismatch with prescribed inhaler devices) was first used by Ghosh and collaborators [14]. The appropriateness of the PIFR range of 30–60 L/min remains controversial. Suboptimal PIFR, which is below the device’s minimal threshold, may result in insufficient drug disaggregation and distal airway drug deposition [14].

The majority of patients with COPD are elderly, and several obstacles may make it difficult for them to use an inhaler device as effectively as possible. First, muscular atrophy, lung hyperinflation, and hypoxemia all contribute to weak respiratory muscles, which leads to poor inspiratory capacity (IC) and inadequate PIFR [15, 16]. Furthermore, a significant number of patients with COPD have comorbidities, which impair hand–lung coordination and frequently result in misinhalation [17–21]. However, pharmacopeia-recommended dose emission tests use a 4-L inhalation volume with an inhalation flow equal to a pressure drop of 4 kPa via the inhaler [22]. However, the maximal inhaling volume for individuals with COPD is about 2 L [23]. As a result, these patients are unable to achieve the required pressure drop (4 kPa) for dose withdrawal from the inhaler, as recommended by the pharmacopeia. This can cause variations in the emitted dose, which can lead to adverse effects or unpredictable clinical responses [23].

The relationship between PIFR and aerosol delivery is multifaceted and critically important for optimizing inhalation therapy. Studies have shown that the emitted dose and fine particle mass of DPIs increase with higher PIFRs, indicating that a strong initial inhalation effort is critical for effective drug delivery [24]. However, achieving an optimal PIFR can be challenging, especially in populations with compromised respiratory function, such as children and patients with COPD. For instance, many young children may not generate sufficient PIFR to effectively use high-resistance DPIs [25]. Furthermore, observational studies using handheld inspiratory flow meters have revealed that a substantial proportion of stable outpatients with COPD fail to achieve the optimal PIFR of at least 60 L/min required for effective DPI use, highlighting the need for tailored inhaler selection based on individual PIFR capabilities [26].

However, a number of scintigraphic investigations have determined that the depth of pulmonary aerosol penetration in numerous respiratory disorders is directly correlated with forced expiratory volume in 1 s (FEV₁) [27–29]. Subsequently, a concurrent enhancement of the depth of respiratory aerosol penetration was thought to be possible if bronchodilators were used to increase FEV₁ [30]. None of these studies emphasized the effective lung dose in relationship with FEV₁, although they all offered an index of the aerosol distribution inside the lung. Moreover, measured PIFRs against different inhaler resistance ranges were found to be positively correlated with FEV₁ and forced vital capacity (FVC) among patients with COPD using different DPIs [31].

Therefore, the hypothesis of the current study was that a preliminary bronchodilator dose may improve aerosol penetration and effective lung dose in patients with COPD with suboptimal PIFR [32, 33]. Moreover, there is not enough information to determine how aerosol drug delivery is affected by suboptimal PIFR in patients with COPD and whether suboptimal PIFR is modifiable or not. Therefore, this study aimed to compare aerosol drug delivery in patients with COPD with optimal versus suboptimal PIFR and to assess the impact of a preliminary bronchodilator dose by pMDI on aerosol drug delivery through DPI in patients with COPD with suboptimal PIFR.

Materials and Methods

The study was conducted at the Chest Department at the Beni-Suef University Hospital after the study protocol was approved by the Research Ethics Committee of the Faculty of Medicine, Beni-Suef University (FMBSUREC/07042024/Hassan). It was also approved by the Research Ethics Committee of the Faculty of Pharmacy, Beni-Suef University (REC-H-PhBSU-22018) and adhered to the Declaration of Helsinki. Participants provided written informed consent. Moreover, participation in the study was declared to be voluntary, and participants were advised that they could withdraw at any time during the study. PIFR was measured using In-Check Dial^® G16 (Clement Clarke International Limited, UK), which is a handheld device with an adjustable dial that simulates the resistance of various inhaler devices. It measures flows from 15 to 120 L/min with an accuracy of ± 10% or 10 L/min, whichever is larger [34]. The technique used is a urinary pharmacokinetic technique based on salbutamol’s 30-min lag time to assess pulmonary drug delivery. It was initially created using an assay that could detect salbutamol amounts in urine with sufficient sensitivity [35]. None of the patients included in this study were prescribed diuretics to avoid confounding urinary drug excretion results. The effective lung dose can be estimated from the drug concentration of a urine sample collected 30 min after inhalation [36]. A preliminary bronchodilator dose of salbutamol was tested through pMDI^®, which is supposed to decrease airway resistance within 5–15 min, with a peak effect typically observed within 30 min [37].

Study Design

This study is a prospective, randomized, case–control study following The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines.

