A U.S. Pharmacopeia (USP) overview of Pan American botanicals used in dietary supplements and herbal medicines
Bibliographic record
Abstract
The United States Pharmacopeial Convention (USP) is a nonprofit, scientific, standard-setting organization, and world leader in establishing quality, purity, and testing standards for medicines, foods, and dietary supplements. USP quality standards are used in more than 140 countries and are legally recognized by more than 40 countries. Currently, there is renewed interest in herbal medicines globally, and health policies are being implemented worldwide for the use of complementary and traditional medicine. In response, USP has developed a robust body of monographs that can be used to guide industry and regulators in ensuring the quality and safety of botanical ingredients used in dietary supplements and herbal medicines. Throughout the Pan American regions, there is a strong tradition of using botanicals as herbal medicines and, as in other regions, a growing desire for botanical dietary supplements. This underscores the need for public quality standards to ensure quality, reduce the flow of substandard and adulterated products, and ensure public health and safety. In April 2022, USP launched the Pan America Botanical Dietary Supplements and Herbal Medicines Expert Panel, with experts representing 12 different countries. The Expert Panel's work focuses on developing quality control standards for the most important botanical ingredients used in the respective countries, ingredients that are also of global importance. This article provides an overview of the state of botanical dietary supplements and herbal medicines in different Pan American regions with a focus on the regulatory status of herbal products, the development of national quality and research initiatives, and policies related to agriculture conservation and sustainability, among other topics.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".