Smart Inhaler Research Articles

Development of a Sound-Based Smart Inhaler With a Mechanical Acoustic Filter for Medication Identification

Development of a Sound-Based Smart Inhaler With a Mechanical Acoustic Filter for Medication Identification

Flowrate Sensing and Measurement in Portable Smart Inhalers

This review discusses approaches and implementations of flowrate sensing and measurement in smart inhalers for effective respiratory disease management. It highlights the importance of compliance with proper inhaling techniques and consistent adherence for managing respiratory conditions. Methods and relevant commercial and prototype research-type devices for sensing and measuring inhalation flowrate in smart inhalers are studied and compared. The study argues that the utilisation of acoustic analysis and air-pressure sensing is a promising approach to detect and evaluate the inhaling action, ultimately allowing improvement in the treatment outcomes and life quality of patients with respiratory diseases.

Adherence to single inhaler triple therapy and digital inhalers in Chronic Obstructive Pulmonary Disease: a literature review and protocol for a randomized controlled trial (TRICOLON study)

BackgroundMedication non-adherence is a significant problem in patients with Chronic Obstructive Pulmonary Disease (COPD). Efforts to address this issue are receiving increased attention. Simplifying treatment by prescribing single-inhaler triple therapy (SITT) as an alternative to multi-inhaler triple therapy (MITT) or with smart inhalers are often considered potential solutions. However, the actual impact of these innovations on adherence and clinical outcomes is unclear.MethodsTo address this knowledge gap we first conducted a literature review focusing on two research questions: 1) the difference in adherence between SITT and MITT users in COPD, and 2) the effect of smart inhalers on adherence in COPD. Separate searches were conducted in PubMed and two authors independently assessed the articles. In addition, we present a protocol for a study to acquire knowledge for the gaps identified.ResultsTo address the first research question, 8 trials were selected for further review. All trials were observational, i.e. randomized controlled trials were lacking. Seven of these trials showed higher adherence and/or persistence in patients on SITT compared with patients on MITT. In addition, four studies showed a positive effect of SITT on various clinical outcomes. For the second research question, 11 trials were selected for review. While most of the studies showed a positive effect of smart inhalers on adherence, there was considerable variation in the results regarding their effect on other clinical outcomes.The TRICOLON (TRIple therapy COnvenience by the use of one or multipLe Inhalers and digital support in ChrONic Obstructive Pulmonary Disease) trial aims to improve understanding regarding the effectiveness of SITT and smart inhalers in enhancing adherence. This open-label, randomized, multi-center study will enroll COPD patients requiring triple therapy at ten participating hospitals. In total, 300 patients will be randomized into three groups: 1) MITT; 2) SITT; 3) SITT with digital support through a smart inhaler and an e-health platform. The follow-up period will be one year, during which three methods of measuring adherence will be used: smart inhaler data, self-reported data using the Test of Adherence to Inhalers (TAI) questionnaire, and drug analysis in scalp hair samples. Finally, differences in clinical outcomes between the study groups will be compared.DiscussionOur review suggests promising results concerning the effect of SITT, as opposed to MITT, and smart inhalers on adherence. However, the quality of evidence is limited due to the absence of randomized controlled trials and/or the short duration of follow-up in many studies. Moreover, its impact on clinical outcomes shows considerable variation. The TRICOLON trial aims to provide solid data on these frequently mentioned solutions to non-adherence in COPD. Collecting data in a well-designed randomized controlled trial is challenging, but the design of this trial addresses both the usefulness of SITT and smart inhalers while ensuring minimal interference in participants' daily lives.Trial registrationNCT05495698 (Clinicaltrials.gov), registered at 08–08-2022. Protocol version: version 5, date 27–02-2023.

