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Answer :
The using of compound-by-compound testing procedure with α=0.05, approximately 5,000 compounds would be indicated as effective, even though none of the compounds in reality produce beneficial results.
Modern combinatorial chemistry allows drug researchers to explore millions of products when searching for the next big pharmaceutical drug. This technique involves investigating hundreds of thousands of compounds to identify potential candidates for further study.
In this scenario, let's assume that none of the 100,000 compounds actually produce beneficial results. However, using a compound-by-compound testing procedure with a significance level (α) of 0.05, some compounds may still be identified as effective.
With an α of 0.05, we can interpret this as a 5% chance of incorrectly rejecting the null hypothesis, which states that a compound is not effective. This means that, on average, we would expect 5% of the tested compounds to be falsely identified as effective, even if they are not.
To calculate the number of compounds that would be indicated as effective, we can multiply the total number of compounds (100,000) by the significance level (α) of 0.05.
Number of compounds indicated as effective = 100,000 * 0.05 = 5,000
Therefore, using the compound-by-compound testing procedure with α=0.05, approximately 5,000 compounds would be indicated as effective, even though none of the compounds in reality produce beneficial results.
This can potentially cause problems because it could lead researchers to invest time, resources, and money into further studying these false-positive compounds. It may divert attention from potentially more promising candidates and delay the discovery of a truly effective pharmaceutical drug. Therefore, it is crucial for researchers to carefully consider and validate the results obtained through combinatorial chemistry to avoid false-positive findings.
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