Systems Biology & Pharmacology
This is the mechanistic core of the catalog — datasets where the data doesn't just describe a biological process, it comes directly out of solving the equations that govern it. A sepsis trajectory here is the output of a real inflammatory-response model from the systems-biology literature. A drug-concentration curve is the output of a real pharmacokinetic compartmental model, coupled to a model of how failing kidneys and liver change clearance over time.
Because the model is explicit, so is the ground truth: the true drug clearance, the true tipping point between survival and death, the true parameter values — all known exactly, and all checked, wherever a published number exists, against that number. Some of those checks land inside the published range. At least one lands only halfway there, and we say so plainly rather than quietly rerunning it until it matched.
What you'll typically find here
- Physiological ODE models — inflammatory response, hemodynamics, organ function — integrated as real differential equations, not curve-fit approximations.
- Pharmacokinetic and pharmacodynamic datasets — dosing, clearance, and exposure data with the true underlying parameters attached, something no real clinical dataset can offer.
- Reference constant packs — standalone, citation-verified parameter sets for building or checking your own models, sold on their own or bundled with a full dataset.
Every number in every model carries a tag: confirmed from the literature, calibrated against it, or an engineering estimate we made and are telling you about. Nothing is presented as measured when it was assumed.