Multiple computational modeling approaches for prediction of wound healing dynamics following pharmacologic intervention

S. M. Rikard, J. Almquist, A. Lundahl, K. M. Hansson, R. Fritsche-Danielson, K. R. Chien, S. M. Pierce. Biomedical Engineering Society (BMES) annual meeting, Phoenix, AZ, USA, 11-14 October 2017.


Diabetic wounds are known to have a delayed course of wound healing. We have recently demonstrated that injection of a synthetic modified RNA (modRNA) that enhances VEGF-A protein expression accelerates healing of full-thickness cutaneous wounds in db/db diabetic mice. Here, we compare two different computational modeling approaches to explore how the dosing amount and time course affect the rate of wound healing. We show that a partial differential equation (PDE) model is appropriate for questions concerning spatial resolution of healing throughout the wound, while a nonlinear mixed effect model (NLME) is more appropriate for capturing population level variations in healing rate when dealing with a sparse data set. Both models display sensitivity to varying dosing amount and timing.

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