Smart closed-loop drug delivery systems

Area of Science:

• Biomedical Engineering
• Pharmacology
• Digital Health

Background:

• Chronic disease management faces challenges with traditional drug delivery, including dosage control, adherence, and variable patient responses.
• Current methods often lead to suboptimal outcomes due to fluctuating drug concentrations and lack of real-time feedback.
• Smart closed-loop systems (CLSs) present a solution by combining biosensing with automated drug delivery for personalized treatment.

Purpose of the Study:

• To review the current state of smart closed-loop systems (CLSs) for chronic disease management.
• To explore advancements in wearable and implantable technologies for CLSs.
• To discuss the potential of AI and synthetic biology in next-generation CLSs.

Main Methods:

• Review of recent literature on wearable and implantable CLS technologies.
• Analysis of device design considerations and trade-offs.
• Exploration of artificial intelligence (AI) applications in CLS control algorithms.

Main Results:

• Advancements in wearable and implantable devices enable continuous biomarker monitoring and responsive therapeutic interventions.
• AI can enhance CLS control algorithms for adaptive and predictive therapeutic responses.
• Integration of synthetic biology and engineered cells shows promise for future implantable CLS.

Conclusions:

• CLSs offer a promising approach to overcome limitations in chronic disease management.
• Future CLS development will likely involve sophisticated AI integration and bioengineering.
• Next-generation CLSs aim for highly personalized, adaptive, and effective therapeutic interventions.