Multiscale computational models of complex biological systems

Abstract

Integration of data across spatial, temporal, and functional scales is a primary focus of biomedical engineering efforts. The advent of powerful computing platforms, coupled with quantitative data from high-throughput experimental methodologies, has allowed multiscale modeling to expand as a means to more comprehensively investigate biological phenomena in experimentally relevant ways. This review aims to highlight recently published multiscale models of biological systems, using their successes to propose the best practices for future model development. We demonstrate that coupling continuous and discrete systems best captures biological information across spatial scales by selecting modeling techniques that are suited to the task. Further, we suggest how to leverage these multiscale models to gain insight into biological systems using quantitative biomedical engineering methods to analyze data in nonintuitive ways. These topics are discussed with a focus on the future of the field, current challenges encountered, and opportunities yet to be realized.

Figure 1. Diabetic Retinopathy as a Case Study in Multiscale Pathophysiology

A detailed look at how the pathogenesis of diabetic retinopathy is a function of multiple spatial scales across biology.

Figure 2. Clustergram of multiscale models as a function of biological discipline and spatial resolution

Each publication was scored as containing (1) or not containing (0) a biological scale within the described multiscale model. For each discipline, the Boolean values were summed and then normalized to the total number of publications within that category, such that the weighted heatmap is scaled from 0 to 1. For example: of the 7 publications in Vascular Biology, 5 involved Whole Cell components, resulting in a weighted score of 5/7 = 0.71. A total of 39 publications were included in this analysis.

Figure 3. Map of Modeling Techniques by Scale

Conceptual map of modeling techniques divided into continuous and discrete categories across spatial scales for which they are most suited.