30 May Spatiotemporal measurement of concentration-dependent diffusion coefficient
With advancements in biotechnology, the production of highly concentrated antibody formulations for subcutaneous injections is becoming common in the biopharmaceutical industry. Measurement of transport and more importantly diffusion of proteins in tissues is essential in drug development.
There is evidence suggesting that the assumption of the constant diffusion coefficient is not valid for high-concentration protein suspensions, and protein diffusion is, in fact, a function of the concentration of the proteins. However, there is no reliable method for measuring the concentration-dependent diffusion coefficient.
We introduce a novel image analysis method to measure the concentration-dependent diffusion coefficient. We utilized both temporal and spatial changes of the concentration field from the sequence of images and numerically solves the general form of Fick’s second law using radial basis functions (RBF). We termed this method the Concentration Image Diffusimetry (CID).
This methodology works for low and high molecule concentrations and different sizes, such as proteins, quantum dots, particles, etc. We assessed CID’s performance using synthetically generated images and show it achieves less than 2% error. We validated CID with FRAP experimental images and showed that CID agrees with established FRAP algorithms for samples with a constant diffusion coefficient. Finally, we demonstrate the application of CID to experimental datasets of a concentration gradient-driven protein diffusion into a tissue replicate.