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Interspecies modeling and prediction of human exenatide pharmacokinetics.

Pharm Res · 2013

Last updated 2026-05-28

Researchers used data from mice, rats, and monkeys to create a model that predicts how the diabetes drug exenatide behaves in humans. The model, which accounts for differences in body weight and drug absorption, accurately matched the drug's effects in animals and could estimate its behavior in people after both injection and subcutaneous administration.

AI summary of the abstract below.

JournalPharm Res, 2013
Citations31
Relative citation ratio1.20
NIH percentile57
Molecules exenatide

Abstract

PURPOSE: To develop a model-based approach for interspecies scaling of the preclinical pharmacokinetics of exenatide and to predict concentration-time profiles in humans. METHODS: A target-mediated drug disposition (TMDD) model was simultaneously fit to concentration-time profiles of exenatide over a wide range of intravenous (IV) and subcutaneous (SC) doses obtained from mice, rats, and monkeys. Allometric relationships were incorporated into the model to scale parameters based on species body weight. Human pharmacokinetic profiles following IV and SC administration were simulated using the final model structure and parameter estimates and compared to clinical data. RESULTS: The final model provided a good simultaneous fit to all animal data and reasonable parameter estimates. Exenatide receptor binding affinity and baseline receptor concentrations were species-dependent. Absorption parameters from rat provided the best prediction of exenatide SC absorption in humans, but good predictions could also be obtained using allometric scaling of preclinical absorption parameters. CONCLUSIONS: A TMDD model combined with allometric scaling was successfully used to simultaneously describe preclinical data for exenatide from three animal species following both IV and SC administration. The majority of model parameters could be shared among the animal species and further used for projecting exenatide behavior in humans.

Verbatim abstract via PubMed 23229855 ↗

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