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Zorluk: OrtaIdentifying Main Conclusions

Recent advancements in artificial intelligence allow pharmaceutical companies to screen billions of candidate molecules in virtual simulations, significantly accelerating early-stage drug discovery. Consequently, many industry analysts predict that total drug development costs will fall dramatically over the next decade. However, high-throughput computational screening frequently generates false positives—molecules that appear promising in simulations but fail during late-stage human clinical trials, where the vast majority of R&D budgets are consumed. Therefore, contrary to industry expectations, total pharmaceutical research expenditures are unlikely to decline significantly without major innovations in clinical trial methodology.

Which of the following best expresses the main conclusion of the argument above?

  1. A
    Total drug development costs will fall dramatically over the next decade due to artificial intelligence.
  2. B
    Late-stage human clinical trials account for the vast majority of pharmaceutical research and development budgets.
  3. Total pharmaceutical research expenditures are unlikely to decline significantly without major innovations in clinical trial methodology.Cevap
  4. D
    High-throughput computational screening models frequently produce false positives that appear viable only in virtual simulations.
  5. E
    Pharmaceutical companies should suspend the use of AI screening tools until clinical trial methodologies become more accurate.

Cevap

Total pharmaceutical research expenditures are unlikely to decline significantly without major innovations in clinical trial methodology.
The author constructs an argument designed to counter a popular industry prediction. After describing how AI speeds up initial molecule screening, the author introduces a pivot with 'However', explaining that false positives still lead to costly late-stage trial failures. The main conclusion, signaled by 'Therefore', is that total R&D spending will not decrease significantly unless clinical trial methods are fundamentally improved.

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1
Identify the background context and the opposing claim.
The argument begins by acknowledging that AI accelerates early drug discovery, leading analysts to predict a major drop in overall development costs.
Establishing the prevailing industry belief sets up the counter-position that the author intends to challenge.
2
Locate the structural pivot and key supporting premise.
The transition word 'However' introduces the fact that AI models produce false positives that fail in expensive late-stage clinical trials.
This premise explains why early-stage speed gains do not automatically reduce total expenditures.
3
Identify the main conclusion introduced by the conclusion marker.
The keyword 'Therefore' signals the author's ultimate claim: total spending is unlikely to drop significantly without major clinical trial innovations.
This claim synthesizes the evidence to refute the initial prediction made by industry analysts.

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Identifying Main Conclusions
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Identifying Main Conclusions

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