Green In Situ Self-Assembling Nanoparticles within Waterless Granules for Oncology Applications
Authors: Nitiraj V. Kulkarni et al.
Year:
Venue: International Conference on Sustainable Innovation with AI and ML — Pages 616–625, Atlantis Press
Publisher: Atlantis Press
Type: conference (published)
Abstract
Presents green in situ self-assembling nanoparticle approaches within waterless granules for oncology applications.
This work intersects with research areas including green synthesis, nanoparticles, self-assembly, oncology, waterless granules, sustainable, drug delivery, and cancer. It is part of the broader research portfolio of Nitiraj V. Kulkarni in the domain of peer-reviewed academic publishing.
Keywords & Topics
green synthesis, nanoparticles, self-assembly, oncology, waterless granules, sustainable, drug delivery, cancer
How to Cite
APA
Nitiraj V. Kulkarni et al. (2026). Green In Situ Self-Assembling Nanoparticles within Waterless Granules for Oncology Applications. International Conference on Sustainable Innovation with AI and ML, Pages 616–625, Atlantis Press. Atlantis Press.
IEEE
Nitiraj V. Kulkarni et al., "Green In Situ Self-Assembling Nanoparticles within Waterless Granules for Oncology Applications," International Conference on Sustainable Innovation with AI and ML, Pages 616–625, Atlantis Press, 2026.
BibTeX
@article{2026_green_nanoparticles_waterless_oncology,
title={Green In Situ Self-Assembling Nanoparticles within Waterless Granules for Oncology Applications},
author={Nitiraj V. Kulkarni et al.},
journal={International Conference on Sustainable Innovation with AI and ML},
year={2026},
publisher={Atlantis Press}
}Identifiers & Links
Last updated: 2026-01-01
Related Publications
- Optimizing Ibrutinib Bioavailability: Formulation and Assessment of Hydroxypropyl-β-Cyclodextrin-Based Nanosponge Delivery Systems — Current Research in Pharmacology and Drug Discovery, 2025
- AI-Driven Radiotherapy Solutions for Rare and Complex Cancers Using Multi-Omics Approaches — Springer Book Chapter, 2025
- Comparative Analysis of Conditional Deep Convolutional and Wasserstein GAN Architectures for Brain Tumor MRI Data Augmentation — International Conference on Sustainable Innovation with AI and ML, 2026
- Digital-Twin Modelling of the Gut Microbiome to Guide Personalized Probiotic-Drug Combinations — International Conference on Sustainable Innovation with AI and ML, 2026
- Deep Reinforcement Learning for Multi-Drug Therapy Optimization in Rare and Refractory Cancers — International Conference on Sustainable Innovation with AI and ML, 2026
- Role of AI-Powered Learning Management Systems in Supporting Teacher Development and Improving Teacher-Student Relationships — International Conference on Sustainable Innovation with AI and ML, 2026
About the Author
Nitiraj V. Kulkarni is an AI safety and cybersecurity researcher based in Pune, India, with 35+ peer-reviewed publications, 5 patents, 6 copyright registrations, and 15,000+ open datasets published on Kaggle and Zenodo. He serves as a peer reviewer for 11+ international journals and conferences. Read full profile.