Local implantable drug delivery system (IDDS) can be used as an effective adjunctive therapy for solid tumor following thermal ablation for destroying the residual cancer cells and preventing the tumor recurrence. In this paper, we develop comprehensive mathematical pharmacokinetic/pharmacodynamic (PK/PD) models for combination therapy using implantable drug delivery system following thermal ablation inside solid tumors with the help of molecular communication paradigm. In this model, doxorubicin (DOX)-loaded implant (act as a transmitter) is assumed to be inserted inside solid tumor (acts as a channel) after thermal ablation. Using this model, we can predict the extracellular and intracellular concentration of both free and bound drugs. Also, Impact of the anticancer drug on both cancer and normal cells is evaluated using a pharmacodynamic (PD) model that depends on both the spatiotemporal intracellular concentration as well as characteristics of anticancer drug and cells. Accuracy and validity of the proposed drug transport model is verified with published experimental data in the literature. The results show that this combination therapy results in high therapeutic efficacy with negligible toxicity effect on the normal tissue. The proposed model can help in optimize development of this combination treatment for solid tumors, particularly, the design parameters of the implant.
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 dualrelease 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.
The paper deals with modelling of propagation medium for molecular communication, which consist of composite biological environments with multiple regions each with distinct diffusion properties for the understanding of the transport of information molecules. For this, we propose a generalized analytical approach for modelling a composite, diffusive, molecular communication channel for arbitrary placement of the transmitting and receiving nano-machines. Using this approach, we derive a generalised closed-form expression for the channel impulse response of a three dimensionally (3D) diffusive medium having multiple regions with an aim to act as a benchmark solution to validate simulations as well as to optimize the design of molecular communication systems. The pulse peak amplitude, pulse peak time and pulse width are derived to evaluate the system performance. In addition, a particle-based simulator for modelling a diffusive medium with multiple regions under three-dimensional diffusion is proposed and validated with the analytical results. It is shown that the channel impulse response and other communication metrics are significantly affected by the diffusion coefficients, regions thickness, properties of region interfaces as well as the positions of transmitter and receiver nano-machines with respect to the interfaces.
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