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. 2023 Nov;25(11):3171-3180.
doi: 10.1111/dom.15211. Epub 2023 Jul 9.

A model-based approach to predict individual weight loss with semaglutide in people with overweight or obesity

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A model-based approach to predict individual weight loss with semaglutide in people with overweight or obesity

Anders Strathe et al. Diabetes Obes Metab. 2023 Nov.

Abstract

Aims: To determine the relationship between exposure and weight-loss trajectories for the glucagon-like peptide-1 analogue semaglutide for weight management.

Materials and methods: Data from one 52-week, phase 2, dose-ranging trial (once-daily subcutaneous semaglutide 0.05-0.4 mg) and two 68-week phase 3 trials (once-weekly subcutaneous semaglutide 2.4 mg) for weight management in people with overweight or obesity with or without type 2 diabetes were used to develop a population pharmacokinetic (PK) model describing semaglutide exposure. An exposure-response model describing weight change was then developed using baseline demographics, glycated haemoglobin and PK data during treatment. The ability of the exposure-response model to predict 1-year weight loss based on weight data collected at baseline and after up to 28 weeks of treatment, was assessed using three independent phase 3 trials.

Results: Based on population PK, exposure levels over time consistently explained the weight-loss trajectories across trials and dosing regimens. The exposure-response model had high precision and limited bias for predicting body weight loss at 1 year in independent datasets, with increased precision when data from later time points were included in the prediction.

Conclusion: An exposure-response model has been established that quantitatively describes the relationship between systemic semaglutide exposure and weight loss and predicts weight-loss trajectories for people with overweight or obesity who are receiving semaglutide doses up to 2.4 mg once weekly.

Keywords: GLP-1 analogue; clinical trial; dose-response relationship; pharmacodynamics; pharmacokinetics; semaglutide.

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