Author(s):
Pinki Verma, Pallavi V, Vandana. K.A., Soundarya M, Hani. M.
Email(s):
vermapinki05@gmail.com
DOI:
10.52711/2231-5659.2026.00056 
Address:
Pinki Verma1*, Pallavi V2, Vandana. K.A.2, Soundarya M2, Hani. M.2
1Associate Professor, Department of Pharmacology, Aditya Bangalore Institute of Pharmacy Education and Research, Rajiv Gandhi University of Health Sciences, Yelahanka, Bengaluru, 560064 Karnataka, India.
2Research Scholar, Department of Pharmacology, Aditya Bangalore Institute of Pharmacy Education and Research, Rajiv Gandhi University of Health Sciences, Yelahanka, Bengaluru, 560064 Karnataka, India.
*Corresponding Author
Published In:
Volume - 16,
Issue - 4,
Year - 2026
ABSTRACT:
Background: Autoimmune diseases (ADs), affecting 3-5% of the global population, represent a profound health burden characterized by chronic inflammation and significant unmet therapeutic needs. Current management strategies, often relying on broad immunosuppression, are frequently ineffective and associated with substantial side effects. The circadian rhythm, a master regulator of physiology, exerts precise control over immune function. Chronotherapy—aligning treatment with biological rhythms—has demonstrated promise in improving efficacy and reducing toxicity, as evidenced by timed glucocorticoid administration in rheumatoid arthritis. However, existing approaches are limited by their reliance on population-averaged rhythms, ignoring individual variability in circadian phase. Main Body: This review synthesizes evidence establishing the circadian-immune axis, from molecular clock mechanisms to rhythmic control of innate and adaptive immunity. We present clinical evidence for chronotherapy across ADs, including inflammatory bowel disease and psoriasis, highlighting how symptoms and pathophysiology exhibit predictable daily patterns. The emergence of wearable technology provides the engine for personalization, enabling continuous, real-time monitoring of circadian phase (via actigraphy, temperature) and disease-specific biomarkers (heart rate variability, skin temperature, sleep). We propose a framework for closed-loop chronotherapy algorithms that integrate these multi-modal data streams. Using machine learning for digital phenotyping and flare prediction, these algorithms can dynamically optimize drug timing to coincide with an individual's peak disease activity, creating a personalized therapeutic schedule. The architecture involves data integration, feature extraction, predictive modelling, and a human-in-the-loop dosing system that prioritizes clinician oversight and patient agency. Conclusion: The convergence of circadian biology, digital health, and artificial intelligence heralds a new paradigm for autoimmune disease treatment. Personalized chronotherapy represents a transformative shift from reactive to predictive and pre-emptive medicine. Despite facing translational challenges-including technical validation, algorithmic fairness, regulatory hurdles, and ethical considerations approach offers a compelling path towards restoring immune homeostasis and significantly improving long-term patient outcomes.
Cite this article:
Pinki Verma, Pallavi V, Vandana. K.A., Soundarya M, Hani. M.. Personalized Chronotherapy Algorithms for Autoimmune Diseases: Harnessing Wearable Biomarkers and Circadian Medicine. Asian Journal of Research in Pharmaceutical Sciences. 2026; 16(4):389-8. doi: 10.52711/2231-5659.2026.00056
Cite(Electronic):
Pinki Verma, Pallavi V, Vandana. K.A., Soundarya M, Hani. M.. Personalized Chronotherapy Algorithms for Autoimmune Diseases: Harnessing Wearable Biomarkers and Circadian Medicine. Asian Journal of Research in Pharmaceutical Sciences. 2026; 16(4):389-8. doi: 10.52711/2231-5659.2026.00056 Available on: https://www.ajpsonline.com/AbstractView.aspx?PID=2026-16-4-9
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