为何药品名称变得如此怪异？对四十年FDA批准中专有名称与通用名正字法独特性的一项回顾性分析

doi: https://doi.org/10.64898/2026.10.15.26365645

Abstract

Background. Regulatory pressure to avoid confusingly similar drug names appears to have pushed manufacturers to coin more distinctive proprietary names, but no one has quantitatively analyzed this trend. Objective. To determine whether proprietary drug names became more orthographically distinctive (unusual in spelling) over time. Methods. We examined 1,321 US Food and Drug Administration (FDA) new molecular entity (NME) names (1985-2024), 2,769 FDA Orange Book trade names (1982-2026), 177,337 US pharmaceutical trademarks (1980-2026), and 1,273 generic names (1982-2025). Compared to prior names (including those already marketed) and ordinary English, we scored each name's character trigram (three-letter sequence) surprisal (statistical unexpectedness) and its edit-distance similarity to the closest existing names. Linear regression tested time trends, controlling for name length. Results. Mean NME trigram surprisal rose in every decade between the 1980s and 2020s, from 7.21 to 8.50 nats (natural-logarithm units, higher meaning less predictable), an 18% increase (b = 0.038, p < .001, R2 = 0.34). Half of 2020s names (7% in the 1980s) contained a letter sequence found in no common English word (e.g., Jesduvroq, Omvoh). Nearest-neighbor similarity fell after the early 1990s. Trademark data showed the same trend (b = 0.016, p < .001). Generic names showed a weaker trend (b = 0.011, R2 = 0.063). Conclusions. Over four decades, drug names became more orthographically distinctive, consistent with namespace crowding, deliberate efforts to avoid confusing names, and branding strategy. Because unfamiliar letter sequences can introduce other error pathways, increased distinctiveness does not necessarily imply improved safety.

Competing Interest Statement

The authors have declared no competing interest.

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Data Availability

All data analyzed in this study are publicly available. Proprietary drug names were obtained from the FDA Center for Drug Evaluation and Research Compilation of New Molecular Entity (NME) Drug and New Biologic Approvals, 1985-2024 (https://www.fda.gov/drugs/drug-approvals-and-databases/compilation-cder-new-molecular-entity-nme-drug-and-new-biologic-approvals). Trade names and generic ingredient names were obtained from the FDA Orange Book data files, Products file (https://www.fda.gov/drugs/drug-approvals-and-databases/orange-book-data-files). Both FDA files were downloaded in February 2026. Pharmaceutical trademarks (International Class 005) were extracted from the US Patent and Trademark Office Trademark Full-Text XML Data, Applications, product TRTYRAP, annual back file, 2025 edition (files dated December 31, 2025, downloaded February 2026), which contains applications filed through February 9, 2026 (https://data.uspto.gov/bulkdata/datasets/trtyrap). English word frequencies were obtained from the wordfreq library, version 3.1.1 (Speer R., 2023, https://pypi.org/project/wordfreq/3.1.1/, archived versions at https://doi.org/10.5281/zenodo.595730). The analysis code, the USPTO extraction code, the FDA source files as downloaded, the extracted USPTO Class 005 records, and the scored name-level datasets for all four datasets (primary and unaugmented baselines), together with the lists of Orange Book entries excluded as not being trade names, are deposited in Zenodo (https://doi.org/10.5281/zenodo.23196771).

https://doi.org/10.5281/zenodo.23196771

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