Prescription Drug Importation: An Expanded FDA Personal Use Exemption and Qualified Regulators for Foreign-Produced Pharmaceuticals
Bibliographic record
Abstract
High-priced prescription drugs have been a problem for U.S. consumers. The United States market economy coupled with patent protection for these products creates an incentive for pharmaceutical companies to charge as much as possible. Unable to afford these drugs, many people are reaching out to neighboring countries and abroad to seek lower-cost options. It has also created a market for online mail-order pharmaceuticals. Despite the need for these drugs, the Food and Drug Administration (“FDA”) continues to make importation illegal. In formulating its policy, the FDA cites to safety and innovation concerns. Claimed uncertainty about the source of foreign prescription drugs has led to ineffective federal policy in this area. To date, none of the major amendments to the Food, Drug, and Cosmetic Act have successfully provided a framework for securing foreign importation. Without proper federal guidance, various states, including Maine, have implemented legislation to facilitate the importation of prescription drugs from other developed countries like Canada and England. This Article proposes two potential solutions to implement policy on the federal level. With an eye towards Maine’s new law and its successes, there is potential for an expanded, codified personal use exemption. Moreover, using “qualifying” countries, or those with an adequate level of manufacturing oversight for prescription drugs, may provide an alternative safeguard for allowing importation.
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 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 | 0.015 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.029 | 0.010 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".