January 16, 1991 - January 16, 2024

  • Date:17SundayJanuary 2021

    Quantitative Prediction of Nanoparticle Assembly for Personalized Nanomedicine

    More information
    11:00 - 12:00
    Prof. Yosi Shamay
    Dept Biomedical Engineering, Technion
    Department of Materials and Interfaces
    Soft Matter and Biomaterials
    AbstractShow full text abstract about Zoom Link: https://weizmann.zoom.us/j/92447973616?pwd=UWJkR...»
    Zoom Link: https://weizmann.zoom.us/j/92447973616?pwd=UWJkRWdraGFVQjdPb3ByWis1bDk2Zz09

    Development of targeted nanoparticle for personalized cancer therapeutics often requires complex synthetic schemes involving both supramolecular self-assembly and multiple chemical modifications. These processes are generally difficult to predict, execute, and control. I will describe a new method to accurately and quantitatively predict self-assembly of kinase inhibitors drug molecules into nanoparticles based on their molecular structures. The drugs assemble with the aid of new kind of excipient comprised of highly conjugated sulfated molecule into particles with ultra-high drug loadings of up to 90%. Using quantitative structure-nanoparticle assembly prediction (QSNAP) calculations and machine learning, a new algorithm was developed as highly predictive indicators of both nano-self assembly and nanoparticle size with unprecedented accuracy.