Inclusion and Exclusion Criteria

The inclusion criteria were the following: patients diagnosed according to the 2022 GOLD Guidelines [38], either men or women, with varying degrees of illness severity. Patients were admitted for an acute exacerbation and then participated in the study before being discharged from the hospital. Patients had to have no prior salbutamol contraindications.

Exclusion criteria comprised the presence of a current exacerbation, having any mental disease or disturbed conscious level affecting the ability to communicate, being unable to inhale forcefully through In-Check Dial, or being unable to perform the pulmonary function tests; a recent history of hemoptysis, pneumothorax, unstable angina pectoris, or myocardial infarction; thoracic, abdominal, or cerebral aneurysms; eye surgery; or abdominal or thoracic surgical procedures [39]. Patients had to have stable renal function and were ineligible to participate if they had severe renal impairment, defined as creatinine clearance or an estimated glomerular filtration rate of < 20 mL/min.

Data Collection

The active study phase took a maximum of 4 days, during which patients received salbutamol study doses (200 μg salbutamol each). Participation in the study began after a washout period of 48 h following the last salbutamol dose. This allowed the body to excrete any salbutamol administered before the study. To minimize interference between study doses and the patient’s regular scheduled doses, ipratropium bromide (Atrovent^® inhalation solution containing a nominal dose of 25 μg/mL, Boehringer Ingelheim) was used in place of the patient’s regular scheduled salbutamol doses during the study period. In addition, all other bronchodilators, including long-acting β₂-agonists (LABAs) and long-acting muscarinic antagonists (LAMAs), were withheld during the washout period before participation to avoid confounding effects on PIFR or urinary drug measurements. The current study’s high-performance liquid chromatography (HPLC) analysis method distinguishes these two drugs [40].

Patient demographics, history, and clinical data were obtained [41]. Interindividual variations in urine amount and concentration due to various dietary and liquid intakes were considered in the method of calculating the total excreted salbutamol amount.

All PIFR measurements were conducted when patients were clinically stable following their COPD exacerbation and were not in the acute phase. This allowed for the values to accurately reflect the baseline inspiratory effort as opposed to being affected by any upheaval in respiratory status.

Using the In-Check^™ Dial, which was adjusted to simulate the internal resistance of the Diskus inhaler, in accordance with the manufacturer’s recommendations, the patients were first divided into groups that were either optimal or suboptimal for both inhaler devices (≥ 60 L/min PIFR for the optimal group and < 60 L/min for the suboptimal group). Ventolin Diskus^® DPI (GSK, Evreux, France) is a multi-unit dose plastic inhaler with a low-medium resistance that includes a foil strip of 60 blisters. The blisters contain 240 μg micronized salbutamol sulfate (equal to 200 μg salbutamol base) and lactose as an excipient in the form of inhalation powder. Before inhaling using DPIs, subjects were educated on how to utilize an inhaler device. They were instructed to breathe out softly before the mouthpiece was securely put between their lips, and they inhaled through their mouth to their maximum lung capacity as strongly, powerfully, and deeply as possible and rapidly at early inhalation. The DPI was then removed from their mouth, and they held their breath for 10 s before slowly breathing out. After that, the patients were ready to receive the study dose and were instructed to perform a mouth rinse with water to minimize oropharyngeal deposition. They were advised to drink plenty of water and urinate for 15 min beforehand.

On the first day of the study, patients with optimal and suboptimal PIFR were randomly assigned to receive study doses of 200 µg salbutamol inhaled by Ventolin Diskus^® DPI. They were asked to provide a urine sample 30 min post-inhalation, to obtain urinary salbutamol excreted 30 min post-study dose (USAL30).

On the alternative day of the study, the inhaled dose of salbutamol was provided only to patients with suboptimal PIFR using the same aerosol generator, preceding with two puffs (100 µg each) of salbutamol delivered by a Ventolin pMDI^® (GSK, Evreux, France) with no resistance before the administration of Ventolin Diskus^® DPI, and USAL30 post DPI dose was obtained. Figure 1 illustrates the sequence of procedures and sample collections throughout the study.

Fig. 1.

Timeline schematic illustrating the sequence of procedures and sample collections throughout the study

The volumes of the urine samples were quantified, and aliquots were frozen at − 14 °C in the freezer and kept for the analysis of salbutamol using solid-phase extraction (SPE) and an HPLC assay using an Oasis mixed-mode cation exchange (MCX) cartridge (Waters Corporation, Milford, MA, USA).

Ex Vivo Protocol

On the next day, following the completion of the in vivo study, all patients received study doses as previously described, but this time, a filter (Filta-Guard, Intersurgical, Wokingham, UK) was placed between the patient’s mouth and the Diskus DPI to prevent the participants from inhaling the medication. In the suboptimal group with a preliminary dose, the patient received pMDI puffs before inserting filters. Every participant received the same study dose, with new filters for each administration. Before being rinsed, the salbutamol that had become entrained on the filter was desorbed using sonication with 25 mL of 30% acetonitrile. The sample was then measured through the high-performance liquid chromatography method to get the salbutamol amount on ex vivo filters (SALF).

