Real GLP-1 weight loss is not a straight line. It starts slow through titration, accelerates, then flattens into a plateau, and where your plateau sits depends on far more than the drug. This models the true curve from the published trials, then re-fits it to your own early response.
Age, height and starting weight are the minimum. Everything else sharpens the projection, and the model tells you which input would help most.
The model fits a titration-weighted exposure term, then solves each drug and dose so its curve passes exactly through the trial endpoint that was actually published, rather than assuming a straight path toward some target. The sub-linear exponent inside that exposure term is what reproduces a real published finding: semaglutide at 1.0 mg does not deliver 42% of the loss seen at 2.4 mg, it delivers closer to two-thirds of it. Straight-line calculators cannot represent that relationship at all.
Every multiplier applied to your projection, sex, diabetes status, prior GLP-1 exposure, baseline BMI, age and lifestyle effort, is taken from a subgroup result reported within the same trial programmes rather than an assumed adjustment. Type 2 diabetes status is the largest single factor, which matches the STEP 2 cohort losing meaningfully less than the STEP 1 cohort at the same dose. If your dose is still titrating, cross-check the schedule against the GLP-1 Titration Engine.
Once you are far enough into treatment to enter a real data point, the tool solves for your individual plateau rather than reporting the trial average, and the uncertainty band tightens considerably as a result. This mirrors the same personal-calibration idea used in the TRT Dose Finder, where a single real measurement narrows a wide population estimate down to something specific to you.
Because that is not how GLP-1 weight loss actually happens. It starts slow through dose titration, accelerates, then flattens into a plateau as your body reaches a new equilibrium. This tool models that exponential approach to a plateau directly, calibrated so the curve passes through the actual endpoint each trial reported at its own timepoint, rather than drawing a straight line to an assumed target.
Semaglutide 2.4 mg against STEP 1 (14.85% at week 68), tirzepatide 5/10/15 mg against SURMOUNT-1 (15.0/19.5/20.9% at week 72), retatrutide 12 mg against its Phase 2 data (24.2% at week 48, investigational), and liraglutide 3.0 mg against SCALE (8.0% at week 56). The personalisation multipliers, such as the 0.65x adjustment for type 2 diabetes, come from published subgroup results within those same trial programmes.
Your own early response is a stronger predictor of your eventual outcome than any population average. Once you enter how many weeks you have been on the drug and your current weight, the tool re-fits the entire curve to your actual trajectory rather than the trial average, which roughly halves the uncertainty band once you are far enough into titration, generally by week 12 to 16.
Yes. It splits projected loss into fat and lean mass using published DEXA substudy figures that differ by drug (roughly 40% lean for semaglutide, 26% for tirzepatide), then adjusts that split based on your resistance training frequency and protein intake. The output shows how much of what you'd lose is muscle, not only the number on the scale.
The STEP 1 extension data found participants regained about two-thirds of their lost weight within a year of stopping. The tool applies that figure to your specific projected loss so you can see the regain in your own units, which is part of why it frames this as a long-term intervention rather than a course to complete.
