Gene

Leptin

Algorithm

Biology

Messenger RNA

Statistics

Endocrinology

Receptor

Computation

Biochemistry

Neuropeptide

Computer science

Parametric model

Scaling

Computational biology

Translation (biology)

Translational research

Mathematics

Internal medicine

Melanin-concentrating hormone

Artificial intelligence

Geometry

Parametric statistics

Antagonist

Medicine

Obesity

Biological system

Machine learning

Pathology

CPT Pharmacometrics & Systems Pharmacology

In this study, we present the translational modeling used in the discovery of AZD1979, a melanin‐concentrating hormone receptor 1 (MCHr1) antagonist aimed for treatment of obesity. The model quantitatively connects the relevant biomarkers and thereby closes the scaling path from rodent to man, as well as from dose to effect level. The complexity of individual modeling steps depends on the quality and quantity of data as well as the prior information; from semimechanistic body‐composition models to standard linear regression. Key predictions are obtained by standard forward simulation (e.g., predicting effect from exposure), as well as non‐parametric input estimation (e.g., predicting energy intake from longitudinal body‐weight data), across species. The work illustrates how modeling integrates data from several species, fills critical gaps between biomarkers, and supports experimental design and human dose‐prediction. We believe this approach can be of general interest for translation in the obesity field, and might inspire translational reasoning more broadly.

Translational Modeling to Guide Study Design and Dose Choice in Obesity Exemplified by AZD1979, a Melanin‐concentrating Hormone Receptor 1 Antagonist