Bioinformatics-Guided Optimization of Nanoparticle-Drug Combinations for Enhanced Proton Therapy: A Multi-Parameter Synergy Analysis of Microwave-Synthesized Metal Oxide Nanoparticles in Non-Small Cell Lung Cancer Treatment

Authors

  • David Aphkhazava PhD, Professor of Biochemistry, University of Georgia, Tbilisi Georgia, Professor, University Unilevel, Tbilisi, Georgia, Orcid: https://orcid.org/0000-0001-6216-6477
  • Archil Chirakadze PhD, Georgian Technical University Institute "Techinform", Tbilisi, Georgia, Georgian Technical University Institute of Cybernetics, Tbilisi, Georgia , Ivane Javakhishvili Tbilisi State University Institute of Physics, Tbilisi, Georgia
  • Nodar Mitagvaria Ivane Beritasvili Center of Eperimental Biomedicine, Tbilisi, Georgia
  • Neli Makhviladze Georgian Techical University, Tbilisi, Georgia
  • Teimuraz Chubinishvili Georgian Techical University, Tbilisi, Georgia
  • Levan Gulua PhD, Professor, Head of bachelor program of Biomedicine at University of Georgia, Tbilisi, Georgia
  • Akaki Sarishvili Professor, University Unilevel, Tbilisi, Georgia
  • Nina Inauri Assistant Professor, Tbilisi State University (TSU), Tbilisi, Georgia
  • Nino Chichiveishvili MD, University Unilevel, Tbilisi, Georgia
  • Manana Makharadze Prof. David Agmashenebeli University of Georgia, Tbilisi, Georgia.
  • Mzia Tsiklauri PhD, Affiliated Professor of the Medical Programs of Gr.Robakidze University, Microbiology, Immunology, Virology, Infection Control.Invited Professor of the Medical Programs of Alte University, Tbilisi, Georgia. Invited Professor of the Medical Programs of Caucasus International University, Laboratory Medicine, Tbilisi, Georgia. Member of the Georgian Immunologists Association, Member of the Accreditation Council of the Quality Development, Center of the Ministry of Education of Georgia
  • Lolita Shengelia PhD, Invited lecturer of Georgian National University, Tbilisi, Georgia; Invited lecturer of Georgian American University, Tbilisi, Georgia
  • Nodar Sulashvili MD, PhD, Doctor of Pharmaceutical and Pharmacological Sciences In Medicine, Invited Lecturer (Professor) of Scientific Research-Skills Center at Tbilisi State Medical University; Professor of Medical and Clinical Pharmacology of International School of Medicine at Alte University; Professor of Pharmacology of Faculty of Medicine at Georgian National University SEU, Associate Affiliated Professor of Medical Pharmacology of Faculty of Medicine at Sulkhan-Saba Orbeliani University; Associate Professor of Medical Pharmacology at School of Medicine at David Aghmashenebeli University of Georgia; Associate Professor of Biochemistry and Pharmacology Direction of School of Health Sciences at the University of Georgia. Associate Professor of Pharmacology of Faculty of Dentistry and Pharmacy at Tbilisi Humanitarian Teaching University; Tbilisi, Georgia; Orcid: https://orcid.org/0000-0002-9005-8577.
  • Giorgi Palavandishvili Georgian Techical University, Tbilisi, Georgia
  • Khtuna Tserodze Georgian Techical University, Tbilisi, Georgia

Keywords:

Bioinformatics, Non-small cell lung cancer (NSCLC), Nanoparticle synergy, Microwave synthesis, Copper oxide nanoparticles, Zinc oxide nanoparticles, Proton therapy enhancement, Selectivity index optimization, Super-additive interactions, MTT assay, Annexin V apoptosis, Drug repurposing, Combinatorial screening, In silico modeling, Acute toxicity testing, Gemcitabine-cisplatin, Metal oxide nanoparticles, Therapeutic window optimization, Multicomponent drug formulations,, Cancer nanomedicine

Abstract

Background: Non-small cell lung cancer (NSCLC) remains a leading cause of cancer mortality, necessitating innovative therapeutic strategies that enhance selectivity while minimizing systemic toxicity. The integration of nanoparticles with conventional chemotherapy and proton therapy presents a promising avenue, yet optimal combination strategies remain poorly characterized.

