Adaptive Therapeutic Systems: Integrating Real-Time Biosensing, AI and Personalized Medicine

Danielle Li

Adaptive Therapeutic Systems: Integrating Real-Time Biosensing, AI and Personalized Medicine

Author(s)	Danielle Li
Country	United States
Abstract	The convergence of real-time biosensing, artificial intelligence (AI), wearable technologies, digital health platforms, and precision medicine is creating a new generation of adaptive therapeutic systems capable of continuously responding to individual patient conditions. Conventional therapeutic models generally rely on periodic clinical assessments and predefined treatment protocols, which may not adequately capture rapid changes in physiological status, treatment response, or disease progression. Adaptive therapeutic systems seek to address this limitation by creating continuous feedback loops between biosensing, data analytics, clinical decision-making, and therapeutic intervention. This paper examines the emerging architecture of adaptive therapeutic systems and evaluates the integration of real-time biosensing technologies with AI and personalized medicine. It explores applications in chronic disease management, cardiovascular monitoring, diabetes, neurological disorders, oncology, rehabilitation, and medication optimisation. Particular attention is given to wearable and implantable sensors, physiological signal processing, machine learning, digital biomarkers, predictive modelling, closed-loop treatment systems, and patient-specific therapeutic adjustment. The paper proposes an Adaptive Therapeutic Intelligence Framework consisting of five interconnected layers: biosensing and data acquisition, physiological data integration, AI-based interpretation, personalised decision support, and adaptive intervention. The study also discusses challenges related to sensor reliability, data interoperability, algorithmic bias, explainability, cybersecurity, patient privacy, clinical validation, regulatory oversight, and human-AI collaboration. It argues that the future of personalised medicine will increasingly move from static treatment plans toward continuously learning therapeutic systems that adapt to changing biological conditions. However, such systems must remain clinically validated, transparent, secure, and human-centred. The paper concludes that the integration of real-time biosensing and AI provides a foundation for more responsive, predictive, and personalised healthcare, particularly when technological innovation is combined with rigorous clinical evidence and responsible governance.
Keywords	Adaptive Therapeutic Systems, Real-Time Biosensing, Artificial Intelligence, Personalized Medicine, Digital Biomarkers, Wearable Sensors, Precision Medicine, Machine Learning, Closed-Loop Therapy, Digital Health.
Field	Engineering
Published In	Volume 6, Issue 6, November-December 2024
Published On	2024-11-01

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American Journal of Advanced Multidisciplinary Research and Innovation

A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

Adaptive Therapeutic Systems: Integrating Real-Time Biosensing, AI and Personalized Medicine

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