Trends in Immunotherapy

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AI Drives Optimization of Delivery Systems Engineered for Precise and Effective Immune-Based Solutions

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https://doi.org/10.54963/ti.v10i1.1401
P, D. B., Murali, S., Gnanaprakasam, C., Reenadevi, R., Madhubala, P., & Mythili, R. (2026). AI Drives Optimization of Delivery Systems Engineered for Precise and Effective Immune-Based Solutions. Trends in Immunotherapy, 10(1), 155–173. https://doi.org/10.54963/ti.v10i1.1401
Volume 10, Issue 1 (2026)
Copyright (c) 2026 Divya Bharathi P, S. Murali, C. Gnanaprakasam, R. Reenadevi, P. Madhubala, R. Mythili
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Authors

  • Divya Bharathi P

    Department of Information Technology, SRM Madurai College for Engineering and Technology, Pottapalaiyam 630612, India
  • S. Murali

    Department of Computer Science, M. G. R College, Hosur 635130, India
  • C. Gnanaprakasam

    Department of Artificial Intelligence and Data Science, Panimalar Engineering College, Chennai 600123, India
  • R. Reenadevi

    Department of CSE, Sona College of Technology, Salem 636005, India
  • P. Madhubala

    Department of Computer Science and Engineering, Bharathiyar Institute of Engineering for Women, Salem 636112, India
  • R. Mythili

    Department of Information Technology, SRM Institute of Science and Technology, Ramapuram, Chennai 600089, India

Received: 14 July 2025; Revised: 14 August 2025; Accepted: 4 September 2025; Published: 12 February 2026

In oncology, the development of intelligent, biocompatible nanocarriers is pivotal for advancing targeted immunotherapy. This study presents a protein-binding immunotherapy model that leverages targeted immune proteins, such as interleukins, interferons, and checkpoint inhibitors, integrated with a drug delivery system (DDS). The proposed Zn²⁺-glutamic acid (Glu) nanocarrier, optimized via the AI-based DeepChem platform, demonstrated strong therapeutic potential for cancer treatment. Computational analysis revealed high coordination stability of the Zn²⁺-Glu complex (binding energy: −42.8 kcal/mol) and notable protein-binding affinity to interleukin-2 (IL-2) (7.9 ± 0.3 pKd) using a graph convolutional network model. The nanocarrier achieved efficient protein encapsulation (85.6 ± 2.2%), pH-sensitive release (68.4 ± 1.7% at pH 6.5 over 12 h), and favorable solubility (log S = −1.8). Non-toxicity prediction indicated 92% safety with a ROC-AUC of 0.89. Immunological assays showed a 3.5-fold increase in CD8⁺ T-cell activity, with nanoparticle stability confirmed by a zeta potential of −22.5 mV and PDI of 0.18. Additional benefits included fluorescence traceability at 650 nm and a 2.3-fold increase in systemic half-life, supporting its theranostic capability. Importantly, the Zn²⁺-Glu platform exhibited immunomodulatory and anti-inflammatory properties, suggesting potential to enhance chemotherapy tolerance by reducing systemic inflammation and minimizing immune-related adverse effects. Integrating bioactive components, such as Moringa Leaf Extract (MLE), could further enhance immune cell function while mitigating chemotherapy-induced immunotoxicity. Overall, the Zn²⁺-Glu nanocomposite offers a scalable, non-toxic, and site-specific DDS, positioning it as a promising next-generation protein-derived immunotherapeutic agent.

Keywords:

Drug Delivery System (DDS) Immunotherapy Artificial Intelligence (AI) Deep Chem Protein Binding

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