Besides improving drug solubility and stability, co-amorphous systems (COAMS) have recently been reported to enhance the pulmonary delivery efficiency of dry powder inhalation (DPI), offering a novel approach to the development of DPI. Conventional drug formulation development utilizes trial-and-error experiments, which require a laborious workload and resources. Moreover, the correlation of forming COAMS to enhanced pulmonary deposition remains underrepresented. Therefore, we proposed applying multiple machine learning (ML) models to the development of co-amorphous DPIs. In this study, we first constructed the database of COAMS through literature mining and then preprocessed the dataset with a molecular representation method. Subsequently, we successfully developed and evaluated the predictive performance of multiple ML models (i.e., logistic regression, random forests, XGBoost, LightGBM, and support vector machines) for forming a co-amorphous system. The five ML models' performance varied, yet all achieved satisfactory predictive accuracy (ACC) of around 0.80 in the testing subset. Specifically, LightGBM exhibited the highest ACC of 0.790 in cross-validation and 0.845 in the testing subset. In addition, SHapley Additive ex Planations (SHAP) analysis revealed that several molecular features (i.e., API_EState_VSA10, Co-former_BCUT2D_MRHI) are critical for models' prediction. More importantly, we conducted experimental validation by using salbutamol sulfate and indomethacin as model drugs to prepare co-amorphous DPIs based on the fine-tuned LightGBM model. The co-amorphous DPIs showed satisfactory aerodynamic performance with fine particle fractions of 41.87%-69.30%. In conclusion, we successfully demonstrated the feasibility of ML for guiding the formation of co-amorphous DPIs, further facilitating the development process in the future.

Pseudohypoaldosteronism type 1B (PHA1B) is a rare autosomal recessive disorder characterized by systemic resistance to aldosterone due to pathogenic variants in epithelial sodium channel (ENaC) subunit genes. We report an eight-month-old Saudi male infant, born to consanguineous parents, who initially presented at seven days of life with persistent hyperkalemia, hyponatremia, and metabolic acidosis. Despite aggressive medical management, including sodium supplementation, insulin-dextrose therapy, nebulized salbutamol, and peritoneal dialysis, electrolyte disturbances persisted. Whole-exome sequencing identified a novel homozygous likely pathogenic variant in the SCNN1B gene (NM_000336.2:c.1573C>T; p.Gln525*), confirming the diagnosis of systemic PHA1B.

A 3-year-old male passenger developed acute respiratory distress approximately 30 minutes after takeoff during an international flight from the United States to Addis Ababa. Despite multiple rounds of nebulized albuterol and escalating oxygen therapy, his respiratory status progressively deteriorated. A multidisciplinary team of onboard physicians administered epinephrine and hydrocortisone from the emergency medical kit while coordinating with ground medical control. The aircraft was subsequently diverted to Athens, Greece, where the child was handed over to emergency services and later stabilized. This case highlights the challenges of managing pediatric respiratory distress in-flight and the critical importance of prompt coordination, adequate medical supplies, and crew preparedness.

Background: Poor adherence to daily asthma controller medications contributes to increased emergency department (ED) visits and hospitalizations in children. A simple bedside tool to assess adherence is needed in clinical settings. Objective: The objective was to determine whether a child's or a caregiver's ability to recognize the prescribed daily controller inhaler is associated with poor adherence and increased asthma morbidity. Methods: A retrospective chart review was conducted on 163 pediatric patients (ages 3-18 years) admitted for asthma exacerbation on patient's and/or caregiver's ability to identify the patient's prescribed daily controller inhaler. Patients were classified as recognizing or not recognizing their inhaler. Clinical outcomes, including ED visits, hospital admissions, systemic corticosteroid use, and adherence markers (prescription refills and follow-up visits), were compared between the groups. Results: The patients unable to recognize their inhaler had significantly poorer adherence, with fewer prescription refills (p = 0.001) and lower rates of specialty follow-up (p ≤ 0.001). These patients also had higher rates of asthma-related ED visits (p = 0.003) and systemic corticosteroid use (p = 0.010). No significant association was found with inpatient admissions, impairment of daily symptoms, or frequency of albuterol use. Patients with three or more intensive care unit admissions in the past year were more likely to recognize their inhalers (p = 0.013), possibly due to increased exposure to asthma education. Conclusion: The inability to recognize a prescribed daily controller inhaler is associated with poor adherence and increased asthma-related ED visits and systemic corticosteroid use. This simple bedside assessment may help identify patients at high risk and guide targeted interventions to improve adherence and asthma outcome.

The physical stability of salbutamol amorphous solid dispersion (ASD) pharmaceutical tablets, manufactured via a novel strategy employing liquid drug feeding during hot-melt extrusion, was evaluated using terahertz time-domain spectroscopy (THz-TDS). A total of 41 salbutamol ASD pharmaceutical tablets were individually tracked for longitudinal assessment, and physical stability was demonstrated over 15 months with no detectable salbutamol crystals. The absorption coefficient spectra retained smooth, continuously increasing profiles, which match the vibrational density of states of amorphous solids. The absence of the crystalline salbutamol phonon mode at 0.98THz was substantiated by first- and second-derivative spectral analyses. Temporal consistency in both absorption coefficient and refractive index spectra across all tablets further supported the lack of detectable crystallinity. These observations were equally demonstrated by the simpler, more straightforward and physically interpretable absorption coefficient ratio α0.98THz/α0.75THz of the salbutamol peak to the baseline. It was found that α0.98THz/α0.75THz is consistent over time and agrees with that of the salbutamol ASDs, whilst distinctively differentiating the pharmaceutical tablets from crystalline salbutamol. The direct, rapid, and non-destructive assessment of crystallinity, particularly via the simple, physically interpretable absorption coefficient ratio, makes THz-TDS advantageous for longitudinal stability studies and individual tracking of solid dosage forms during drug product development.

Accurate prediction of bronchodilator performance remains challenging. We present a coupled computational fluid and particle dynamics (CFPD) and physiologically-based pharmacokinetic/pharmacodynamics (PBPK/PD) framework that leverages subject-specific CT-derived airway trees and airflow distributions to model regional lung exposure and the resulting clinical effect, quantified as the change in Forced Expiratory Volume in 1 second (ΔFEV1). Data from six asthmatic and ten healthy subjects were analyzed. CFPD simulations predicted subject-specific airflow and drug deposition by airway generation for inhalation of 400 μg albuterol using a metered dose inhaler (MDI) and a dry powder inhaler (DPI). The deposited dose was input into the PBPK model at the epithelial lining fluid (ELF) to predict drug concentrations in plasma and tissues. The PD model predicted ΔFEV1 at the subepithelium effect-site. Two key observations emerged. First, MDI use shifted the inhaled dose toward the respiratory region, whereas DPI delivery resulted in greater deposition in generations G2-G5. Second, asthmatic subjects exhibited higher resistance than healthy subjects in generations G5-G10, resulting in larger ΔFEV1. Fitted PD model parameters, yielded a half-maximal effective concentration (EC50 =1.1±0.07 nM) and Hill slope (n =1.6±0.1), with R2 = 0.98. In summary, we developed a subject-specific coupled CFPD-PBPK/PD framework to predict inhaled albuterol exposure in plasma and ELF, as well as the resulting ΔFEV1 clinical response. This approach has the potential to inform inhaler selection, optimize dosing strategies, and enable disease-specific inhalational therapies. The present study was limited to male subjects, and future work should extend the framework to include sex-specific physiological differences.