Artificial Intelligence-Driven Automated Drug Delivery Systems for Analgesia and Anaesthesia in the Modern World

Mohit Aggarwal; Vaskar Majumdar; Anupam Chakrabarti; Chirasree Choudhury

doi:10.36948/ijfmr.2026.v08i03.79139

Artificial Intelligence-Driven Automated Drug Delivery Systems for Analgesia and Anaesthesia in the Modern World

Author(s)	Dr. Mohit Aggarwal, Prof. Dr. Vaskar Majumdar, Prof. Dr. Anupam Chakrabarti, Dr. Chirasree Choudhury
Country	India
Abstract	Background: The management of pain and anaesthesia has long depended on clinician expertise and fixed pharmacokinetic models. However, considerable inter-individual variability in drug response, narrow therapeutic windows, and the risk of adverse events — including awareness under anaesthesia and opioid-induced respiratory depression — underscore the limitations of conventional approaches. Artificial intelligence (AI), through machine learning (ML), deep learning (DL), and closed-loop control algorithms, is now enabling real-time, patient-specific automated drug delivery systems that promise to overcome these limitations. Objectives: This review article comprehensively examines the current state of AI-driven automated drug delivery systems for analgesia and anaesthesia, covering closed-loop total intravenous anaesthesia (TIVA), automated analgesia titration, reinforcement learning-based controllers, and future directions including federated learning and digital twins. Methods: A literature review was conducted using PubMed, Scopus, Google Scholar, and ClinicalTrials.gov databases. Articles published between 2010 and 2024 were screened using key terms including "closed-loop anaesthesia," "AI drug delivery," "automated analgesia," "machine learning pharmacokinetics," and "reinforcement learning anaesthesia." Results and Conclusions: Evidence shows that AI-guided closed-loop systems achieve superior drug-dosing precision compared to manual administration, reduce propofol consumption, shorten recovery times, and lower rates of intraoperative awareness. Challenges including regulatory approval, algorithmic bias, interpretability, and cybersecurity remain. The integration of AI with pharmacokinetic–pharmacodynamic (PK–PD) modelling, continuous monitoring, and wearable sensors represents the future trajectory of perioperative medicine.
Keywords	Artificial Intelligence, Closed-loop Anaesthesia, Automated Drug Delivery, Analgesia, Machine Learning, Pharmacokinetics, Total Intravenous Anaesthesia, Reinforcement Learning, Patient Safety
Field	Medical / Pharmacy
Published In	Volume 8, Issue 3, May-June 2026
Published On	2026-05-22
DOI	https://doi.org/10.36948/ijfmr.2026.v08i03.79139

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Artificial Intelligence-Driven Automated Drug Delivery Systems for Analgesia and Anaesthesia in the Modern World

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