Decoding Extrahepatic Targeting of Lipid Nanoparticles with Interpretable Machine Learning

arXiv:2609.17721 · q-bio.QM, cs.CE, cs.LG · Submitted 2026-09-15 · Read on arXiv

q-bio.QM, cs.CE, cs.LG

Submitted: 2026-09-15

Updated: 2026-09-15

Code: https://github.com/AsalMehradfar/lnp-extrahepatic-targeting

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• AUC — 20× in this paper · explained in 2 episodes
• Calibration — 9× in this paper · explained in 7 episodes
• Accuracy — 8× in this paper · explained in 1 episode
• Interpretability — 6× in this paper · explained in 15 episodes
• Regularization — 6× in this paper · explained in 3 episodes
• SHAP values — 3× in this paper · explained in 2 episodes
• Aggregation — 2× in this paper · explained in 1 episode
• Predictive Modeling — 2× in this paper · explained in 2 episodes
• Benchmarking — 1× in this paper · explained in 3 episodes
• External Validation — 1× in this paper · explained in 2 episodes
• Generalizability — 1× in this paper · explained in 6 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• Mechanistic interpretability — 1× in this paper · explained in 2 episodes
• Robustness — 1× in this paper · explained in 5 episodes

Sources

• Machine Learning-guided Lipid Nanoparticle Design for mRNA Delivery
• A Machine Learning Benchmarking Framework for Lipid Nanoparticle Transfection Efficiency Prediction

Related papers

• A likelihood-based framework for simultaneously learning both noise and growth dynamics using biologically-informed neural networks
• Automated Lesion Segmentation of Stroke MRI Using nnU-Net: A Comprehensive External Validation Across Acute and Chronic Lesions
• Resolving satellite-in situ mismatches in Net Primary Production using high-frequency in situ bio-optical observations in the subpolar Northwest Atlantic
• easyplater: The easy way to generate microplate designs deconvolved from multivariate clinical data
• Essential Workers at Risk: An Agent-Based Model (SAFE-ABM) with Bayesian Uncertainty Quantification
• OmniBioTwin: A System-of-Twinned-Systems Framework for Health Digital Twins