IoT Enabled Smart Drug Delivery System Using Machine Learning for Personalized Therapy.

The study addresses the creation of a smart drug delivery system with the use of machine learning and IoT to implement personalized drug delivery. It is aimed at improving the precision and effectiveness of drug delivery utilizing the real-time patient information to model the therapeutic interventions. The system involves IoT devices, i.e. wearable sensors, to constantly track patient information, including vital signs and medication adherence. This data is then fed into machine learning algorithms to predict the right doses of drugs and change the delivery schedules thus personalizing therapy to that individual. The design and implementation of this integrated system, extensive simulations and case studies to determine the efficiency of the system in terms of accuracy, reliability, and scalability are the methodology. The initial resultsindicate that drug delivery system with the use of EoT can considerably increase the drug efficacy, reduce side effects and patient adherence. Moreover, the fact that the IoT technology seamlessly integrates with the machine learning is why the system can be utilized in revolutionizing personalized medicine. The importance of this study is that, such studies offer a more dynamic and efficient method of drug delivery which can save on the cost of health care through limited trial and error prescriptions and rehospitalization. The technology has potential opportunities of large-scale use in clinical practices ensuring better patient outcomes and a more data-driven approach to healthcare management.