Use of Technology to Improve Adherence in Allergy/Immunology

The integration of technology into health care has shown significant promise in enhancing patient adherence, particularly in the field of allergy/immunology. This article explores the multifaceted approaches through which digital health interventions can be used to improve adherence rates among patients with allergic diseases and immunologic disorders. By reviewing recent advancements in telemedicine, mobile health applications, wearable devices, and digital reminders, as well as smart inhalers, we aim to provide a comprehensive overview of how these technologies can support patients in managing their conditions. The analysis highlights the role of personalized digital health plans, which, through the use of artificial intelligence and machine learning algorithms, can offer tailored advice, monitor symptoms, and adjust treatment protocols in real time. Moreover, the article discusses the impact of electronic health records and patient portals in fostering a collaborative patient-provider relationship, thereby enhancing communication and adherence. The integration of these technologies has been shown to not only improve clinical outcomes but also increase patient satisfaction and engagement.

DIGIPREDICT: physiological, behavioural and environmental predictors of asthma attacks—a prospective observational study using digital markers and artificial intelligence—study protocol

IntroductionAsthma attacks are a leading cause of morbidity and mortality but are preventable in most if detected and treated promptly. However, the changes that occur physiologically and behaviourally in the...

Smart inhaler tailors drug delivery to each patient

Using patient data, machine learning algorithm optimizes inhalers to treat respiratory illness.

A user-centered smart inhaler algorithm for targeted drug delivery in juvenile onset recurrent respiratory papillomatosis treatment integrating computational fluid particle dynamics and machine learning

Recurrent respiratory papillomatosis (RRP) is a chronic condition primarily affecting children, known as juvenile onset RRP (JORRP), caused by a viral infection. Antiviral medications have been used to reduce the need for frequent surgeries, slow the growth of papillomata, and prevent disease spread. Effective treatment of JORRP necessitates targeted drug delivery (TDD) to ensure that inhaled aerosolized drugs reach specific sites, such as the larynx and glottis, without harming healthy tissues. Using computational fluid particle dynamics (CFPD) and machine learning (ML), this study (1) investigated how drug properties and individual factors influence TDD efficiency for JORRP treatment and (2) developed personalized inhalation therapy using an ML-empowered smart inhaler control algorithm for precise medication release. This algorithm optimizes the inhaler nozzle position and diameter based on drug and patient-specific data, enhancing drug delivery to the larynx and glottis. CFPD simulations show that particle size significantly affects deposition fractions in the upper airway, emphasizing the importance of particle size selection. Additionally, optimal nozzle diameter and delivery efficiency depend on particle size, inhalation flow rate, and release time. The ML-based TDD strategy, employing a classification and regression tree model, outperforms conventional inhalation therapy by achieving a higher delivery efficiency to the larynx and glottis. This innovative concept of an ML-empowered smart inhaler represents a promising step toward personalized and precise pulmonary healthcare through inhalation therapy. It demonstrates the potential of AI-driven smart inhalers for improving the treatment outcomes of lung diseases that require TDD at designated lung sites.