Solid-Phase Extraction

Urine samples were prepared by acidifying 2 mL of 0.5 N HCl for every 10 mL of urine 30 min post-dose. To prepare the cartridge for solid-phase extraction, 6 mL of methanol was used for conditioning. After that, 6 mL of water was added for equilibration, and 10 mL of the prepared urine sample was loaded. Multiple washing was then performed to ensure that no urine remained in the extract. Subsequently, 10 mL of 5% methanol in 0.1 N HCl, 10 mL of methanol, and 6 mL of 2.5% triethanolamine (TEA) in methanol were used as washes , and 10 mL of 5% ammonium hydroxide in methanol was the elution step [33, 42].

High-Performance Liquid Chromatography (HPLC) Analysis

Urine Samples

An HPLC (Agilent 1260 Infinity, Germany) instrument equipped with Agilent 1260 Infinity quaternary pump VL (G1311C), Agilent 1260 Infinity thermo-stated column compartment (G1316A), Agilent 1260 Infinity Diode array detector VL (G1315D), and Agilent 1260 Infinity standard auto-sampler (G1329B) at 230 nm with injection volume of 20 μL was used. The mobile phase used was (90:10 v/v) a mixture of acetonitrile and water (containing 0.1% glacial acetic acid and 0.1% TEA) in isocratic mode. It was pumped through the column at a flow of 1 mL/min maintained at 25 °C. Separation and quantitation were performed on ZORBAX Eclipse plus C18 ODS1 column 250 mm × 4.6 mm (length × internal diameter), 5 μm (particle size) (Agilent), guarded by C18 (4 mm × 3 mm) Agilent ODS guard column. The lower limit of quantification (LOQ) was 1.00 μg/mL, and the limit of detection (LOD) was 0.36 μg/mL. Calibration solutions ranging from 10 to 100 μg/mL were used in the construction of a calibration curve to interpret sample concentrations [32, 43, 44].

The total amount of urine post 30 min of inhalation from each patient was initially recorded. After the HPLC method, the salbutamol concentration of each sample measured was multiplied by the total volume of urine sample resulting in the total excreted salbutamol amount of each patient regardless of urinary concentration.

Aqueous Samples of Ex Vivo Filters

The system was composed of an ODS 5 µm (4.6 mm × 250 mm, ZORBAX Eclipse) C-18 high-performance liquid chromatography column. The mobile phase contained (90:10, v/v) a mixture of acetonitrile and water (containing 0.1% glacial acetic acid and 0.1% TEA) in isocratic mode. It was pumped through the columns at a flow of 1 mL/min maintained at 25 °C, and photodiode array detection was set at 225 nm. The lower limit of detection was 0.35 µg/mL, and the lower limit of quantification was 2.55 µg/mL. Calibration solutions, which ranged from 10 to 100 µg/mL (w/v), were used in the construction of a calibration curve to interpret sample concentrations.

Statistical Analysis

Descriptive analysis was performed where all data were expressed as mean ± standard deviation (SD). Data normality was tested through the Shapiro–Wilk test. Non-parametric tests were applied on the basis of the results of the normality test. A Mann–Whitney U test was used to compare the difference in continuous variables (urinary salbutamol excretion 30 min post-inhalation and emitted dose) between optimal and suboptimal groups. A Wilcoxon signed-rank test was used to determine the difference in these continuous variables between suboptimal groups with and without preliminary bronchodilator dose. Significance was defined as p < 0.05, and all tests were performed using SPSS version 17.0 (SPSS, Chicago, USA).

Results

In Vivo

Overall, 24 patients with COPD completed the study and were divided into two groups (optimal and suboptimal), each containing 12 patients (n = 12), their demographic and clinical data are summarized in Table 1. The results in Table 1 show that there was a significant difference (p < 0.05) between the optimal and suboptimal group in weight (84.08 ± 13.10 versus 69.91 ± 10.62 kg, p = 0.012) and body mass index (BMI, 28.93 ± 3.328 versus 25.05 ± 2.79 kg/m², p = 0.012). PIFR exhibited a significant difference between the two cohorts as well (71.66 ± 6.15 versus 41.25 ± 9.79 L/min, p = 0.000). Figure 2 shows the differences in demographics between optimal and suboptimal groups ((A) weight; (B) BMI). The percentages of FEV₁ predicted pre- and post-administration of the Diskus inhaler among the three tested groups are presented in Table 2.

Table 1.

