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Local delivery of anticancer drug in tumor using miniaturized implants over a prolonged period of time is a powerful treatment strategy that provides lower toxicity and higher drug bioavailability compared to conventional systemic chemotherapy. Prediction of anticancer drug distribution in tumor following implantation of the drug implant is necessary to improve and optimize the implantable drug delivery systems (IDDSs). In this paper, we develop mathematical and stochastic simulation models for the prediction of spatiotemporal concentration of anticancer doxorubicin following implantation of a dual-release implant in an isolated tumor microenvironment (TME). Our model utilizes mathematical convolution of the channel impulse response (CIR) with the drug release function based on the abstraction of molecular communication. The derived CIR can be used to obtain drug concentration profile in the surrounding tissue for various release profiles and different anticancer drugs. We derive closed-form analytical expression for anticancer drug concentration. The required release rates are obtained by fitting the experimental data on dual-release implant available in the literature to a mathematical expression. In addition, we also present a particle-based stochastic simulator and compare the results with those predicted by the analytical model. The accuracy of predictions by both the models is further verified by comparing with the published experimental data in the literature. Both the proposed models can be useful for the design optimization of the implantable drug delivery systems (IDDSs) in tumors and other tissues and can potentially reduce the number of animal experiments thus saving cost and time.

Modelling of Implantable Drug Delivery System in Tumor Microenvironment Using Molecular Communication Paradigm