Development of the measures to evaluate the similarity of drug brand names

Hisakazu Ohtani, Masayuki Takeda, Yuki Imada, Yasufumi Sawada

Research output: Contribution to journalArticlepeer-review

5 Citations (Scopus)

Abstract

Brand name confusion is one of the most common causes of drug-related errors. The aim of this study was to develop quantitative measures of similarity among brand names of drugs. We modified the fragmentary pattern-based measure, a measure of similarity for character strings based on the string resemblance system, to develop three novel measures of similarity, i.e., the head and tail-weighted fragmentary pattern-based measure (htfrag), visually weighted htfrag (vwhtfrag), and auditorily weighted htfrag (awhtfrag). The 227 pairs of brand names for which confusion errors have been reported were used as a positive control group. Ten sets of 2270 random pairs of brand names were generated as negative controls. Then we evaluated the measures developed by using the geometric mean of sensitivity and selectivity as an objective function, in comparison with two conventional measures of similarity based on the vector space model (cos1 and htco). The measures developed, htfrag, vwhtfrag, and awhtfrag, provided better discrimination with mean objective function values of 0.953, 0.962, and 0.940, respectively, which were higher than those for the conventional measures cos1 and htco (0.922 and 0.892, respectively). The rates of false-positives and false-negatives were 3.3 - 10.7 % and 5.3 - 11.9% for cos1, respectively, while the rates for vwhtfrag were 4.8 - 5.9% and 2.2%, respectively. The measures of similarity developed may provide significant information to avoid drug-related errors associated with brand name confusion.

Original languageEnglish
Pages (from-to)349-356
Number of pages8
JournalYakugaku Zasshi
Volume126
Issue number5
DOIs
Publication statusPublished - May 1 2006

All Science Journal Classification (ASJC) codes

  • Pharmacology
  • Pharmaceutical Science

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