Simulations Plus (SLP) investor relations material

Overview 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.