Semaglutide: First Global Approval
Bibliographic record
Abstract
Compliance with Ethical Standards Funding: The preparation of this review was not supported by any external funding. Conflicts of interest: During the peer review process the manufacturer of the agent under review was offered an opportunity to comment on the article. Changes resulting from any comments received were made by the authors on the basis of scientific completeness and accuracy. Sohita Dhillon is a salaried employee of Adis/Springer, is responsible for the article content and declares no relevant conflicts of interest Additional information about this Adis Drug Review can be found here. Abstract Novo Nordisk has developed a subcutaneous formulation of semaglutide (Ozempic®), a modified human glucagon-like peptide-1 (GLP-1) analogue, for the treatment of type 2 diabetes mellitus. It has been developed using Novo Nordisk's proprietary protein-acylation technology, and is administered using an injection device. Semaglutide lowers blood glucose by stimulating the release of insulin and also lowers body weight. Once-weekly subcutaneous semaglutide has recently been approved in the US, Puerto Rico and Canada, and has received a positive opinion in the EU for the treatment of patients with type 2 diabetes. It will be launched as the Ozempic® Pen, a pre-filled device. Semaglutide is also under regulatory review in Japan and Switzerland for the treatment of type 2 diabetes. Clinical development for obesity, non-alcoholic steatohepatitis and non-alcoholic fatty liver disease is underway worldwide. This article summarizes the milestones in the development of semaglutide leading to this first approval for type 2 diabetes. Access to the full article can be found here. © Springer International Publishing AG, part of Springer Nature 2018
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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 | 0.017 | 0.060 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.007 | 0.005 |
| Insufficient payload (model declined to judge) | 0.272 | 0.165 |
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".