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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.006 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".