Ultrasound-guided drug and gene delivery (USDG) enables controlled and spatially precise delivery of drugs and macromolecules, encapsulated in microbubbles (MBs) and submicron gas vesicles (GVs), to target areas such as cancer tumors. It is a non-invasive, high precision, low toxicity process with drastically reduced drug dosage. These advantages open doors to numerous biomedical applications, from sonothrombolysis to blood–brain barrier opening. However, the progress and deployment of this technology is subject to extensive experimentation and heuristics. This empiricism entails severe risks and limitations for clinical applications and delays the adoption of this potent technology.
The project aims to design a virtual research environment to assist medical applications of USDG and imaging. The project focus are the encapsulated microbubbles and gas vesicles with submicron size that are used as ultrasound contrast agents and can also act as drug carriers. Detailed knowledge of their physical properties is essential in ultrasound-mediated therapeutic applications, which are driven by combined effects of ultrasound and contrast agents in cavitation and sonoporation. Today, our understanding and quantification of these processes is limited. State-of-the-art continuum models of the contrast agents cannot incorporate the critical details such as varying thickness of the encapsulating shell. Furthermore, they do not allow for simulations of several contrast agents that interact at a submicron/mesoscopic level. This represents a severe limitation since the contrast agents’ dynamic interaction with the direct environment substantially modifies their cavitation behavior and in turn the outcome of drug delivery. The goal of this research project is to develop new, data-informed mesoscopic models of ultrasound contrast agents to accurately model their rheological and acoustic behavior that critically affects the technology of USDG. The proposed models of contrast agents will allow for computational studies that will provide the optimal experimental range of ultrasound parameters such as intensities, frequencies, beam collimation, and duration of ultrasound exposure for biomedical applications.
The grand result of MULTraSonicA will be a computational framework that would allow for controlled testing, data-driven quantification of uncertainties in design parameters and a rational optimization of experimental US parameters. The proposed virtual environment (the new mesoscopic models of MBs and GVs and virtual US machine) will assist and advance USDG across biomedical applications such as treatment of various diseases, e.g. cancers, inflammatory
diseases, cardiovascular diseases such as thrombosis, stroke and myocardial infarction.
