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Article ? AI-assigned paper type based on the abstract. Classification may not be perfect — flag errors using the feedback button. Tier 2 ? Original research — experimental, observational, or case-control study. Direct primary evidence. Human Health Effects Policy & Risk Sign in to save

Gaps between Laboratory Experiments and Real-World Exposure: Toxicological Assessment of Microplastics Is Based on Inadequate Evidence

Environment & Health 2026 Score: 50 ? 0–100 AI score estimating relevance to the microplastics field. Papers below 30 are filtered from public browse.
Y. Chen Y. Chen Qian Liu, Yuzhu Zhang, Q. Y. Zhou, Q. Y. Zhou, Shanjun Song, Shanjun Song, Qian Liu, Qian Liu, Qian Liu, Y. Chen Y. Chen

Summary

**TLDR:** This review of existing research found that current studies on microplastic toxicity don't match real-world conditions—most lab experiments test single types of plastic particles at high doses for short periods, while people are actually exposed to many different microplastics mixed with other pollutants over long periods of time. The authors argue we need better testing methods that mirror how people actually encounter microplastics in daily life to truly understand the health risks. This research gap makes it hard to know if microplastics are truly dangerous to human health at the levels we're actually exposed to.

The global significance of microplastic (MP) toxicity assessment is widely acknowledged. Current studies have enhanced our understanding of the mechanisms behind MP toxicity; however, most research mainly focused on the toxicity of individual MPs, overlooking the environmental complexity that arises from the diversity of MPs and the combined effects of multiple pollutants. Furthermore, a notable gap exists in research concerning low-dose and long-term exposure, which significantly limits the relevance of current toxicity data for risk assessments. To address these challenges, we suggest a more thorough and logical approach to evaluating MP toxicity, including: enhancing the harmonization of methods for detecting and quantifying MPs in various environmental and biological matrixes; leveraging AI to simulate real environmental exposures and to predict the complex interactions between MPs and other environmental factors; and combining insights from environmental science, toxicology, materials science, and other relevant fields to bridge the gap between laboratory findings and real-world conditions. Collectively, these efforts could transform fragmented data into risk intelligence, delivering actionable governance solutions for global MP challenges.

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