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A complementary in vivo-in silico approach to optimize nanomaterial delivery in solid tumors
Nanomaterials are increasingly used to try and improve delivery of anticancer drugs to tumors. Recent clinical trials have shown that while nanomaterials enhance specificity of the associated drugs to the tumor, the efficacy is still very low. Much work has been put into improving nanomaterial design to enhance targeted delivery, but this has only had minimal success. Here, we aim at looking at the tumor physiology to decide which tumors are most suited for nanomaterial therapy and which nanomaterial is most suited for a particular tumor type. To accomplish this, we will systematically study differently sized nanomaterials and pharmaceutical agent, investigating delivery to particular tumors. Tumors will be characterized in view of their blood flow and the ability of compounds to reach the tumors after intravenous administration. Using these data, a predictive in silico based model will be developed which will allow any clinician or researcher to determine the optimal nanomaterial formulation to target a particular tumor based on minimal input data (blood flow and vessel leakiness) that can easily be obtained through standard (pre)clinical imaging methods. The data obtained and the model generated will have a major impact on the field of nanomedicine specifically, but through its generic character, will also transform the fields of drug delivery and cancer therapy.
Date:1 Oct 2020 → Today
Keywords:Nanomedicine, Nanoparticles, Biodistribution, in silico, tumor targeting
Disciplines:Bioinformatics of disease, Medical nanotechnology, Non-clinical studies