SMART INHALERS: HARNESSING IOT FOR PRECISE ASTHMA MANAGEMENT

Effective management techniques are required for the widespread chronic respiratory disease known as asthma in order to reduce its negative effects on public health. Smart inhalers are a prime example of how the introduction of Internet of Things (IoT) technology has sparked creative solutions. In this essay, the seamless integration of IoT technology is used to elaborate on the transformational potential of smart inhalers in improving asthma management. The traditional approach to managing asthma relies on individualised prescription regimens that must be consistently followed. But obstacles including patient forgetfulness and insufficient real-time monitoring frequently prevent effective adherence, aggravating symptoms and lowering quality of life. Smart inhalers are the result of the confluence of IoT technology with asthma therapy, signalling a paradigm change. Smart inhalers, driven by IoT, offer a wide range of characteristics and signal a paradigm change in the treatment of asthma. (1) These gadgets can monitor medicine use, inhaler technique, and environmental triggers in real time since they include sensors and connection. Personalised therapy modifications are made possible by the real-time data creation that gives healthcare professionals insights into patient behaviour, adherence trends, and symptom development. The ability of smart inhalers to revolutionise medication adherence is one of their main benefits. (2)Patients are better able to maintain their regimens when they receive prompt guidance on how to use an inhaler and reminders to take prescription drugs as directed. The resultant decline in emergency room visits, hospital admissions, and asthma attacks is evidence of these devices' effectiveness. Healthcare professionals are empowered to quickly react and prevent the progression of symptoms thanks to the real-time data stream from smart inhalers. (3)Asthma care has advanced dramatically with the introduction of IoT-enabled smart inhalers, which are expected to improve asthma sufferers' medication compliance, symptom management, and overall quality of life. Predicted developments in smart inhaler technology, including artificial intelligence and predictive analytics, portend improved personalisation and therapeutic efficacy as the IoT environment changes. The promise of smart inhalers to reshape asthma care resonates deeply with the principles of patient education, engagement, and interdisciplinary collaboration among healthcare professionals, researchers, and technology developers, setting a promising trajectory for respiratory healthcare. (4)

Inhaler Adherence in COPD: A Crucial Step Towards the Correct Treatment.

COPD is a typical example of chronic disease. As such, treatment adherence tends to be as low as between 30% and 50%, with specific issues in COPD due to the use of inhaled therapies. Decreased adherence in COPD is associated with worse outcomes, with increased risk for exacerbations and long-term mortality. Factors that impact adherence are multiple, some related to patient, some related to clinicians and finally some related to healthcare system. Among clinician factors, prescription of simplified treatment regimens delivered by an inhaler adapted to the patient's characteristics is crucial. Although it has been observed a huge improvement in the design and usability of inhaler devices for COPD in the last two centuries, there is still a clear gap in this field. Smart inhalers as well as simplified treatment regimens could improve adherence and therefore improve long-term outcomes in COPD.

Smart inhaler mask for portable medical gas cylinders utilizing IoT technologies

Over the past decade, there has been a significant increase in the development of wearable and smart health devices based on the Internet of Things (IoT), that enable real time remote control and monitoring of health parameters. In this context, the purpose of this article is to present the development and evaluation process of a smart inhaler mask designed for medical gas cylinders, utilizing IoT technologies. Handheld medical gas cylinders, although essential for a specific group of people, often come with a significant cost, and lack features such as dosage measurement and gas storage monitoring. Consequently, a smart inhaler mask was developed to address these limitations by enabling in-situ and real-time measurement of gas dosage, tracking the remaining gas within the cylinder, and assisting users in monitoring the overall usage of the medical gas cylinder. To facilitate the access and interpretation of this information, a newly developed and user-friendly Graphical User Interface (GUI) has been implemented in the form of a mobile application. This study outlines the evaluation process employed to verify the reliability and accuracy of the results obtained from the smart inhaler mask.

Treatable traits, combination inhaler therapy and the future of asthma management.

The landscape of asthma has considerably changed in the last decade. Effective medications and inhaler devices have been developed and integrated into the asthma pharmacopoeia, but unfortunately, the proportion of uncontrolled patients remains unacceptably high. This is now recognized to be mainly due to the inappropriate use of medications or inhaler devices, heterogeneity of the disease or other factors contributing to the disease. Currently, inhaled corticosteroids (ICS), with or without long-acting beta agonists (LABA), are the cornerstone of asthma management, and recently international guidelines recognized the importance of combination inhaler therapy (ICS/LABA) even in mild asthma. In future, ultra-long-acting personalized medications and smart inhalers will complement combination inhaler therapy in order to effectively addresses issues such as adherence, inhaler technique and polypharmacy (both of drugs and devices). Asthma is now acknowledged as a multifaceted cluster of disorders and the treatment model has evolved from one-size-fits-all to precision medicine approaches such as treatable traits (TTs, defined as measurable and treatable clinically important factors) which encourages the quality use of medications and identification and management of all underlying behavioural and biological treatable risk factors. TT requires research and validation in a clinical context and the implementation strategies and efficacy in various settings (primary/secondary/tertiary care, low-middle income countries) and populations (mild/moderate/severe asthma) are currently evolving. Combination inhaler therapy and the TTs approach are complementary treatment approaches. This review examines the current status of personalized medicine and combination inhaler therapy, and describes futuristic views for these two strategies.

