Multiple computational modeling approaches for prediction of wound healing dynamics following pharmacologic intervention
Paper in proceedings, 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.


S. M. Rikard

Joachim Almquist

Chalmers, Biology and Biological Engineering, Systems and Synthetic Biology

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

Subject Categories

Computational Mathematics

Bioinformatics and Systems Biology

Areas of Advance

Life Science Engineering (2010-2018)

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