Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2025 Jul:198:109081.
doi: 10.1016/j.compchemeng.2025.109081. Epub 2025 Mar 9.

Machine learning enabled multiscale model for nanoparticle margination and physiology based pharmacokinetics

Sahil Kulkarni  1 , Benjamin Lin  2   3 , Ravi Radhakrishnan  1   3
Affiliations

Machine learning enabled multiscale model for nanoparticle margination and physiology based pharmacokinetics

Sahil Kulkarni et al. Comput Chem Eng. 2025 Jul.

Abstract

This study presents a multiscale modeling framework for simulating and predicting the behavior and biodistribution of nanoparticles (NPs), focusing on applications such as targeted drug delivery. The framework encompasses two coupled models: (1) a DeepONet-enabled Fokker-Planck equation to model the NP drift-diffusion in the red-blood cell-free layer (RBCFL) that predicts NP margination and concentration profiles taking hematocrit and vessel radius as inputs, built on top of a hemorheological model of shear-induced blood flow and (2) a physiologically based pharmacokinetic (PBPK) model that uses the predicted concentration profiles in microvasculature to inform the biodistribution of NPs across different organ in the body.

Keywords: DeepONet; Fokker–Planck; Hematocrit; Margination; Nanoparticles; PBPK.

PubMed Disclaimer

Conflict of interest statement

Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

References

    1. Abbitt KB, Nash GB, 2001. Characteristics of leucocyte adhesion directly observed in flowing whole blood in vitro. Br. J. Haematol 112 (1), 55–63. - PubMed
    1. Alber M, Buganza Tepole A, Cannon W, Dura-Bernal S, Garikipati K, Karniadakis G, Lytton W, Perdikaris P, Petzold L, Kuhl E, 2019. Integrating machine learning and multiscale modeling—perspectives, challenges, and opportunities in the biological, biomedical, and behavioral sciences. Npj Digit. Med 2, 10.1038/s41746-019-0193-y. - DOI - PMC - PubMed
    1. Barenholz Y, 2012. Doxil®–the first FDA-approved nano-drug: lessons learned. J Control. Release 160 (2), 117–134. - PubMed
    1. Baydin A, Pearlmutter B, Radul A, Siskind J, 2018. Automatic differentiation in machine learning: A survey. J. Mach. Learn. Res 18, 1–43.
    1. Blanco E, Shen H, Ferrari M, 2015. Principles of nanoparticle design for overcoming biological barriers to drug delivery. Nature Biotechnol. 33 (9), 941–951. 10.1038/nbt.3330. - DOI - PMC - PubMed

LinkOut - more resources