Fog-Enabled Efficient Asthma Monitoring System

Abstract: For monitoring patients at risk for chronic diseases, wireless and wearable sensors are now widely used in the healthcare sector. This guarantees that patients adhere to their treatment regimens and safeguards them from unexpected attacks. Numerous sensors have produced a vast amount of data. In this paper, we propose to use fog computing to support the monitoring of asthma patients using IoT-enabled devices such as smart inhalers to monitor the rate and environmental factors surrounding asthma attacks, ensuring that data is collected and processed effectively. The main challenge would be limiting the selection of information to that which is pertinent to the patient's health in the given context. A fog computing layer is necessary because a simple sensor-to-cloud architecture is unworkable. By minimizing the amount of data transferred back and forth between the cloud and the sensors and removing the risk that a data center failure carries, this increases overall system efficiency.

Abstracts from The Aerosol Society Drug Delivery to the Lungs 33.

Abstracts from The Aerosol Society Drug Delivery to the Lungs 33.

Anticipated barriers and facilitators for implementing smart inhalers in asthma medication adherence management

Smart inhalers are electronic monitoring devices which are promising in increasing medication adherence and maintaining asthma control. A multi-stakeholder capacity and needs assessment is recommended prior to implementation in healthcare systems. This study aimed to explore perceptions of stakeholders and to identify anticipated facilitators and barriers associated with the implementation of smart digital inhalers in the Dutch healthcare system. Data were collected through focus group discussions with female patients with asthma (n = 9) and healthcare professionals (n = 7) and through individual semi-structured interviews with policy makers (n = 4) and smart inhaler developers (n = 4). Data were analysed using the Framework method. Five themes were identified: (i) perceived benefits, (ii) usability, (iii) feasibility, (iv) payment and reimbursement, and (v) data safety and ownership. In total, 14 barriers and 32 facilitators were found among all stakeholders. The results of this study could contribute to the design of a tailored implementation strategy for smart inhalers in daily practice.

Smart inhalers: Transforming asthma management and the pharmacist's involvement in patient education

Background: Asthma remains a global healthcare challenge despite advancements in classification, diagnosis, and inhalation therapy. A significant proportion of patients continue to experience uncontrolled asthma, which is linked to factors such as non-adherence to treatment and improper inhaler technique. Aim: This article aims to explore the potential of smart inhalers in transforming asthma management and to highlight the critical role of pharmacists in patient education. Methods: A comprehensive review of literature was conducted, focusing on the prevalence of uncontrolled asthma, the impact of non-adherence, and the integration of digital health technologies, particularly smart inhalers. The study involved an examination of the role of pharmacists in providing asthma education and promoting proper inhaler technique. Results: Findings reveal that 30% to 70% of asthma patients are non-adherent to their medication regimens. Smart inhalers equipped with digital health technologies can enhance medication adherence by providing real-time feedback to patients regarding their inhaler use and asthma status. The involvement of pharmacists in patient education is crucial for optimizing inhaler technique and improving overall asthma management. Conclusion: Smart inhalers represent a promising advancement in asthma care by addressing non-adherence and enhancing self-management.

Effectiveness, usability and acceptability of a smart inhaler programme in patients with asthma: protocol of the multicentre, pragmatic, open-label, cluster randomised controlled ACCEPTANCE trial

IntroductionSuboptimal asthma control is associated with incorrect inhaler use and poor medication adherence, which could lead to unfavourable clinical and economic outcomes. Smart inhaler programmes using electronic monitoring devices (EMDs)...

