(191as) Modeling Chemical Transport in PDMS-Based Organ-on-Chip Microsystems

Organ-on-chip microsystems are being used to evaluate chemical responses to human cells cultured in appropriate 3D heterotypic environments. These microsystems are often fabricated from polydimethylsiloxane (PDMS), which has high affinity for small hydrophobic molecule creating undesirable change in chemical dose response curves and timing of exposure to cells. Here, we modeled the chemical adsorption onto PDMS surfaces in an organ-on-chip microsystem using computational fluid dynamics (CFD). The goal of this model is to predict the cultured cells’ actual time-dependent chemical exposure within a PDMS fabricated microsystem. It was possible to establish quantitative relationships for chemical adsorption onto PDMS surfaces through fitting spectroscopic data to a microscale model of chemical binding kinetics with PDMS and extracting time-dependent adsorption coefficients, saturation amount, and forward and reverse rate constants. Experimental kinetic rate constants were used to model adsorption due to continuous and bolus exposure of three chemicals and subsequent chemical transport in a hypothetical microsystem. These chemicals were hexazinone having no interaction with PDMS surfaces (the octanol-water partition coefficient, log P = 1.85), ethofumesate having reversible binding with PDMS surfaces (log P = 2.7), and propiconazole with strong affinity to PDMS surfaces (log P = 3.72). From this analysis, we determined that timing is critical for delivery of chemicals that reversibly bind to PDMS in order to avoid over- or under-dosing cells. For such chemicals, a bolus dose at the inlet may translate into an extended exposure for cells in the device due to delayed release of the chemical from PDMS surfaces. In addition, for chemicals with strong affinity to PDMS, the actual exposure may be an order of magnitude less than the nominal inlet concentration. The model can be used in a forward direction to properly evaluate the effect of chemicals by accurately quantifying cellular exposures or in a backward direction to achieve desired exposures by optimizing inlet dosing strategies.