Exposing gaps in cannabis safety testing across US states

Regional (in)Consistency and Comparability of Cannabis Laboratory Testing: A Statistical Exploration of Total Yeast and Mold.

Clinical therapeutics • • Moderately Relevant
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AI Summary

This study examines a critical but often overlooked aspect of cannabis safety: consistency in laboratory testing for yeast and mold contamination across different US states. Researchers obtained testing data from six states (Maryland, Massachusetts, Michigan, New Jersey, Nevada, and Rhode Island) and discovered significant inconsistencies in how states measure and regulate microbial contamination. Using statistical modeling, they found that lognormal distributions better predicted contamination patterns than other models, particularly because they could capture both the proportion of clean products and the risk of highly contaminated batches. Notably, states with higher regulatory thresholds (action limits) for acceptable contamination showed better statistical fit—suggesting these states may have more consistent testing practices or different contamination profiles.

The research reveals an important public health concern: testing standards vary dramatically between states, meaning the same cannabis product could pass safety testing in one state but fail in another. This inconsistency undermines consumer protection and makes cross-state comparisons nearly impossible. The study demonstrates that regulatory alignment is essential for ensuring product safety and market transparency, as different states are essentially operating under different safety standards. The findings suggest that policymakers need to work toward harmonized testing protocols and standards—a practical framework the authors provide to support this goal.

For cannabis consumers and industry stakeholders, this research highlights why laboratory testing alone isn't enough: the standards themselves need to be consistent and evidence-based across jurisdictions. As cannabis markets continue to expand and become more interstate-oriented, the need for standardized testing procedures grows more urgent. The study provides a concrete tool that regulators and laboratories can use to improve their practices and ultimately protect consumer health more effectively.

📄 Original Abstract

Independent laboratory testing of cultivated cannabis is essential for ensuring product quality and protecting consumer health. While individual US states have collected extensive laboratory testing data from their medical and adult-use cannabis markets, a comprehensive, cross-state analysis remains lacking. To address this gap, we apply a design science research methodology to develop a structured framework for analyzing and comparing cannabis laboratory testing practices across decentralized regulatory environments. With data obtained through Freedom of Information Act requests from Maryland, Massachusetts, Michigan, New Jersey, Nevada, and Rhode Island, we construct a statistical artifact that models the total yeast and mold contamination profile within cannabis flower products utilizing an innate characteristic of the state-reported lab data: overdispersion. Lognormal models showed superior ability to capture the full breadth of total yeast and mold counts, from the proportion of uncontaminated sampling to the probability of high contamination events in state data, compared with the generalized gamma distribution. State data with higher regulatory action limits had generally better goodness of fit, both statistically and visually, to the proposed models than their lower-limit state counterparts. This analysis reveals inconsistencies in testing outcomes and protocols, offering a clearer understanding of how regulatory differences impact public health protections and market transparency. By leveraging design science principles, this research produces a practical tool that supports evidence-based decision-making. The resulting framework is not only valuable to laboratories and industry stakeholders but also highly relevant to policymakers seeking to harmonize testing standards, enhance consumer safety, and promote regulatory alignment across jurisdictions. As more data becomes available, the framework can be expanded to support broader policy development and cross-state collaboration.

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