Digital Coaching Using Smart Inhaler Technology to Improve Asthma Management in Patients With Asthma in Italy: Community-Based Study.

Reliance on short-acting β-2 agonists and nonadherence to maintenance medication are associated with poor clinical outcomes in asthma. Digital health solutions could support optimal medication use and therefore disease control in patients with asthma; however, their use in community settings has not been determined. The primary objective of this study is to investigate community implementation of the Turbu+ program designed to support asthma self-management, including adherence to budesonide and formoterol (Symbicort) Turbuhaler, a combination inhaler for both maintenance therapy or maintenance and reliever therapy. The secondary objective is to provide health care professionals with insights into how patients were using their medication in real life. Patients with physician-diagnosed asthma were prescribed budesonide and formoterol as maintenance therapy, at a dose of either 1 inhalation twice daily (1-BID) or 2 inhalations twice daily (2-BID), or as maintenance and reliever therapy (1-BID and reliever or 2-BID and reliever in a single inhaler), and they received training on Turbu+ in secondary care centers across Italy. An electronic device attached to the patients' inhaler for ≥90 days (data cutoff) securely uploaded medication use data to a smartphone app and provided reminders, visualized medication use, and motivational nudge messages. Average medication adherence was defined as the proportion of daily maintenance inhalations taken as prescribed (number of recorded maintenance actuations per day or maintenance inhalations prescribed per day) averaged over the monitoring period. The proportion of adherent days was defined as the proportion of days when all prescribed maintenance inhalations were taken on a given day. The Wilcoxon test was used to compare the proportion of adherent days between patients in the maintenance regimen and patients in the maintenance and reliever regimen of a given dose. In 661 patients, the mean (SD) number of days monitored was 217.2 (SD 109.0) days. The average medication adherence (maintenance doses taken/doses prescribed) was 70.2% (108,040/153,820) overall and was similar across the groups (1-BID: 6332/9520, 66.5%; 1‑BID and reliever: 43,578/61,360, 71.0%; 2-BID: 10,088/14,960, 67.4%; 2-BID and reliever: 48,042/67,980, 70.7%). The proportion of adherent days (prescribed maintenance doses/doses taken in a given day) was 56.6% (31,812/56,175) overall and was higher with maintenance and reliever therapy (1-BID and reliever vs 1-BID: 18,413/30,680, 60.0% vs 2510/4760, 52.7%; P<.001; 2-BID and reliever vs 2-BID: 8995/16,995, 52.9% vs 1894/3740, 50.6%; P=.02). Rates of discontinuation from the Turbu+ program were significantly lower with maintenance and reliever therapy compared with maintenance therapy alone (P=.01). Overall, the high medication adherence observed during the study might be attributed to the electronic monitoring and feedback mechanism provided by the Turbu+ program.

Predicting asthma attacks using connected mobile devices and machine learning: the AAMOS-00 observational study protocol

IntroductionSupported self-management empowering people with asthma to detect early deterioration and take timely action reduces the risk of asthma attacks. Smartphones and smart monitoring devices coupled with machine learning could...

250 Tracking Asthma Medication Use in Children After an Emergency Department Visit With a Smart Inhaler and Connected Mobile Application

Asthma is the most common chronic childhood illness and the third leading cause of hospitalization among pediatric patients in the US. It is responsible for more than 1.8 million emergency department (ED) visits per year and represents significant health care burden and costs. The primary objective of this study is to determine the feasibility of employing a “smart” inhaler connected to a mobile application to track asthma inhaler use after an ED visit. Future goals are to determine if regular daily use of a steroid inhaler results in less rescue medication use, and to connect this usage with real time environmental data to build a risk profile to alert patients of conditions that increase risk of asthma exacerbation.

Design Validation of a Smart Inhaler Device with an Integrated Spacer for Enhanced Aerosolization Performance

Design Validation of a Smart Inhaler Device with an Integrated Spacer for Enhanced Aerosolization Performance