Demographic data and baseline clinical parameters for all patients (n = 24) and each group (n = 12) as mean ± SD or n (%)

Parameter	Total patients n = 24	Optimal	Suboptimal	P value
Sex
Male	16 (66.6%)	9 (75%)	8 (66.6%)	0.653
Female	8 (33.3%)	3 (25%)	4 (33.3%)
Smoking:
Non-smoker	13 (54.16%)	5 (41.6%)	8 (66.6%)
Smoker	6 (25%)	3 (25%)	3 (25%)	0.288
Ex-smoker	5 (20.8%)	4 (33.3%)	1 (8.3%)
GOLD group:
C group	10 (41.6%)	6 (50%)	4 (33.3%)	0.408
D group	14 (58.3%)	6 (50%)	8 (66.6%)
GOLD stage:
Stage II	8 (33.3%)	5 (41.6%)	3 (25%)
Stage III	6 (25%)	3 (25%)	3 (25%)	0.638
Stage IV	10 (41.6%)	4 (33.3%)	6 (50%)
Age, years	64.3 ± 7.39	63.583 ± 5.567	65.083 ± 9.059	0.418
Weight, kg	77 ± 13.72	84.083 ± 13.104	69.916 ± 10.621	0.012*
Height, cm	168.62 ± 9.91	170.25 ± 9.2059	167 ± 10.719	0.224
BMI, kg/m2	26.9 ± 3.59	28.930 ± 3.3287	25.054 ± 2.791	0.012*
PIFR, L/min	56.45 ± 17.47	71.666 ± 6.154	41.25 ± 9.799	0.000*

BMI, body mass index; PIFR, peak inspiratory flow rate from flow meter; GOLD, Global Initiative for Obstructive Lung Disease

*Significant at the 0.05 level

Fig. 2.

Differences in demographics between optimal and suboptimal groups (Gp.); A weight; B BMI. Normal BMI: ≥ 18.5 to < 25 kg/m²; average normal weight for patients: 70 kg

Table 2.

Percentage of FEV₁ predicted pre- and post-Diskus inhaler between optimal and suboptimal groups with/without the preliminary bronchodilator dose

Parameter	Optimal (n = 12)	Suboptimal without preliminary dose (n = 12)	P value	Optimal (n = 12)	Suboptimal with preliminary dose (n = 12)	P value	Suboptimal without preliminary dose (n = 12)	Suboptimal with preliminary dose (n = 12)	P value
Pre-FEV1 % pred.	45.5 ± 20.2	36.6 ± 16.4	0.418	45.5 ± 20.2	36.7 ± 19.4	0.370	36.6 ± 16.4	36.7 ± 19.4	0.534
Post-FEV1 % pred.	54.1 ± 23.2	45.3 ± 20.4	0.386	54.1 ± 23.2	48.2 ± 23.2	0.603	45.3 ± 20.4	48.2 ± 23.2	0.138

Pre-FEV₁ % pred., pre-Diskus inhaler FEV₁ % predicted; Post-FEV₁ % pred., post-Diskus inhaler FEV₁ % predicted

*Significant at the 0.05 level

There was a significant difference between the three tested groups for the USAL30 percentage of nominal dose (p = 0.032). The mean ± SD USAL30 percentage of the nominal dose after inhaling the study doses is presented in Table 3. Further statistical analysis showed that there was a significant difference between the optimal and suboptimal group without a preliminary Ventolin pMDI^® dose (6.18% ± 1.74 versus 4.99% ± 1.66, p = 0.013). Providing a preliminary dose of bronchodilator via pMDI^® before using Diskus^® improved USAL30 in the suboptimal group when compared with the suboptimal group without a preliminary dose, though this did not reach statistical significance (5.45% ± 1.44 (with preliminary dose) versus 4.99% ± 1.66 (without preliminary dose), p = 0.071). Moreover, no significant difference was found between the optimal group and suboptimal group with preliminary Ventolin pMDI^® dose (6.18% ± 1.74 versus 5.45% ± 1.44, p = 0.119). A weak positive correlation was observed between patients’ PIFR and the percentage of the nominal dose of salbutamol at USAL30 (Fig. 3).

Table 3.

Percentage of nominal dose of SALF and USAL30 between optimal and suboptimal groups with/without the preliminary bronchodilator dose

Group	Optimal group (n = 12)	Suboptimal group without preliminary dose (n = 12)	P value	Suboptimal group with preliminary dose (n = 12)	P value
USAL30, mean ± SD dose (%)	6.18 ± 1.74	4.99 ± 1.66	0.013*	5.45 ± 1.44	0.119
USAL30 95% confidence interval	Lower bound: 5.07 Upper bound: 7.28	Lower bound: 3.93 Upper bound: 6.05		Lower bound: 4.54 Upper bound: 6.37
SALF, mean ± SD dose (%)	77.20 ± 14.10	70.16 ± 23.41	0.356	74.77 ± 17.76	0.603
SALF 95% confidence interval	Lower bound: 68.24 Upper bound: 86.16	Lower bound: 55.28 Upper bound: 85.04		Lower bound: 63.48 Upper bound: 86.06

USAL30, urinary salbutamol 30 min post-study dose; SALF, salbutamol collected on the filter

*Significant at the 0.05 level

Fig. 3.

