Overview of ATX-101 (Deoxycholic Acid Injection): A Nonsurgical Approach for Reduction of Submental Fat
Bibliographic record
Abstract
In 2015, ATX-101 (deoxycholic acid injection; Kybella in the United States and Belkyra in Canada; Kythera Biopharmaceuticals, Inc., Westlake Village, CA [an affiliate of Allergan plc, Dublin, Ireland]) was approved as a first-in-class injectable drug for improvement in the appearance of moderate to severe convexity or fullness associated with submental fat. ATX-101 has been evaluated in a clinical development program that included 18 Phase 1 to 3 studies supporting the current indication. Since 2007, the toxicity and safety profiles of ATX-101 have been characterized in numerous preclinical studies, its pharmacokinetics, pharmacodynamics, and optimal treatment paradigm have been defined in multiple Phase 1 and 2 studies, and its efficacy and clinical safety have been confirmed in 4 large Phase 3 trials (2 conducted in Europe and 2 in the United States and Canada [REFINE-1 and REFINE-2]). As subcutaneous injection of deoxycholic acid has been shown to cause adipocytolysis, the reduction in submental fat achieved after ATX-101 treatment is expected to be long lasting. This prediction is confirmed by data from long-term follow-up studies of up to 4 years after last treatment with ATX-101, which demonstrate that the treatment response is maintained over time in most subjects. ATX-101 offers a durable, minimally invasive alternative to liposuction and surgery for addressing submental fullness.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.005 |
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".