Computational modeling of the effects of biofouling and foreign body response on continuous glucose monitors

Biofouling and eventual foreign body response are critical issues limiting the long-term performance of implantable continuous glucose monitors (CGMs). The implant is subjected to reduced blood flow in situ governed by the inflammatory response, resulting in decreased access to glucose and a decrease in sensor sensitivity (drift). In this work, a computational model of an amperometric 2^nd generation enzymatic glucose sensor is examined that incorporates the time-dependent changes in the interstitial environment due to the foreign body response (FBR). Appropriate physics are applied with respect to glucose transport from tissue, temporal foreign body response, enzyme kinetics, and measured electrochemical current. The resultant sensor performance is modeled against publicly available clinical data over a 14-day wear time, using test cases of an idealized implant that is not subjected to FBR, fibrous encapsulation with neovascularization, and fibrous encapsulation without neovascularization. The resultant sensitivity, lag-time, and sensor performance are compared against the reference clinical data. Results demonstrate that in silico modeling has utility in predicting in vivo performance, offering a vital tool for sensor design and pre-clinical optimization.