Correlation between patients’ PIFR and the percentage of nominal dose of salbutamol at USAL30

Ex Vivo

The mean ± SD SALF percentage of the nominal dose after inhaling the study doses is illustrated in Table 3. There was no significant difference between the three tested groups (p = 0.573), with an incremental increase associated with the use of a preliminary Ventolin pMDI^® dose over not using it in patients with suboptimal PIFR (74.77 ± 17.76 versus 70.16 ± 23.41, p = 0.239). Figure 4 shows the correlation between patients’ PIFR and the percentage of the nominal dose after inhaling the study doses of SALF.

Fig. 4.

Correlation between patients’ PIFR and the percentage of nominal dose of salbutamol at SALF

Discussion

In the current study, the impact of suboptimal PIFR on aerosol drug delivery was assessed using medium-resistant DPI. The aerodynamic properties of the aerosolized drug, the type of pulmonary disease, the type of the aerosol-generating system, and the inhalation pattern (e.g., fully exhaling before dose inhalation, and the breath-holding time following dose inhalation) are some of the factors that can affect the pulmonary deposition of inhaled aerosol and, in turn, affect the aerosol drug delivery [45, 46]. All of these variables were controlled in this study by employing the same aerosolized drug, with the same disease, giving the patients instructions on the best inhaler technique, complete exhalation before dosage inhalation, and an adequate breath-holding period following dose inhalation. The only variables examined were the PIFR during dose inhalation (optimal/suboptimal) and the added effect of preliminary bronchodilation.

This investigation revealed a significant relationship between suboptimal PIFR and impaired bronchodilator delivery in individuals diagnosed with COPD, which may negatively impact lung function and symptom control. This aligns with prior studies that have demonstrated a direct influence of PIFR on the efficacy of drug administration for DPIs in a proportional manner [47, 48]. Elevated PIFR values were observed to be associated with potentially improved health outcomes. Consequently, it is essential to guarantee that patients with COPD attain a sufficient PIFR to facilitate optimal medication delivery and deposition within the lower respiratory system.

The findings indicated no significant differences in gender distribution between the optimal and suboptimal groups. In contrast to earlier research, female sex was consistently linked to reduced PIFR in COPD [48]. Various demographic factors have been correlated with PIFRs, with advancing age [3–8] and female sex [49–52] being the primary characteristics consistently associated with diminished airflow (PIFR). Research demonstrates that female patients with COPD often report a greater symptom burden compared with male patients, despite exhibiting comparable levels of lung function deterioration. For example, female individuals tend to experience more pronounced dyspnea and fatigue, which are not always directly related to objective indicators of lung function such as FEV₁ [53, 54]. This implies that symptoms may not consistently represent the extent of lung function impairment, particularly among female individuals.

In a similar vein, no significant difference in smoking status was identified, indicating that the ratios of smokers, former smokers, and non-smokers were analogous across the two populations. The most plausible interpretation of this observation is that a substantial proportion of the participants were heavy smokers, of advanced age, and had engaged in smoking for prolonged periods. Furthermore, those individuals who had ceased smoking had already experienced significant health declines, with the majority having quit only a few months prior, while the non-smoking participants predominantly comprised female individuals, resulting in a diminished sample size and, hence, limited statistical power. Numerous studies have indicated that the mean daily cigarette consumption and the median duration of smoking were between 1 and 3 years, which correlated with a decline in pulmonary function. Another investigation demonstrated that the cessation of smoking mitigated the rate of decline in lung function and noted that the influence of the randomization group on lung function improvement in the first year could be partially attributed to variations in the timing of smoking cessation and the baseline smoking quantity [55].

There was no significant difference in the distribution between the GOLD C and D groups, indicating that all subjects had essentially identical illness severity. When assessing the GOLD stage, no significant difference was seen across groups. The majority of both groups were assigned to stage 2 or 3, with no significant difference in distribution between them. This revealed that the suboptimal group’s decreased lung function might not be simply due to more severe illness. According to earlier research, various factors, not simply severity, contributed to suboptimal PIFR [48, 50, 56].

The optimal and suboptimal groups did not differ significantly in age. Both groups had identical mean ages, implying that age alone may not explain the observed variations in lung function, consistent with previous research [47, 48, 57]. This demonstrated that patients of various ages struggle to achieve enough inspiratory flow due to weak respiratory muscles and/or the existence of intrinsic positive end-expiratory pressure (PEEP) [57]. The association between age and poor PIFR was not as strong as earlier research had revealed [49, 50, 52, 56, 58–60]. The current study’s small age range may help to explain this difference.

