Clinical trial success rates of anti‐obesity agents: the importance of combination therapies
Bibliographic record
Abstract
The objective of this study was to construct a clinical trial profile assessing the risk of drug failure among anti-obesity agents. Research was conducted by looking at anti-obesity therapies currently on the market or in clinical trials (phases I to III) conducted from 1998 to September 2014, with the exclusion of any drugs whose phase I trial was conducted prior to January 1998. This was completed primarily through a search on http://clinicaltrials.gov where a total of 51 drugs met the search criteria. The transition probabilities were then calculated based on various classifications and compared against industry standards. The transition probability of anti-obesity agents was 8.50% whereas the transition probability of industry standards was 10.40%. Combination therapies had four times the transition probability than monotherapies, 40% and 4.75%, respectively. Therefore, it was determined that 92% of drugs fail during clinical trial testing for this indication and combination therapy appears to improve clinical trial success rates to 10-fold.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.087 | 0.146 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".