Advances and Challenges in IoT-Based Smart Drug Delivery Systems: A Comprehensive Review

Raikar, Amisha S.; Kumar, Pramod; Raikar, Gokuldas (Vedant) S.; Somnache, Sandesh N.

doi:10.3390/asi6040062

Cited by 13 publications

(3 citation statements)

References 55 publications

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“…This integration has the potential to significantly reduce the need for unnecessary hospital or clinical site visits. The AI capabilities of autoinjectors enable accurate data tracking, ensure prompt corrective measures, and increase patient safety (50)(51)(52). Furthermore, they can provide instructions to patients through an application on smart phones or tablets, empowering them to manage their treatments more effectively, revolutionizing patient care, and elevating their healthcare experience (53-55).…”

Section: Benefits Of the Ai-powered Autoinjectorsmentioning

confidence: 99%

Risks and benefits associated with the primary functions of artificial intelligence powered autoinjectors

Machal

2024

Front. Med. Technol.

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ObjectivesThis research aims to present and assess the Primary Functions of autoinjectors introduced in ISO 11608-1:2022. Investigate the risks in current autoinjector technology, identify and assess risks and benefits associated with Artificial Intelligence (AI) powered autoinjectors, and propose a framework for mitigating these risks. ISO 11608-1:2022 is a standard that specifies requirements and test methods for needle-based injection systems intended to deliver drugs, focusing on design and function to ensure patient safety and product effectiveness. ‘KZH’ is an FDA product code used to classify autoinjectors, for regulatory purposes, ensuring they meet defined safety and efficacy standards before being marketed.MethodA comprehensive analysis of autoinjectors problems is conducted using data from the United States Food and Drug Administration (FDA) database. This database records medical device reporting events, including those related to autoinjectors, reported by various sources. The analysis focuses on events associated with the product code KZH, covering data from January 1, 2008, to September 30, 2023. This research employs statistical frequency analysis and incorporates pertinent the FDA, United Kingdom, European Commission regulations, and ISO standards.Results500 medical device reporting events are assessed for autoinjectors under the KZH code. Ultimately, 188 of these events are confirmed to be associated with autoinjectors, all 500 medical devices were seen to lack AI capabilities. An analysis of these events for traditional mechanical autoinjectors revealed a predominant occurrence of malfunctions (72%) and injuries (26%) among event types. Device problems, such as breakage, defects, jams, and others, accounted for 45% of incidents, while 10% are attributed to patient problems, particularly missed and underdoses.ConclusionTraditional autoinjectors are designed to assist patients in medication administration, underscoring the need for quality control, reliability, and design enhancements. AI autoinjectors, sharing this goal, bring additional cybersecurity and software risks, requiring a comprehensive risk management framework that includes standards, tools, training, and ongoing monitoring. The integration of AI promises to improve functionality, enable real-time monitoring, and facilitate remote clinical trials, timely interventions, and tailored medical treatments.

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Section: Benefits Of the Ai-powered Autoinjectorsmentioning

confidence: 99%

Risks and benefits associated with the primary functions of artificial intelligence powered autoinjectors

Machal

2024

Front. Med. Technol.

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“…Wearable electronic textiles (e-textiles) have evolved significantly in recent years, owing to advances in material science, nanotechnology, miniaturization, and the internet of things (IoT). [1][2][3][4][5] In this context, there is an increasing interest in capturing ambient energy and transforming it into usable electricity, which offers a viable path for powering interconnected wearable devices. Solar energy, thermal energy from the human body and surroundings, mechanical energy from human actions, and wind power are all examples of freely available energy derived from the surrounding environment.…”

Section: Introductionmentioning

confidence: 99%

2D Material‐Based Wearable Energy Harvesting Textiles: A Review

Ali,

Dulal,

Karim

et al. 2023

Small Structures

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Wearable electronic textiles (e‐textiles) have emerged as a transformative technology revolutionizing healthcare monitoring and communication by seamlessly integrating with the human body. However, their practical application has been limited by the lack of compatible and sustainable power sources. Various energy sources, including solar, thermal, mechanical, and wind, have been explored for harvesting, leading to diverse energy harvesting technologies, such as photovoltaic, thermoelectric, piezoelectric, and triboelectric systems. Notably, 2D materials have gained significant attention as attractive candidates for energy harvesting and storage in e‐textiles due to their unique properties, such as high surface‐to‐volume ratio, mechanical strength, and electrical conductivity. Textile‐based energy harvesters employing 2D materials offer promising solutions for powering next‐generation smart and wearable devices integrated into clothing. This comprehensive review explores the utilization of 2D materials in textile‐based energy harvesters, covering their preparation, fabrication, and characterization strategies. Recent advancements are highlighted, focusing on the integration of 2D materials and their practical implementations, shedding light on the performance and effectiveness of 2D‐material‐based energy harvesters in e‐textiles, and highlighting their potential as a sustainable alternative to conventional power supplies in wearable technologies.

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“…A non-invasive anesthetic control system built on the Internet of Things has also been created. This method provides a promising new way to administer anesthetics safely and effectively [12].…”

Section: Introductionmentioning

confidence: 99%

Advanced Iot-Based Anesthesia Management System With Remote Monitoring and Controlling

Rajkumar,

2023

IJASIS

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In this paper, an efficient system based on the Internet of Things (IoT) which allows for remote monitoring and controlling through Raspberry Pi, to improve the delivery of anesthetic in clinical settings is presented. This method permits real-time monitoring and smooth remote control of anesthetic equipment by using the IoT capabilities and the adaptability of Raspberry Pi. The Raspberry Pi serves as a hub, communicating with the rest of the anesthetic machine and aggregating data from a wide range of sensors. Anesthesia parameters, real-time data visualization, and crucial alert notifications may all be accessed by medical staff through online or mobile apps, thanks to the system's secure cloud interface. The ease of use, confidentiality of patient information, and conformity with applicable laws and regulations are prioritized to guarantee that only authorized individuals have access to medical equipment. Due to its proven dependability and safety, the system is a vital tool for today's hospitals, helping to improve both patient outcomes and doctors' efficiency.

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Advances and Challenges in IoT-Based Smart Drug Delivery Systems: A Comprehensive Review

Cited by 13 publications

References 55 publications

Risks and benefits associated with the primary functions of artificial intelligence powered autoinjectors

Risks and benefits associated with the primary functions of artificial intelligence powered autoinjectors

2D Material‐Based Wearable Energy Harvesting Textiles: A Review

Advanced Iot-Based Anesthesia Management System With Remote Monitoring and Controlling

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