A similarity scaling approach for organ-on-chip devices.

Abstract

Organ-on-chip devices (OoCs) provide more nuanced insights into (patho)physiological processes of the human body than static tissue models, and are currently the most promising approach to emulating human (patho)physiology <i>in vitro</i>. OoC designs vary greatly and questions remain as to how to maximize biomimicry and clinical translatability of the <i>in vitro</i> findings. Scaling is critical, yet has largely been <i>ad hoc</i>, consisting in matching one or a few variables between the OoC and the target organ. This has limited the predictive value of OoCs. Here, we propose a systematic approach based on the principle of similitude widely used in the physical sciences, and present three case studies from the recent literature to demonstrate how the approach works. A lung-on-a-chip and a liver-on-a-chip both satisfied important similarity criteria, and therefore yielded results that were in good agreement with clinical data. A gut-liver system failed to satisfy a key criterion of kinematic similarity, and yielded unphysiological pharmacokinetic responses <i>in vitro</i>. The similarity scaling approach promises to improve markedly the design and operation of organ- and human-on-chip devices.