Survodutide for treatment of obesity: rationale and design of two randomized phase 3 clinical trials (<scp>SYNCHRONIZE™</scp>‐1 and ‐2)
Bibliographic record
Abstract
Abstract Objective The objective of this study was to describe the rationale and design of two multinational phase 3 clinical trials of survodutide, an investigational glucagon and glucagon‐like peptide‐1 receptor dual agonist for the treatment of obesity with or without type 2 diabetes (T2D; SYNCHRONIZE‐1 and ‐2). Methods In these ongoing double‐blind trials, participants were randomized to once‐weekly subcutaneous injections of survodutide or placebo added to lifestyle modification. Survodutide doses are uptitrated to 3.6 or 6.0 mg, and dose flexibility is permitted. Participants ( n = 726) in SYNCHRONIZE‐1 (NCT06066515) have a baseline BMI ≥ 30 kg/m 2 or ≥27 kg/m 2 with at least one obesity‐related complication but without T2D; participants ( n = 755) in SYNCHRONIZE‐2 (NCT06066528) have a baseline BMI ≥ 27 kg/m 2 and T2D. The primary endpoints are percentage change in body weight and proportion of participants achieving ≥5% body weight reduction from baseline to week 76. Secondary endpoints include change in systolic blood pressure and measures of glycemia. A SYNCHRONIZE‐1 substudy is evaluating changes in body composition and liver fat content using magnetic resonance imaging. Conclusions These trials are designed to provide robust evaluation of the efficacy, safety, and tolerability of survodutide for the treatment of obesity in the presence or absence of T2D.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.071 | 0.037 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.007 | 0.006 |
| Insufficient payload (model declined to judge) | 0.007 | 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".