The suboptimal cohort exhibited a markedly lower average weight and BMI than the optimal cohort, indicating that body weight and BMI may influence the reduced pulmonary function in the suboptimal group. A reduction in weight alongside a lower BMI may lead to diminished strength of respiratory muscles and compromised pulmonary mechanics, resulting in suboptimal lung function. Males, in particular, are more vulnerable to this phenomenon owing to a central pattern of adipose distribution that appears to correlate with age, placing them at a heightened risk before reaching 60 years of age [61, 62]. Lower BMI and low weight significantly impact the progression of COPD, as evidenced by multiple studies. Individuals with low BMI (< 18.5 kg/m²) exhibit a higher incidence of COPD development, with rates reaching 20.1% among heavy smokers, compared with 3.4–12.4% in higher BMI groups [63]. Furthermore, underweight patients demonstrate poorer lung function, as indicated by lower FEV₁ and increased frequency of exacerbations, with a hazard ratio of 1.70 for all-cause mortality in those experiencing a BMI decrease [64]. Specifically, those with suboptimal PIFR are at an elevated risk for exacerbations, which may be exacerbated by low BMI, as these patients often struggle with effective medication inhalation [65]. Contrary to earlier research, a notable distinction in weight or BMI was observed between the two cohorts [48, 49, 52, 56, 58]. This may be due to normal spirometric outcomes, or it could signify a restrictive mechanism in cases of mild obesity accompanied by a compensatory elevation in inspiratory capacity (IC) [66].

Moreover, the PIFR was significantly diminished in the suboptimal cohort compared with the optimal cohort. This finding aligns with expectations, as PIFR is intrinsically associated with the strength of inspiratory muscles and overall pulmonary function. The lower PIFR observed in the suboptimal cohort suggested a decrease in inspiratory flow, potentially resulting in compromised pulmonary performance. In addition, numerous studies have identified correlations with other spirometric measurements. Maximal inspiratory pressure has been consistently linked to PIFR [24, 51, 58]. Research conducted by Prime et al. revealed a robust correlation between FEV₁ and PIFR through the resistance of the Ellipta inhaler (r = 0.73, p < 0.0001) among patients with severe COPD [67]. Those patients may struggle to adequately disperse the powdered medication, leading to impaired aerosol drug delivery and subsequent poor clinical benefits [68].

Although the In-Check DIAL^® G16 is a validated tool commonly used in both clinical and research settings, its measurement accuracy (± 10% or ± 10 L/min, whichever is greater) may affect the reliability of patient classification around key PIFR thresholds (e.g., 60 L/min). This potential measurement variability should be considered when interpreting PIFR-based inhaler selection.

Aerosol delivery from DPIs to patients with COPD is critically dependent on achieving an optimal PIFR, which many patients struggle to attain. Studies have shown that measuring PIF against the simulated resistance of a DPI is not frequently performed in clinical practice owing to time or equipment limitations, yet it is essential for ensuring the inhalation maneuver is well-matched with the device [69, 70]. Studies have shown that a significant proportion of patients with COPD exhibit improper PIFRs, with variations depending on the resistance of the DPI used. For instance, against medium-high resistance DPIs, 54% of patients achieved optimal PIFR, while 42% had excessive PIFR against low-resistance DPIs, which can affect drug absorption [71].

The USAL30 method, which involves taking a urine sample 30 min after inhalation of salbutamol, is significant for several reasons: the drug content of a urine sample taken 30 min post-inhalation is considered representative of the amount of salbutamol delivered to the lungs. This timing allows for the assessment of the drug’s absorption and bioavailability shortly after administration, providing a clear picture of its effectiveness in reaching the target site of action. The method is noted for its reproducibility, making it a reliable approach for assessing the relative bioavailability of salbutamol. This consistency is crucial for clinical studies and can help in comparing results across different patient populations or inhalation techniques. The USAL30 method is straightforward and does not require complex procedures, such as the ingestion of charcoal or the use of radiolabeled markers, which are often needed in other studies. This simplicity enhances its practicality in clinical settings, allowing for easier implementation in routine assessments of inhaled medications. The method can be used alongside measurements of lung function, enabling researchers to correlate improved drug deposition with enhanced spirometry results. This connection is vital for understanding how different inhalation techniques impact therapeutic outcomes. It can be adapted for evaluating the relative bioavailability of salbutamol when using various inhalation devices and techniques. This adaptability is essential for advancing research in optimizing inhalation therapies for better patient care [35].

