The CAM Model: An in vivo Testbed for Molecular Communication Systems

TL;DR

The paper addresses the need for realistic in vivo testbeds for molecular communication by proposing the chorioallantoic membrane (CAM) model as a versatile 3D MC platform. It develops an analytical diffusion–flow channel model based on a wrapped normal distribution to describe particle propagation in dispersive closed-loop vascular networks, and validates this framework with PBS simulations. The authors introduce parametric models for injection dynamics, transient/steady-state distribution, and liver accumulation, and fit these models to an experimental ICG dataset consisting of 69 measurements across 25 eggs, demonstrating three distinct phases of distribution. The CAM testbed and accompanying models offer a practical pathway for bridging concept and application in MC, enabling in vivo validation, design insight, and more realistic evaluation of molecular signaling strategies, while acknowledging limitations and outlining future refinements.

Abstract

Molecular communication (MC) research increasingly focuses on biomedical applications like health monitoring and drug delivery, demanding testing in realistic living environments. Elevating MC research requires developing advanced in vivo testbeds. We introduce the chorioallantoic membrane (CAM) model as the first versatile 3D in vivo MC platform. The CAM, a highly vascularized membrane in fertilized chicken eggs, is established in bioengineering, cancer research, and drug development. Its biological realism, reproducibility, and versatility make it ideal for next-generation MC testbeds, bridging proof-of-concept systems and practical applications. We comprehensively characterize the CAM model's properties and MC system relevance. Through experimental studies, we investigate fluorescent molecule distribution in the CAM's closed-loop vascular system. We derive an analytical model using the wrapped normal distribution to describe particle propagation in dispersive closed-loop systems dominated by diffusion and flow. Parametric models are developed to approximate particle dynamics in the CAM, with parameters estimated via nonlinear least squares curve fitting. A dataset of 69 regions from 25 eggs validates our models. We analyze parameter relationships and biological plausibility. Finally, we develop a parametric model for long-term particle behavior and liver accumulation in chick embryos.

Figures (22)

• Figure 1: Schematic illustration of the CAM model consisting of the chicken embryo, the yolk bag, and the CAM. Furthermore, a tumor is engrafted on the CAM (Created with BioRender.com).
• Figure 2: Photos of the ICG fluorescence intensity distribution and accumulation in the CAM model over time for a long-term experiment.
• Figure 3: Snapshots of the distribution of fluorescent molecules in the vascular system of the CAM model directly after injection via a syringe (left) and after a few seconds fully distributed (right).
• Figure 4: CAM model for tumor and distribution studies. Left: ICG injection into CAM vessels at $t = 0~min$ and distribution in the vascular system. Right: ICG is accumulated in tumor tissue after $\sim \!15~min$Ettner2024.
• Figure 5: Interpretation of the CAM model as closed-loop MC system with TX, e.g., a syringe or a tumor, several nRX, e.g., yolk bag, organs, tumor tissue, and several sRX (Created with BioRender.com).