The Regulatory Framework Across International Jurisdictions for Risks Associated with Consumption of Botanical Food Supplements
Bibliographic record
Abstract
Dietary supplements, including those containing botanical ingredients and botanical-derived compounds, have been marketed to consumers globally for many decades. However, the legislative framework for such products remains inconsistent across jurisdictions internationally. This study aims to compare the regulatory framework of botanical food supplements in the EU, USA, Canada, Australia, New Zealand, India, Japan, and China. The study also aims to investigate and describe safety assessment criteria for botanical food supplements where they are present in the above said jurisdictions, and attempts to analyze whether these criteria are suitable for addressing the toxicological risks associated with the use of botanical food supplement products, based on the evaluation of reported adverse effects related to botanical food supplement use as examples. Finally, this study discusses some future issues that need further attention, such as the consideration of less than lifetime exposures, potential for misidentification, and adulteration of botanical supplements by pharmacologically active substances. It is concluded that the regulatory approaches towards botanical food supplements differ significantly across jurisdictions. In addition, national authorities are increasingly considering having more regulatory oversight for such products. Further consideration of the actual impact of adverse events arising from botanical food supplement usage will be helpful in guiding such decisions.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.028 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".