One of the key findings of this study was that patients with COPD with suboptimal PIFR without a preliminary dose had significantly lower USAL30 compared with the optimal group, which suggests that suboptimal PIFR leads to reduced lung delivery of the drug, which is similar to previous studies stating that significantly higher USAL30 was obtained with optimal PIFR than with suboptimal PIFR [72–74]. Therefore, it was anticipated that optimal PIFR would lead to better clinical outcomes than suboptimal PIFR owing to better pulmonary deposition. This confirms DPIs’ flow-dependent dose emission characteristic [75]. This makes it reasonable to consider that the powder leaves the inhaler device before the particles have had a chance to de-aggregate. It was previously noted that if there is only a second delay before the patient accelerates their inhalation to the maximum flow, hence decreasing powder de-aggregation, the initial energy for respirable dose generation may not be sufficient [8]. Moreover, the inhaler’s internal resistance and inhalation flow combine to produce the turbulent energy needed for a DPI’s respirable dose release [6, 26]. Hence, greater energy and better-quality emitted doses result from optimal PIFR. Consequently, the optimal patients would be those who breathe as strongly, powerfully, and deeply as they can to improve pulmonary drug delivery.

With the addition of a preliminary bronchodilator dose, the difference in USAL30 between the optimal and suboptimal groups was found to be not statistically significant, which means that better aerosol delivery is supposed to be achieved in patients with suboptimal PIFR as well as with optimal PIFR, in agreement with previous findings in this concern [72]. This may be due to the effect of the preliminary dose of pMDI^® bronchodilator on improving various measures of aerosol drug delivery, including emitted dose, fine particle fraction, and lung deposition, compared with using the DPI alone [72, 76]. Moreover, this improvement is likely attributed to the bronchodilator’s ability to enhance the patient’s lung function and respiratory muscle strength, enabling them to generate a higher PIFR when subsequently using the Diskus DPI [72, 77]. A higher PIFR is critical for effective disaggregation and dispersion of the powder medication from DPIs, as the turbulent energy generated by the patient’s inspiratory effort is the driving force behind this process. Another explanation could be deeper aerosol penetration in the lungs by the direct effect of bronchodilation on improving FEV₁, which was repeatedly proven to enhance aerosol penetration into patients’ lungs across a range of obstructive lung illnesses [28, 29]. Pavia et al. showed a direct correlation between FEV₁ and the depth of aerosol deposition in patients with COPD [27]. Therefore, as observed by Labiris and Dolovich, deeper penetration of the subsequently provided medical aerosol particles was accomplished when FEV₁ was enhanced with a preliminary dose of two pMDI^® puffs. This could be the cause of the elevated USAL30 percentage when using both pMDI^® and DPI [30]. By overcoming the limitations of suboptimal PIFR through the pre-bronchodilator pMDI approach, the study participants were able to achieve more optimal aerosol generation and deposition within the lungs [33, 77].

However, comparing the two suboptimal groups with and without the preliminary bronchodilator dose, USAL30 was found to be slightly higher in the suboptimal group with a preliminary dose compared with the suboptimal group without a preliminary dose, but the difference was not statistically significant. Adding a preliminary pMDI^® increased the USAL30 percentage by 1%, which represents a magnitude of 19.28% of the delivered dose compared with the suboptimal group without the addition of preliminary pMDI^®. This finding is in line with a previous study that declared an incremental increase associated with the two puffs by using a pMDI^®, but the differences were not significant [33]. The explanation of this finding could be that the preliminary dose of pMDI^® bronchodilator does not reach the last peak effect, which is observed within 30–60 min after inhalation, leading to partial amelioration on aerosol drug delivery [37].

A weak positive correlation between patient PIFR and the percentage of nominal dose of USAL30 is consistent with previous studies [78, 79], and it reflects the importance of inhalation techniques for better aerosol drug delivery. The 30-minute urinary recovery of salbutamol has been identified as an index for comparing lung deposition of salbutamol following inhalation [80]. Moreover, studies have repeatedly shown that PIFR plays a crucial role in the effective delivery of inhaled medications, from DPIs to the lungs [81, 82]. Therefore, the correlation between patient PIFR and USAL30 percentage of the nominal dose is highly consistent with prior findings, taking into account that the presented sample size of the current study could be insufficient to extrapolate stronger correlations.

Regarding the ex vivo findings, the SALF percentage of the nominal dose indicated that the total emitted dose delivered by the Diskus® was high regardless of the patient’s PIFR. This suggests that suboptimal PIFR did not cause a greater loss of dose within the inhaler device itself. However, it is more likely to have different pathways of the inhaled dose according to PIFR as proven by in vivo results of the current study. One explanation of that could be that on ex vivo testing, both the medication’s respirable dose (< 5 μm), as well as bigger particles (> 5 μm) that would be ingested and systemically absorbed, are deposited on the filters, making it impossible for the drug on the filters to represent an effective lung dose. [83]. Previous in vitro studies found no significant difference between fine particle doses at diameters ≤ 5 µm and ≤ 3 µm at different flow rates [32]. The optimal and suboptimal group with a preliminary dose showed a nonsignificant increase in SALF percentage of nominal dose if compared with the suboptimal group without a preliminary dose, in agreement with previous studies [33, 72, 84, 85]. This demonstrated that the bronchodilation effect of pMDI minimally decreases aerosol loss within inhaler devices in patients with suboptimal PIFR. This is consistent with the findings of the in vitro testing of the preliminary bronchodilator dose before administration of Diskus^®, which showed no significant difference when compared with a lack of such doses [32, 86, 87]. Moreover, it was observed that ex vivo percentages are higher than in vivo ones, which can be attributed to differences in the two techniques. During ex vivo study, all the doses get trapped on the filter, while in vivo conditions allow for different particle sizes to follow distinct pathways, such as gastrointestinal (GIT) for larger particles, which contributes minimally to the systemic absorption of the inhaled dose within 30 min after dose inhalation (only to 0.3%), or lung deposition [33, 74].

