Computational Model to Predict Tissue Concentration of Drugs Delivered via Intravital Fluid Exchange Devices

The microcirculation is capable of precise blood flow regulation enabling fine control over the distribution of oxygen (O 2 ) to tissues in the body. The objective is to determine the role of capillaries in sensing and reporting local O 2 concentration within tissue to upstream arterioles. It is hypothesized that red blood cells (RBCs) release ATP into the vessel lumen following O 2 desaturation; ATP in the plasma binds to purinergic receptors on the endothelium triggering a signalling cascade that leads to a conducted vasodilatory response. Luminal application of ATP is known to initiate conducted dilation in arterioles yet whether or not this conducted response is present in capillaries has yet to be demonstrated. To investigate this mechanism of vascular control, we developed gas and liquid microfluidic devices for use in intravital video microscopy experiments to enable the local control of gases and agonists in skeletal muscle. These devices consist of a microfluidic flow channel interfaced with a glass slide with a laser cut micro‐outlet to allow exchange between the device and skeletal muscle during in vivo experiments. Experimentally, the gas exchange device was used to control the spatial distribution of O 2 in the tissue to cause a highly localized hypoxic condition, to induce the release of ATP from RBCs. The liquid device was used to introduce ATP to a localized region of the capillary bed to stimulate ATP mediated mechanisms downstream. Further, we used acetylcholine (ACh) and phenylephrine (PE) as positive and negative controls, respectively. All animal protocols were approved by Memorial University’s Institutional Animal Care Committee. To quantify the local distribution of solutes in skeletal muscle we developed a transient, 3D transport model to predict the concentration of solutes applied experimentally in skeletal muscle. The transport equation was discretized and solved in parallel on a graphics processing unit. The computational model predicts highly localized spatial distributions of these solutes. As expected, the highest concentration of simulated solutes was at the surface of the tissue in contact with the exchange window, with steep decreases in concentration with increasing distance from the exchange window, falling by two orders of magnitude within 240 μm of the edge of the window in both the x and y directions, and by 300 μm in the z direction (see Fig. & ). Logarithmic increases in applied drugs within the simulated microfluidic channel raise relative tissue concentrations proportionally. Predicted steady state concentrations of ACh, PE, and ATP varied due to the assumed rate of enzymatic degradation and efflux into the vasculature. In conclusion, our novel intravital video microscopy devices allow the exchange of gas and drugs to tissue to investigate the mechanisms of regulation in the microcirculation. Further, we quantified the localization of our devices using computational models of molecular transport, confirming the highly‐localized concentration gradients. Support or Funding Information Project funded through NSERC Discovery Grant to GM Fraser. Tissue model results for 15 mmHg oxygen. The colour map shows the predicted tissue concentrations with 15 mmHg oxygen at the micro‐outlet. The top panel shows the gradients at the surface of the tissue closest to the gas‐based microfluidic device, in the x–y plane. The bottom panel illustrates the tissue partial pressure of oxygen perpendicular to the x–z plane centred at the middle of the micro‐outlet. Figure 1 Tissue model results for adenosine triphosphate 10 −4 M. The log scale colour map shows predicted tissue concentrations with 10 −4 M adenosine triphosphate (ATP) at the micro‐outlet. The top panel shows the gradients at the surface of the tissue at the micro‐outlet. The bottom panel illustrates tissue ATP levels in the x–z plane centred on the micro‐outlet. ATP levels within the volume were above 3.47 × 10 −7 M due to the initial assumption of blood ATP concentration. Figure 2

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