arXiv (All)
open access
Decoding Extrahepatic Targeting of Lipid Nanoparticles with Interpretable Machine Learning
Lipid nanoparticles (LNPs) have transformed RNA medicine, yet their clinical utility remains constrained by predominant hepatic accumulation after systemic administration. Redirecting LNPs to extrahepatic tissues requires understanding of how lipid chemistry and formulation composition jointly gover
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Extrahepatic Gene Editing In Vivo Using Organic Solvent‐Free Lipid Nanoparticles#213176
- Machine learning reshapes the paradigm of nanomedicine research.#371675
- Charge-switching ionizable lipids lower the toxicity of lipid nanoparticles#922243
- Sub-chronic exposure to nanoplastics in vitro disrupts hepatic lipid homeostasis in human hepatocytes#274769
- Decoding Undesirable Inflammatory Responses of Nucleic Acid-Delivering Lipid Nanoparticles.#285007
Record · ID 1011446
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive