Proprietary Name Testing Using “Prescription Analysis Studies”

1. Proprietary Name Testing Using “Prescription Analysis Studies” Thomas H. Hassall, MS Director, Global Regulatory Policy Merck Research Laboratories

2. FDA’s Trademark Assessment Process • “Expert Panel” - DMETS staff panel identifies a pool of proprietary names with potential for confusion • “Prescription Analysis Studies” - to “determine the degree of confusion of the proposed name with other names due to handwriting or verbal pronunciation”1 • “Safety Evaluator Risk Assessment” - Considers similarities vs mitigating factors (population, dose, dosage form, regimen, route, consequence of error, other). This is a “judgment call.” 1. Quote from text of DMETS review

3. Summary of 17 FDA Prescription Analysis Studies • Initial Sample = 22 Reviews • 5 Did not perform RX Analysis --Remaining 17-- • 2002 (2); 2001 (8); 2000 (6); 1999 (1) • 9 different reviewers • Average time to completion = 60 days (range = 16 - 135 days)

4. Summary of 17 Prescription Analysis Studies • Sample Size/Response(%) and Outcome • Outpatient Written 33/60% 75% correct* • Inpatient Written 33/60% 56% correct* • Telephone 33/47% 23% correct* *most incorrect responses were phonetic misspelling of the name • In 13 of 17 studies (76%), no mix-up with an existing name occurred • In 4 studies, actual mis-identification occurred (2 acceptable; 2 unacceptable)

5. Reviewer Conclusions vs % Correct/Incorrect Responses

6. My Conclusions Prescription Analysis Studies… • Do not test names for the risk of medication error; • An incorrect response involving an existing name is not significant by itself; • Lack of an incorrect response involving an existing name is not significant by itself; • Do not “determine the degree of confusion of the proposed name with other names due to hand-writing or verbal pronunciation;” • Do not produce reliably reproducible results.

7. My Conclusions Prescription Analysis Studies… • Are useful screening tools that may enrich the pool of potentially confusing candidate names initially generated by the expert panel that will undergo the Safety Evaluator Risk Assessment; • Do not identify potential errors with a higher or lower risk for occurrence compared with other names in the pool identified by the expert panel;

8. My Conclusions • Recommendation #238 - HHS Advisory Committee on Regulatory Reform calls for - • FDA review of Manufacturer generated data from • Protocols designed to evaluate their products’ names for possible look-alike and sound-alike names; • FDA’s role should be to confirm that “GNP’s” (good naming practices) have been followed.

9. My Conclusions • The usefulness of any test or study that is purported to actually assess the risk of name confusion that may contribute to medication errors must be validated before it can be recommended for regulatory purposes.