Simulations Plus (SLP) Status update summary
Event summary combining transcript, slides, and related documents.
Status update summary
23 Jun, 2026Overview of OBESITYsym model and its applications
OBESITYsym is a mechanistic QSP model designed to predict weight loss and nausea in obesity treatments, integrating calorie balance and pharmacologic effects across various drug modalities.
The model is built using proprietary software (Thales), enabling simulation and prediction for both injected and oral medications, including semaglutide, liraglutide, tirzepatide, Orforglipron, and retatrutide.
OBESITYsym can translate preclinical data to first-in-human predictions and is expandable to accommodate new mechanisms and targets.
The model accounts for genetic and phenotypic variability, simulating diverse patient populations and integrating both pathophysiology and pharmacology.
Recent advances include discrete populations for type 2 diabetes and MASH, supporting simulation of metabolic syndrome beyond obesity alone.
Model methodology and validation
The model uses a mechanistic approach, integrating energy intake, expenditure, and pharmacologic effects, with simulated populations reflecting inter-patient variability.
Calibration and validation are performed using clinical trial data, with robust agreement between simulated and observed outcomes for weight loss and nausea across multiple drugs and dosing regimens.
The model supports complex dosing protocols and can simulate various uptitration schedules to optimize treatment strategies.
Translational predictions leverage potency ratios from in vitro studies to inform in vivo outcomes, aiding early clinical development.
The iterative modeling-data collection process enables rapid adaptation to new clinical data and evolving treatment paradigms.
Application to novel treatments and mechanistic insights
OBESITYsym was used to dissect the contributions of food intake reduction and energy expenditure in retatrutide, a GLP-GIP-GCG triple agonist, quantifying the glucagon receptor's effect on energy expenditure.
The model accurately predicted weight loss outcomes in recent TRIUMPH phase III studies for retatrutide, validating its translational capability.
Nausea prediction is robust, though ongoing data collection will further refine the model's ability to capture adverse event profiles.
Mechanistic differences in weight loss between obese and type 2 diabetic populations are modeled, including factors like urinary glucose excretion.
The platform is adaptable to new drug classes and mechanisms, provided sufficient clinical data are available for calibration.
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