(279c) Computational Modeling of Cathodic Voltage Controlled Electrochemical Treatment of Biofilms in-Vivo

Computational
Modeling of Cathodic Voltage Controlled Electrochemical Treatment of Biofilms In-vivo

Amir Mokhtare¹,
Mark Ehrensberger²and Edward P Furlani^1,3

¹Dept. of
Chemical and Biological Engineering,² Dept. of Biomedical
Engineering, ² Dept. of Biomedical Engineering, ³

University at Buffalo,
The State University of New York, Buffalo NY

Email: efurlani@buffalo.edu Abstract

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.

Keywords: Biofilm induced infections, prosthetic
joint replacement, in-vivo mathematical modeling, electrochemical treatment. Results

References

[1]           M. T. Ehrensberger et al., Biomaterials, vol. 41, pp. 97,
02/ 2015.

[2]           F.
L. Hellweger et al., Nature Reviews Microbiology, vol. 14, no. 7,
pp. 461, 2016.

[3]           E.
Nilsson et al., Bioelectrochemistry, vol. 53, no. 2, pp. 213,
2001.

[4]           S.
Nodzo et al., Clinical Orthopaedics and Related Research®, vol.
473, no. 9, pp. 2856, 2015// 2015.