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Creating Matched In vivo/In vitro Patient-Derived Model Pairs of PDX and PDX-Derived Organoids for Cancer Pharmacology Research
Published on: May 5, 2021
Look-alike, sound-alike drugs in oncology
Laurel Kovacic1, Carole Chambers
1University of Washington, Seattle, Washington, USA. laurelk@bccancer.bc.ca
Background:
Medication errors with oncology drugs can place cancer patients at risk for adverse events or death. Look-alike, sound-alike (LASA) drug names may increase the risk for errors. Published lists of LASA drug names are generally a result of voluntarily reported medication incidents. This study performed a proactive review of the oncology drug formulary from the Cancer Services of the Alberta Health Services for LASA drug pairs.
Methods:
The Levenshtein Distance and Bigram Similarity algorithms, same first and last letters, and Lexi-Comp(R) on-line alerts were used to review the outpatient oncology formulary to identify potential LASA generic drug name pairs.
Results:
indicate there are more potential LASA generic drug name pairs in the oncology formulary than are published in the literature. The risk detection methods used in this study identified unique and common LASA drug pairs. The Bigram Similarity algorithm identified 186 LASA drug pairs from 3320 possible pairs. The Levenshtein Distance algorithm, same first and last letters, and Lexi-Comp(R) methods identified 42, 75, and 38 LASA drug pairs, respectively. Five generic LASA drug pairs were identified in common by all four of the risk determination methods.
Discussion:
LASA drug pairs identified by three or four methods were considered to provide the highest risk for errors. A step-wise approach to risk reduction, dependent on the number of detection methods identifying a pair, is presented.
Conclusion:
For specialty areas of practice, a proactive system of reviewing LASA drug name pairs may be warranted for increasing medication safety.
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