1Plantaxome Global Innovations, Chengalpattu, Tamil Nadu 603202, India. Email: rajeshkannanuk@gmail.com
2Department of Mathematics, College of Engineering and Technology, SRM Institute of Science and Technology, Kattankulathur, Chengalpattu, Tamil Nadu 603203, India
3Department of Nursing, Sree Balaji College of Nursing, Chromepet, Chennai, Tamil Nadu 600044, India
4Department of Research, Sri Venkateshwaraa Medical College Hospital & Research Centre, Ariyur, Puducherry 605102, India. Email: reva63@rediffmail.com
5Department of Mathematics, Dhanalakshmi College of Engineering, Tambaram, Chennai 601301, Tamil Nadu, India
6Plantaxome Global Innovations, Chengalpattu, Tamil Nadu 603202, India
7Department of Chemistry, Karpaga Vinayaga College of Engineering and Technology, Chennai, Tamil Nadu 603308, India
8Department of Biochemistry, Sree Balaji Medical College & Hospital, Bharath Institute of Higher Education Institute (BIHER University), Chromepet, Chennai, Tamil Nadu 600044, India
*Corresponding Authors: R. Rajesh Kannan Ramar, Plantaxome Global Innovations, Chengalpattu, Tamil Nadu 603202, India. Email: rajeshkannanuk@gmail.com; K Revathi, Department of Research, Sri Venkateshwaraa Medical College Hospital & Research Centre, Ariyur, Puducherry 605102, India. Email: reva63@rediffmail.com
This article focuses on using personalised methodologies in clinical practice to improve epilepsy patient outcomes and lower the risk of sudden unexpected death in epilepsy (SUDEP). Epilepsy is a chronic neurological condition that causes recurrent seizures and affects millions worldwide. Precision medicine, which aims to tailor treatment strategies based on individual patient characteristics, has emerged as a promising approach. The work discusses the use of precision medicine in epilepsy management, including personalised treatment approaches. It investigates risk stratification and prediction models for SUDEP, emphasising the significance of identifying high-risk individuals. Pharmacogenomics is important in individualised antiepileptic drug therapy because it optimises treatment selection and dosage based on genetic factors. The review also highlights the importance of lifestyle changes and patient education in improving epilepsy patient outcomes. Genetic testing is being investigated to assess the risk of epilepsy and SUDEP. Seizure detection and monitoring technologies are being investigated as valuable tools for individualised management and treatment adjustments. The review emphasises the significance of collaborative care and multidisciplinary teams in improving patient management. The field's challenges and future directions and the transition from research to clinical implementation are discussed. The review recognises the importance of addressing issues like cost-effectiveness, accessibility, and interpreting complex data generated by personalised methodologies. It emphasises the importance of ongoing research and collaborative efforts to establish personalised medicine's definitive role in epilepsy management. Overall, this review highlights the potential of personalised approaches in epilepsy and SUDEP, aiming to improve patient outcomes and optimise care in clinical practice through precision medicine. Leveraging computational and dynamical models of neural populations, this review highlights how individualized seizure dynamics can inform precision medicine strategies, guiding risk prediction, therapy selection, and timing of interventions.
Keywords: Epilepsy, SUDEP, Precision medicine, Seizure, Therapy.
How to cite this article: R. Rajesh Kannan Ramar, G. Manikandan, R. Devi, K Revathi, A Ramachandran, Vaithianathan Kaasi, M. Prabakaran, P. Sandhya, E. Logeswari, “Precision Medicine in Epilepsy: Integrating Computational Neural Dynamics for Personalized SUDEP Risk Prediction and Global Clinical Translation” Int J Drug Deliv Technol. 2026;16(11s): 337-351. DOI: 10.25258/ijddt.16.11s.32.
Source of support: Nil.
Conflict of interest: None