Computational modeling of cathodic voltage controlled electrochemical treatment of biofilms in-vivo

The last few decades have witnessed a proliferation in the use of prosthetic implants. Chronic bone and joint related disorders such as osteomyelitis, septic arthritis, etc. are widespread and can have a devastating impact on quality of life. Consequently, the use of total joint arthoplasty (TJA) has grown steadily as a life enhancing procedure. Although successful joint replacement restores functionality and provides pain relief, prosthetic joint infections (PJIs) can be a devastating outcome of orthopedic surgery and can impose horrendous physical burdens on individual patients and financial stress on the health industry as a whole. PJIs are often caused by aggregated communities of bacteria known as bacterial biofilms, which tend to be incredibly resistant to antibiotics. As a result, new methodologies are needed to efficiently treat biofilm-based PJIs in-vivo. In this regard, electrochemical treatment of the infected implants is among the most promising strategies for the eradication of surface-based biofilm infections. Cathodic voltage controlled electrical stimulation (CVCES), is a recently developed electrochemical approach that has proven to be effective in the treatment of biofilm-based PJIs. Analysis of in-vivo assays have revealed that CVCES combined with conventional antibiotic drugs can lead to complete treatment of the infections without any histological damage to the surrounding tissue. However, many fundamental aspects of this treatment are unknown and rational design towards optimization is lacking. In this presentation we introduce a one-dimensional (1D) computational modeling framework to simulate the electrochemical behavior of an in-vivo CVCES system. We use dilute solution theory (ionic interaction are neglected) for determining the electrochemical potential of ionic species in the system and solve the Nernst-Plank equations along with Maxwell's equations to predict the toxic (to bacteria) species concentration speciation and electric potential. Water-based electroneutrality is used as a simplifying assumption to facilitate numerical convergence. In addition, Butler-Volmer electrochemical surface reaction kinetics are assumed at the surface of the working electrode and as boundary conditions for the models. We have used our experimental current-voltage scanning data to identify the dominant electrochemical surface reactions and have extracted transfer coefficients and exchange current densities required to characterize the reactions. The surrounding tissue, i.e. the electrolyte medium in the in-vivo experiments, was approximated by the dilute solution of sodium chloride. Moreover, the most important buffer systems inside the tissue, namely the bicarbonate buffer system and buffer capacity of proteins and organic phosphates, were introduced in the form of homogeneous reactions. Hydrogen evolution and oxygen reduction electrochemical reactions are assumed at the working electrode surfaces and characterized by voltage current scanning data. Both experimental and mathematical modeling results showed that oxygen reduction surface reaction become diffusion limited after few minutes and only contribute a small amount to the total current density at the electrode surface. Simulation results also elucidate how buffering capacity of the tissue would counteract the diffusion of hydroxide ions in the tissue. The mathematical model also provides the temporal-spatial variation of the both current-density and pH profiles that are very difficult to obtain in experiments. The simulation results are in an acceptable quantitative range with the experimental results. The modeling framework can be extended to higher dimensions to represent more realistic examples such as human knee or hip implants. Such models can be utilized to optimize the electrode configurations and operation parameters.