Finally, suboptimal PIFR in patients with COPD seems modifiable through targeted interventions such as appropriate device selection, proper inhaler technique training, regular patient monitoring, and applying preliminary bronchodilation if DPI is selected. The study specifically focused on patients with COPD with suboptimal PIFR using the Diskus^® DPI resistance range. However, the principles of this approach may apply to other DPI devices, as they all rely on the patient’s inspiratory effort to disperse and deliver the medication effectively. Clinicians should assess PIFR as part of the inhaler device selection process. This personalized approach for device selection may be particularly beneficial for elderly patients with COPD or those with advanced disease, who are more likely to have impaired PIFR. It is important to mention that the ultimate goal of our study was to improve aerosol drug delivery using DPI through preliminary dose and to generalize this approach to other inhaled drugs.

Limitations and Future Research Directions

While this study was limited to the Diskus DPI, this choice was intentional, as Diskus is one of the most widely used DPI devices in clinical practice. Its popularity stems from several advantages, including ease of use, consistent dose delivery, and wide availability. These features make it a practical and relevant choice for evaluating inhalation performance in real-world settings. Future research should focus on longitudinal studies to assess the long-term impact of bronchodilator therapy on patients with COPD with varying PIFR levels. This will help in understanding the chronic effects and potential benefits of sustained bronchodilator use, personalizing bronchodilator therapy on the basis of individual patient characteristics, including PIFR, lung function, and compensatory abilities. This approach can optimize treatment outcomes and improve the quality of life for patients with COPD. More specific methods should be used such as scanning electron microscopy and image analysis-based particle size determination to justify the speculative reason for the results with a larger sample size. Comparative studies should be conducted between different types of inhalers (e.g., Diskus^® versus HandiHaler^®) to determine the most effective device for patients with varying PIFR levels. This can guide clinical decisions and patient-specific inhaler prescriptions. Studies should investigate the impact of different preliminary doses and timing on the effectiveness of subsequent bronchodilator therapy. This can help in optimizing dosing regimens for better clinical outcomes. In addition, investigating the impact of this strategy on other clinical endpoints, such as exacerbation rates, quality of life, and healthcare utilization, would provide a more comprehensive understanding of its direct implications.

Conclusions

A significant difference in aerosol drug delivery was observed between patients with COPD with optimal and suboptimal PIFR using the Diskus^® inhaler, which necessitates individualizing inhaler selection with patients with COPD. Administering a preliminary dose of pMDI^® before using a DPI minimally affects the suboptimal inhalation through DPI by priming the airways and improving the patient’s inhalation dynamics.

Funding

Open access funding provided by The Science, Technology & Innovation Funding Authority (STDF) in cooperation with The Egyptian Knowledge Bank (EKB).

Declarations

Funding

No external funding was used in the preparation of this manuscript.

Conflicts of interest

Mohamed Ismail Hassan, Nabila Ibrahim Laz, Yasmin M. Madney, Mohamed E.A. Abdelrahim, and Hadeer S. Harb declare that they have no potential conflicts of interest that might be relevant to the contents of this manuscript.

Author contributions

Mohamed Ismail Hassan (M.I.H.): conception, research, and writing; N.I.L.: conception, planning of study design, and copy editing; Y.M.M.: data entry, statistical analysis, and reviewing of results; M.E.A.A.: conception, planning of study design, and copy editing; H.S.H.: conception, planning of study design, and copy editing. All authors have read and agreed to the published version of the manuscript.

Data availability statement

The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.

Ethics approval

The study was conducted at the Chest Department at the Beni-Suef University Hospital after the study protocol was approved by the Research Ethics Committee of the Faculty of Medicine, Beni-Suef University (FMBSUREC/07042024/Hassan). It was also approved by the Research Ethics Committee of the Faculty of Pharmacy, Beni-Suef University (REC-H-PhBSU-22018) and adhered to the Declaration of Helsinki.

Code availability

Not applicable.

Consent to participate

Each patient provided consent before participating in the study.

Consent for publication

Not applicable.