Decoding microplastic toxicity on human health: navigating translational challenges using organ-on-chip models

Microplastic (MP) pollution is a serious environmental issue due to the rapid rise in plastic production and persistence of plastics in ecosystems. The inevitable exposure to MPs and reports of the presence of MPs in several tissues in our bodies are concerning amidst growing chronic illnesses. However, the precise effects of MPs on human health remain poorly understood, contributing to public apprehension in the absence of definitive mitigation strategies. Currently, in vitro two-dimensional models (2D) and in vivo animal models are used to study the adverse effects of MPs on human health. While these models have provided some insights, they suffer from various limitations such as short-term exposure, unrealistic high dosages and irrelevance to human physiology. Near-physiological in vitro models, such as organ-on-a-chip (OoC) platforms, built from three-dimensional (3D) structures with dynamic microfluidic flow, mechanical stimulation, and multicellular co-culture environments can enable the study of MP transport, cellular interactions, and organ-level toxicity more accurately. This review highlights the core concepts of MPs and NPs with respect to toxicological studies at the cellular and organ levels, the analytical challenges for detection in biological materials and their clinical interpretation. We discuss the various models developed so far and their limitations associated with human physiology and clinical impact. We explain the design considerations and principles for developing appropriate OoC models to study the effects of dose, duration and exposure pathways of MPs on human health. OoC models are promising systems that can accurately identify the impact of MPs on human health, aid in identifying the mechanisms of toxicity and serve as key platforms for testing and validating therapeutic interventions. Precise evaluation of the health effects of MPs with a mechanistic understanding is imperative for healthcare management and measured public communication.