Multimodal in vivo study of nanoparticle decomposition and targeting dynamcis

The use of nanoparticles to deliver drugs to tumors is now well established. Although this approach has improved therapy for a group of patients, the full potential of nanoparticles in cancer therapy remains to be explored. Exciting developments in nanotechnology have allowed for the production of a wide variety of advanced nanoparticles. One highly interesting development is the synthesis of so-called targeted nanoparticles; Particles equipped with molecules on their surface making them specifically recognise and accumulate in tumor tissue. In the development and application of such targeted nanoparticles, detailed studies to learn about and understand their in vivo behavior are essential. For example, it is not well known how fast targeted nanoparticles accumulate in tumor tissue after injection. Moreover, it is now becoming clear that certain nanoparticles readily disintegrate upon injection into the blood, resulting in drug release in the blood. As such, the drug may be released before the tumor is reached. Hence, knowledge of nanoparticle degradation and tumor targeting rates and dynamics are crucial for successful application of targeted nanoparticles. However, these dynamics remain largely unstudied, which may be compounded by the fact that suitable experimental in vivo tools to do so are lacking We have established the synthesis of innovative nanoparticles of which these dynamics can be quantitatively monitored. Combining in vivo microscopy and magnetic resonance imaging, we have also developed a unique experimental set-up which is highly suitable to study in vivo nanoparticle dynamics. This novel experimental approach has been and will be exploited to study degradation and targeting dynamics of our nanoparticles at an unprecedented level of detail. Importantly, this will provide general knowledge applicable to a variety of targeted therapies. We have now shown that we can tune NP integrity in vivo by varying NP composition. We anticipate to further fine-tune the design of our nanoparticles and increase their value in the battle against cancer.

In the field of nanomedicine, the in vivo application of nanoparticles (NPs) for biomedical purposes is widely studied. Although crucially important for successful application, in vivo NP decomposition and targeting kinetics remain largely unknown. This c an be explained by the fact that appropriate experimental tools to study such dynamics are lacking. Therefor, innovation of improved methodology and technology to study such dynamics will have a broad impact on the nanomedicine research community. Detaile d, quantitative knowledge of these dynamics is expected to allow for tailoring of NP properties to a broad range of specific in vivo applications, resulting in improved diagnostics and therapy in a variety of diseases. We will develop two innovative NPs o f which decomposition and targeting kinetics can be quantitatively monitored. These NPs will be developed under the supervision of WJM Mulder during a 9 month visit to his lab in New York. One of the agents has been developed already, whereas the second n eeds optimization. As the envisioned NPs are highly advanced, optimization of this second agent will be challenging. However, this is not crucial for the success of this project as semi-quantitative alternatives are available. To monitor the dynamics we w ill employ and develop advanced state-of-the-art dynamic intravital microscopy and magnetic resonance imaging (MRI). Suitable compartment modeling of the dynamic data by our international collaborator HBW Larsson will allow for quantification of targeting dynamics. This highly novel multimodal experimental set-up will provide a broad and quantitative understanding of NP decomposition and targeting dynamics at both cellular as well as the whole tumor level. Importantly, by incorporating dynamic MRI in our set-up we will obtain new insights in how the observed dynamics affect image contrast and as such interpretation of clinically relevant molecular imaging data.