Objective: This study employed a systematic bioinformatics-guided approach to identify and characterize synergistic combinations of microwave-synthesized metallic nanoparticles (CuO, ZnO, Ni-Cu, AgₓLa₁₋ₓMnO₃, and Fe₃O₄-decorated h-BN nanosheets) with FDA-approved chemotherapeutic agents (gemcitabine, cisplatin, carboplatin, paclitaxel, tepotinib, osimertinib, and amivantamab) for NSCLC treatment enhancement.

Methods: Over 125 multicomponent formulations were synthesized using high-frequency microwave reactors (1500W) and systematically evaluated through: (1) in vitro cytotoxicity assessment on A549 lung carcinoma and NHDF normal fibroblast cell lines using MTT proliferation and Annexin V-FITC/PI apoptosis assays; (2) computational optimization of a novel composite Selectivity Index (SVA = √[SV × SA]) integrating anti-proliferative (SV) and apoptotic (SA) parameters; (3) in vivo acute toxicity profiling in chick embryos and Wistar rats using multi-parameter behavioral and physiological monitoring; (4) statistical modeling of concentration-dependent synergy patterns to identify super-additive interactions.

Results: The bioinformatics-optimized combinations demonstrated 3-7-fold superior selectivity compared to monotherapies and current standard-of-care regimens. Notably, CuO nanoparticles exhibited non-monotonic, concentration-dependent synergistic enhancement (peak efficacy at 2000 mg/mL), attributed to super-additive interactions rather than direct cytotoxic effects. ZnO nanoparticles showed approximately 20% greater efficacy enhancement than CuO. Gemcitabine-cisplatin combinations fortified with optimized nanoparticle concentrations achieved 8.7-15.2-fold improvement in therapeutic value (efficacy/cost ratio). Acute toxicity indices revealed 1.5-1.8-fold lower systemic toxicity for nanoparticle-enhanced combinations compared to individual drug components, with no significant embryonic or neurological adverse effects at therapeutic concentrations.

Conclusion: This bioinformatics-driven screening methodology successfully identified nanoparticle-drug combinations with unprecedented selectivity profiles for NSCLC treatment. The non-monotonic synergy patterns underscore the critical importance of computational dose optimization in nanomedicine. These formulations represent promising candidates for proton therapy enhancement, warranting translational validation in preclinical xenograft models and dosimetric planning studies.

Significance: The integration of computational selectivity modeling with systematic in vitro/in vivo validation establishes a reproducible framework for rational design of nanoparticle-augmented cancer therapeutics, potentially accelerating clinical translation through drug repurposing strategies.

Published

2026-02-23

How to Cite

David Aphkhazava, Archil Chirakadze, Nodar Mitagvaria, Neli Makhviladze, Teimuraz Chubinishvili, Levan Gulua, Akaki Sarishvili, Nina Inauri, Nino Chichiveishvili, Manana Makharadze, Mzia Tsiklauri, Lolita Shengelia, Nodar Sulashvili, Giorgi Palavandishvili, & Khtuna Tserodze. (2026). Bioinformatics-Guided Optimization of Nanoparticle-Drug Combinations for Enhanced Proton Therapy: A Multi-Parameter Synergy Analysis of Microwave-Synthesized Metal Oxide Nanoparticles in Non-Small Cell Lung Cancer Treatment. Foundations and Trends in Research, (12). Retrieved from https://ojs.scipub.de/index.php/FTR/article/view/7909

Issue

No. 12 (2026): Foundations and Trends in Research

Section

Biological Sciences

License

Creative Commons License

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.